Crédito — Risk Intelligence (mock)

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margin: 0; padding: 0; }\nhtml, body { height: 100%; }\nbody { font-family: var(--font); background: var(--bg-app); color: var(--text); font-size: 13px; }\n.num { font-variant-numeric: tabular-nums; }\n\n/* ---------- Header global ---------- */\n.app-header {\n display: flex; align-items: center; gap: 16px;\n padding: 10px 24px; background: var(--bg-app);\n}\n.brand { font-weight: 800; font-size: 18px; color: var(--secondary); letter-spacing: 0.5px; }\n.brand small { display: block; font-size: 8px; font-weight: 600; letter-spacing: 2px; color: var(--text-2); }\n.tenant {\n display: flex; align-items: center; gap: 8px; background: var(--surface-container);\n border: 1px solid var(--border); border-radius: var(--radius-card); padding: 8px 12px;\n font-weight: 600; font-size: 13px;\n}\n.modules {\n margin: 0 auto; display: flex; gap: 4px; background: var(--surface-container);\n border-radius: 16px; padding: 6px; box-shadow: 0 1px 3px rgba(31,42,78,0.08);\n}\n.module-tab {\n display: flex; flex-direction: column; align-items: center; gap: 2px;\n padding: 8px 22px; border-radius: 12px; font-size: 11px; font-weight: 600;\n color: var(--text-2); border: none; background: transparent; cursor: default; font-family: var(--font);\n}\n.module-tab .mico { font-size: 15px; }\n.module-tab.active { background: var(--primary); color: #fff; }\n.module-tab.disabled { color: var(--border); }\n.header-right { display: flex; align-items: center; gap: 14px; }\n.avatar {\n width: 36px; height: 36px; border-radius: var(--radius-card); background: var(--secondary);\n color: #fff; display: flex; align-items: center; justify-content: center; font-weight: 700; font-size: 12px;\n}\n.hicon { color: var(--secondary); font-size: 16px; }\n\n/* ---------- Layout ---------- */\n.app-body { display: flex; align-items: flex-start; }\n.sidebar { width: 232px; flex-shrink: 0; padding: 8px 12px 24px 24px; }\n.sidebar h1 { font-size: 26px; font-weight: 800; color: var(--secondary); margin: 6px 0 18px 6px; }\n.menu-item {\n display: flex; align-items: center; gap: 10px; width: 100%;\n padding: 11px 14px; margin-bottom: 2px; border: none; background: transparent;\n border-radius: var(--radius-panel); font-family: var(--font); font-size: 13.5px; font-weight: 500;\n color: var(--text); cursor: pointer; text-align: left;\n}\n.menu-item:hover { background: var(--hover); }\n.menu-item.active { background: var(--surface-container); font-weight: 600; box-shadow: 0 1px 3px rgba(31,42,78,0.10); }\n.menu-item .ico { width: 18px; text-align: center; color: var(--secondary); }\n.main {\n flex: 1; background: var(--surface-container); border-radius: var(--radius-container);\n margin: 0 24px 24px 0; padding: 20px 24px 28px; min-height: 86vh; min-width: 0;\n}\n\n/* ---------- Cabecera de sección (badges FUERA de paneles skeletonizables — X-2) ---------- */\n.section-head { display: flex; align-items: flex-start; justify-content: space-between; gap: 16px; flex-wrap: wrap; }\n.breadcrumb { display: flex; align-items: center; gap: 8px; font-size: 14px; padding-top: 6px; }\n.breadcrumb .home { color: var(--secondary); }\n.breadcrumb .sep { color: var(--text-2); }\n.breadcrumb .leaf { font-weight: 600; }\n.head-badges { display: flex; align-items: center; gap: 10px; flex-wrap: wrap; justify-content: flex-end; }\n.badge-supuesto {\n display: inline-flex; align-items: center; gap: 6px;\n background: var(--surface-card); border: 1px solid var(--border);\n border-radius: 999px; padding: 7px 14px; font-size: 12px; color: var(--text-2); font-weight: 500;\n}\n.badge-supuesto .lbl { font-weight: 700; color: var(--secondary); }\n.badge-data {\n display: inline-flex; align-items: center; gap: 8px; background: var(--surface-card);\n border-radius: var(--radius-card); padding: 8px 14px; font-size: 13px;\n}\n.badge-data b { font-weight: 700; }\n.badge-data.warn { background: var(--fondo-alerta); color: var(--sem-warn); }\n.badge-data.err { background: var(--fondo-error); color: var(--sem-error); }\n.dataset-select, .btn-filtros {\n display: inline-flex; align-items: center; gap: 8px; background: var(--surface-container);\n border: 1px solid var(--border); border-radius: var(--radius-card); padding: 8px 14px;\n font-family: var(--font); font-size: 13px; cursor: pointer;\n}\n.btn-filtros { font-weight: 600; }\n.btn-filtros .count {\n background: var(--primary); color: #fff; border-radius: 999px;\n font-size: 10px; width: 16px; height: 16px; display: inline-flex; align-items: center; justify-content: center;\n}\n\n/* ---------- Tabs pill ---------- */\n.tabs-bar {\n display: inline-flex; gap: 6px; background: var(--surface-card);\n border-radius: 12px; padding: 6px; margin: 16px 0 18px;\n}\n.tab-pill {\n border: none; background: transparent; font-family: var(--font); font-size: 13px; font-weight: 600;\n color: var(--text-2); padding: 8px 20px; border-radius: var(--radius-card); cursor: pointer;\n}\n.tab-pill.active { background: var(--surface-container); color: var(--text); border: 1px solid var(--border); }\n\n/* ---------- Dashboard grid ---------- */\n.dash { display: grid; grid-template-columns: 230px 1fr; gap: 16px; align-items: start; }\n.kpi-col { display: flex; flex-direction: column; gap: 12px; }\n.kpi-card { background: var(--surface-card); border-radius: var(--radius-card); padding: 14px 16px; }\n.kpi-card h3 { font-size: 13px; font-weight: 700; margin-bottom: 6px; }\n.kpi-card .big { font-size: 21px; font-weight: 800; letter-spacing: -0.3px; }\n.kpi-card .sub { font-size: 10.5px; color: var(--text-2); margin-top: 3px; line-height: 1.35; }\n.kpi-card .rows { margin-top: 10px; display: flex; flex-direction: column; gap: 4px; }\n.kpi-card .row { display: flex; justify-content: space-between; font-size: 11.5px; color: var(--text-2); }\n.kpi-card .row b { color: var(--text); font-weight: 600; }\n.trend { font-weight: 700; color: var(--secondary); } /* Δ de riesgo/mezcla: neutro SIEMPRE (L-5/L-6) */\n.grid-2x2 { display: grid; grid-template-columns: 1fr 1fr; gap: 16px; min-width: 0; }\n.panel {\n background: var(--surface-container); border: 1px solid var(--border);\n border-radius: var(--radius-panel); padding: 14px 16px; min-width: 0; min-height: 300px;\n display: flex; flex-direction: column;\n}\n.panel-head { display: flex; align-items: center; justify-content: space-between; gap: 8px; margin-bottom: 8px; flex-wrap: wrap; }\n.panel-head h2 { font-size: 14.5px; font-weight: 700; }\n.chart-box { flex: 1; min-height: 230px; }\n.panel-foot { font-size: 10.5px; color: var(--text-2); margin-top: 8px; line-height: 1.4; }\n.seg {\n display: inline-flex; background: var(--surface-card); border-radius: var(--radius-card); padding: 3px; gap: 2px;\n}\n.seg button {\n border: none; background: transparent; font-family: var(--font); font-size: 11px; font-weight: 600;\n color: var(--text-2); padding: 5px 10px; border-radius: 6px; cursor: pointer;\n}\n.seg button.active { background: var(--surface-container); color: var(--text); border: 1px solid var(--border); }\n.select-mini {\n font-family: var(--font); font-size: 12px; border: 1px solid var(--border);\n border-radius: var(--radius-card); padding: 5px 8px; background: var(--surface-container);\n}\n\n/* ---------- Estado / pills ---------- */\n.pill { display: inline-flex; align-items: center; gap: 5px; border-radius: 999px; padding: 3px 10px; font-size: 11px; font-weight: 700; }\n.pill.ok { background: var(--fondo-ok); color: var(--sem-ok); }\n.pill.warn { background: var(--fondo-alerta); color: var(--sem-warn); }\n.pill.err { background: var(--fondo-error); color: var(--sem-error); }\n.pill.na { background: var(--surface-card); color: var(--text-2); border: 1px solid var(--border); }\n.chip-mon { display: inline-block; border: 1px solid var(--border); background: var(--surface-card); color: var(--text-2); border-radius: 4px; padding: 1px 7px; font-size: 10.5px; font-weight: 600; }\n\n/* ---------- Tabla ---------- */\n.tbl-wrap { flex: 1; overflow: auto; }\ntable.tbl { width: 100%; border-collapse: collapse; font-size: 12px; }\n.tbl th { text-align: right; font-weight: 700; padding: 7px 8px; border-bottom: 1px solid var(--border); white-space: nowrap; }\n.tbl th.gh { text-align: center; border-bottom: 1px solid var(--border); color: var(--text-2); font-size: 11px; }\n.tbl th:first-child, .tbl td:first-child { text-align: left; }\n.tbl td { padding: 7px 8px; border-bottom: 1px solid var(--surface-card); text-align: right; white-space: nowrap; }\n.tbl tr.grp td { font-weight: 700; cursor: pointer; }\n.tbl tr.grp:hover td { background: var(--hover); }\n.tbl tr.child td:first-child { padding-left: 26px; color: var(--text-2); }\n.tbl .caret { display: inline-block; width: 14px; color: var(--text-2); font-size: 10px; }\n.btn-export {\n border: 1px solid var(--border); background: var(--surface-container); border-radius: var(--radius-card);\n font-family: var(--font); font-size: 11.5px; font-weight: 600; padding: 5px 12px; cursor: pointer; color: var(--secondary);\n}\n\n/* ---------- Estados UI ---------- */\n.skeleton { border-radius: var(--radius-panel); background: var(--skeleton); animation: pulse 1.4s ease-in-out infinite; min-height: 300px; }\n.skeleton.sm { min-height: 96px; border-radius: var(--radius-card); }\n@keyframes pulse { 0%,100% { opacity: 1; } 50% { opacity: 0.55; } }\n@media (prefers-reduced-motion: reduce) { .skeleton { animation: none; } }\n.state-box { flex: 1; display: flex; flex-direction: column; align-items: center; justify-content: center; gap: 8px; text-align: center; padding: 20px; }\n.state-box .t { font-weight: 700; font-size: 13.5px; }\n.state-box .d { color: var(--text-2); font-size: 12px; max-width: 340px; line-height: 1.45; }\n.state-box .ic { font-size: 26px; }\n.btn-retry {\n margin-top: 6px; border: none; background: var(--primary); color: #fff; font-family: var(--font);\n font-weight: 600; font-size: 12px; padding: 8px 18px; border-radius: var(--radius-card); cursor: pointer;\n}\n\n/* ---------- Placeholder de sección ---------- */\n.placeholder-note {\n background: var(--surface-card); border: 1px dashed var(--border); border-radius: var(--radius-panel);\n padding: 34px; text-align: center; color: var(--text-2); margin-top: 8px;\n}\n.placeholder-note b { color: var(--secondary); display: block; font-size: 15px; margin-bottom: 6px; }\n\n/* ---------- Panel de filtros (derecho) ---------- */\n.filters-overlay { position: fixed; inset: 0; background: rgba(31,42,78,0.25); z-index: 40; }\n.filters-panel {\n position: fixed; top: 0; right: 0; bottom: 0; width: 320px; background: var(--surface-container);\n z-index: 41; padding: 20px; overflow-y: auto; box-shadow: -4px 0 16px rgba(31,42,78,0.15);\n}\n.filters-panel h2 { font-size: 16px; font-weight: 800; color: var(--secondary); margin-bottom: 14px; }\n.f-group { margin-bottom: 16px; }\n.f-group label { display: block; font-size: 11px; font-weight: 700; color: var(--text-2); margin-bottom: 5px; text-transform: uppercase; letter-spacing: 0.4px; }\n.f-group select, .f-group input {\n width: 100%; font-family: var(--font); font-size: 12.5px; border: 1px solid var(--border);\n border-radius: var(--radius-card); padding: 8px 10px; background: var(--surface-container);\n}\n.f-sep { border-top: 1px solid var(--border); margin: 14px 0; }\n.f-note { font-size: 10.5px; color: var(--text-2); line-height: 1.4; }\n\n/* ---------- Switcher de estado del prototipo ---------- */\n.proto-switch {\n position: fixed; bottom: 16px; right: 16px; z-index: 50;\n background: var(--secondary); color: #fff; border-radius: var(--radius-panel);\n padding: 10px 12px; box-shadow: 0 4px 14px rgba(31,42,78,0.35); font-size: 11px;\n}\n.proto-switch .t { font-weight: 700; margin-bottom: 6px; opacity: 0.8; }\n.proto-switch .opts { display: flex; gap: 4px; flex-wrap: wrap; }\n.proto-switch button {\n border: 1px solid rgba(255,255,255,0.3); background: transparent; color: #fff;\n font-family: var(--font); font-size: 10.5px; font-weight: 600; padding: 4px 9px; border-radius: 6px; cursor: pointer;\n}\n.proto-switch button.active { background: #fff; color: var(--secondary); }\n\n@media (max-width: 1100px) {\n .dash { grid-template-columns: 1fr; }\n .kpi-col { flex-direction: row; flex-wrap: wrap; }\n .kpi-card { flex: 1 1 180px; }\n .grid-2x2 { grid-template-columns: 1fr; }\n}\n\n/* F2.3 — Métricas de Riesgo */\n.seg-medida { margin-right: 6px; }\n.seg-medida button { font-weight: 600; min-width: 40px; }\n.seg button[disabled] { opacity: .45; cursor: not-allowed; }\n.mr-nota { grid-column: 1 / -1; margin-top: 10px; padding: 8px 12px; font-size: 11px; color: var(--text-2); background: var(--card-bg); border: 1px dashed var(--border); border-radius: var(--radius); }\n\n/* F2.10 — Backtesting */\n.chip-window { display: inline-flex; align-items: center; border: 1px solid var(--border); background: var(--surface-card); color: var(--text-2); border-radius: 999px; padding: 7px 12px; font-size: 11.5px; font-weight: 600; }\n.bt-val { flex: 1; display: flex; flex-direction: column; gap: 10px; overflow: auto; }\n.bt-winhead { font-size: 12px; font-weight: 700; color: var(--secondary); background: var(--surface-card); border-radius: var(--radius-card); padding: 7px 10px; }\n.bt-block { border: 1px solid var(--border); border-radius: var(--radius-card); padding: 9px 11px; }\n.bt-block h4 { font-size: 12px; font-weight: 700; margin-bottom: 4px; }\n.bt-nd { font-size: 13px; font-weight: 700; color: var(--text-2); }\n.bt-det { font-size: 10.5px; color: var(--text-2); margin-top: 4px; line-height: 1.4; }\n.badge-basilea { display: block; border-radius: 6px; border: 1px solid var(--border); border-left: 4px solid var(--text-2); background: var(--surface-card); padding: 7px 10px; margin-top: 4px; }\n.badge-basilea .z { display: block; font-size: 12.5px; font-weight: 800; }\n.badge-basilea .r { display: block; font-size: 9.5px; color: var(--text-2); margin-top: 2px; font-weight: 600; text-transform: uppercase; letter-spacing: 0.3px; }\n.badge-basilea.arch { border-left-color: var(--sem-ok); background: var(--fondo-ok); }\n.badge-basilea.arch .z { color: var(--sem-ok); }\n.bt-archived { border: 1px dashed var(--border); border-radius: var(--radius-card); padding: 9px 11px; opacity: 0.78; }\n.bt-arch-rot { font-size: 10px; font-weight: 800; text-transform: uppercase; letter-spacing: 0.4px; color: var(--text-2); margin-bottom: 4px; }\n.bt-arch-sub { font-size: 11px; color: var(--text-2); margin-bottom: 6px; }\n.bt-arch-grid { display: grid; grid-template-columns: auto auto 1fr; gap: 3px 10px; font-size: 11.5px; align-items: baseline; }\n.bt-arch-grid b { font-weight: 700; }\n.bt-arch-grid .num { color: var(--text-2); font-size: 10.5px; }\n.bt-sub2 { font-size: 10.5px; color: var(--text-2); line-height: 1.4; margin: -2px 0 6px; }\n.bt-sub2 b { font-weight: 700; }\n.tbl tr.bt-out td { color: var(--text-2); opacity: 0.62; }\n\n/* F2.8 — Factores de Riesgo: subtítulo anti-Gauss del panel TR (cuerpo capturable, no tooltip — X-#2) */\n.fr-sub { font-size: 11px; font-style: italic; color: var(--text-2); padding: 4px 14px 0; }\n\n/* F2.7 — Visión General (arquetipo overview §11) */\n.ov { display: flex; flex-direction: column; gap: 16px; }\n.ov-cards { display: grid; grid-template-columns: repeat(4, 1fr); gap: 14px; }\n.ov-card { min-height: 170px; }\n.ov-card .rows { margin-top: 8px; }\n.ov-mid { display: grid; grid-template-columns: 1.9fr 1fr 1fr; gap: 14px; align-items: stretch; }\n.ov-mid .panel { min-height: 320px; }\n.ov-limits .tbl td, .ov-limits .tbl th { font-size: 11px; padding: 7px 6px; }\n.ov-limits .tbl td:first-child { white-space: normal; }\n.ov-limits .pill { padding: 2px 7px; font-size: 10px; }\n.ov-nav { display: grid; grid-template-columns: repeat(4, 1fr); gap: 14px; }\n.nav-card {\n background: var(--surface-card); border: 1px solid transparent; border-radius: var(--radius-card);\n padding: 13px 15px; text-align: left; font-family: var(--font); cursor: pointer;\n display: flex; flex-direction: column; gap: 5px; min-height: 120px;\n transition: box-shadow .12s ease, transform .12s ease;\n}\n.nav-card:hover { box-shadow: 0 4px 14px rgba(31,42,78,0.16); transform: translateY(-2px); border-color: var(--border); background: var(--surface-container); }\n.nav-card h4 { font-size: 12.5px; font-weight: 700; color: var(--secondary); }\n.nav-card .nv-big { font-size: 14.5px; font-weight: 800; letter-spacing: -0.2px; }\n.nav-card .nv-sub { font-size: 10px; color: var(--text-2); line-height: 1.35; }\n.nav-card .nv-go { margin-top: auto; font-size: 11px; font-weight: 700; color: var(--primary); }\n.nav-card .nv-fix { font-size: 13px; font-weight: 700; }\n.nav-card .nv-nd { font-weight: 700; color: var(--text-2); }\n.nav-card .chip-mon { align-self: flex-start; }\n.nv-muted { color: var(--text-2); font-weight: 500; }\n@media (max-width: 1250px) { .ov-mid { grid-template-columns: 1fr 1fr; } .ov-limits { grid-column: 1 / -1; } }\n@media (max-width: 1100px) { .ov-cards, .ov-nav { grid-template-columns: repeat(2, 1fr); } .ov-mid { grid-template-columns: 1fr; } }\n","/* Risk Intelligence — Crédito (mock) — tokens del baseline RI (04-design-system-mapping.md)\n Prohibido hex fuera de :root [inviolable L-7] */\n:root {\n --bg-app: #eff3f8;\n --primary: #0d77bf;\n --secondary: #1f2a4e;\n --text: #000;\n --text-2: #434343;\n --border: #dfdfdf;\n --hover: #d9e2ed;\n --skeleton: #d9e2ed;\n --sem-error: #c10007;\n --fondo-error: #ffe2e2;\n --sem-ok: #008236;\n --fondo-ok: #dcfce7;\n --sem-warn: #de560d;\n --fondo-alerta: #ffedd4;\n --surface-container: #ffffff;\n --surface-card: #eff3f8;\n --radius-container: 20px;\n --radius-panel: 10px;\n --radius-card: 8px;\n --sp: 4px;\n --font: 'Inter', sans-serif;\n}\n* { box-sizing: border-box; margin: 0; padding: 0; }\nhtml, body { height: 100%; }\nbody { font-family: var(--font); background: var(--bg-app); color: var(--text); font-size: 13px; }\n.num { font-variant-numeric: tabular-nums; }\n\n/* ---------- Header global ---------- */\n.app-header {\n display: flex; align-items: center; gap: 16px;\n padding: 10px 24px; background: var(--bg-app);\n}\n.brand { font-weight: 800; font-size: 18px; color: var(--secondary); letter-spacing: 0.5px; }\n.brand small { display: block; font-size: 8px; font-weight: 600; letter-spacing: 2px; color: var(--text-2); }\n.tenant {\n display: flex; align-items: center; gap: 8px; background: var(--surface-container);\n border: 1px solid var(--border); border-radius: var(--radius-card); padding: 8px 12px;\n font-weight: 600; font-size: 13px;\n}\n.modules {\n margin: 0 auto; display: flex; gap: 4px; background: var(--surface-container);\n border-radius: 16px; padding: 6px; box-shadow: 0 1px 3px rgba(31,42,78,0.08);\n}\n.module-tab {\n display: flex; flex-direction: column; align-items: center; gap: 2px;\n padding: 8px 22px; border-radius: 12px; font-size: 11px; font-weight: 600;\n color: var(--text-2); border: none; background: transparent; cursor: default; font-family: var(--font);\n}\n.module-tab .mico { font-size: 15px; }\n.module-tab.active { background: var(--primary); color: #fff; }\n.module-tab.disabled { color: var(--border); }\n.header-right { display: flex; align-items: center; gap: 14px; }\n.avatar {\n width: 36px; height: 36px; border-radius: var(--radius-card); background: var(--secondary);\n color: #fff; display: flex; align-items: center; justify-content: center; font-weight: 700; font-size: 12px;\n}\n.hicon { color: var(--secondary); font-size: 16px; }\n\n/* ---------- Layout ---------- */\n.app-body { display: flex; align-items: flex-start; }\n.sidebar { width: 232px; flex-shrink: 0; padding: 8px 12px 24px 24px; }\n.sidebar h1 { font-size: 26px; font-weight: 800; color: var(--secondary); margin: 6px 0 18px 6px; }\n.menu-item {\n display: flex; align-items: center; gap: 10px; width: 100%;\n padding: 11px 14px; margin-bottom: 2px; border: none; background: transparent;\n border-radius: var(--radius-panel); font-family: var(--font); font-size: 13.5px; font-weight: 500;\n color: var(--text); cursor: pointer; text-align: left;\n}\n.menu-item:hover { background: var(--hover); }\n.menu-item.active { background: var(--surface-container); font-weight: 600; box-shadow: 0 1px 3px rgba(31,42,78,0.10); }\n.menu-item .ico { width: 18px; text-align: center; color: var(--secondary); }\n.main {\n flex: 1; background: var(--surface-container); border-radius: var(--radius-container);\n margin: 0 24px 24px 0; padding: 20px 24px 28px; min-height: 86vh; min-width: 0;\n}\n\n/* ---------- Cabecera de sección (badges FUERA de paneles skeletonizables — X-2) ---------- */\n.section-head { display: flex; align-items: flex-start; justify-content: space-between; gap: 16px; flex-wrap: wrap; }\n.breadcrumb { display: flex; align-items: center; gap: 8px; font-size: 14px; padding-top: 6px; }\n.breadcrumb .home { color: var(--secondary); }\n.breadcrumb .sep { color: var(--text-2); }\n.breadcrumb .leaf { font-weight: 600; }\n.head-badges { display: flex; align-items: center; gap: 10px; flex-wrap: wrap; justify-content: flex-end; }\n.badge-supuesto {\n display: inline-flex; align-items: center; gap: 6px;\n background: var(--surface-card); border: 1px solid var(--border);\n border-radius: 999px; padding: 7px 14px; font-size: 12px; color: var(--text-2); font-weight: 500;\n}\n.badge-supuesto .lbl { font-weight: 700; color: var(--secondary); }\n.badge-data {\n display: inline-flex; align-items: center; gap: 8px; background: var(--surface-card);\n border-radius: var(--radius-card); padding: 8px 14px; font-size: 13px;\n}\n.badge-data b { font-weight: 700; }\n.badge-data.warn { background: var(--fondo-alerta); color: var(--sem-warn); }\n.badge-data.err { background: var(--fondo-error); color: var(--sem-error); }\n.dataset-select, .btn-filtros {\n display: inline-flex; align-items: center; gap: 8px; background: var(--surface-container);\n border: 1px solid var(--border); border-radius: var(--radius-card); padding: 8px 14px;\n font-family: var(--font); font-size: 13px; cursor: pointer;\n}\n.btn-filtros { font-weight: 600; }\n.btn-filtros .count {\n background: var(--primary); color: #fff; border-radius: 999px;\n font-size: 10px; width: 16px; height: 16px; display: inline-flex; align-items: center; justify-content: center;\n}\n\n/* ---------- Tabs pill ---------- */\n.tabs-bar {\n display: inline-flex; gap: 6px; background: var(--surface-card);\n border-radius: 12px; padding: 6px; margin: 16px 0 18px;\n}\n.tab-pill {\n border: none; background: transparent; font-family: var(--font); font-size: 13px; font-weight: 600;\n color: var(--text-2); padding: 8px 20px; border-radius: var(--radius-card); cursor: pointer;\n}\n.tab-pill.active { background: var(--surface-container); color: var(--text); border: 1px solid var(--border); }\n\n/* ---------- Dashboard grid ---------- */\n.dash { display: grid; grid-template-columns: 230px 1fr; gap: 16px; align-items: start; }\n.kpi-col { display: flex; flex-direction: column; gap: 12px; }\n.kpi-card { background: var(--surface-card); border-radius: var(--radius-card); padding: 14px 16px; }\n.kpi-card h3 { font-size: 13px; font-weight: 700; margin-bottom: 6px; }\n.kpi-card .big { font-size: 21px; font-weight: 800; letter-spacing: -0.3px; }\n.kpi-card .sub { font-size: 10.5px; color: var(--text-2); margin-top: 3px; line-height: 1.35; }\n.kpi-card .rows { margin-top: 10px; display: flex; flex-direction: column; gap: 4px; }\n.kpi-card .row { display: flex; justify-content: space-between; font-size: 11.5px; color: var(--text-2); }\n.kpi-card .row b { color: var(--text); font-weight: 600; }\n.trend { font-weight: 700; color: var(--secondary); } /* Δ de riesgo/mezcla: neutro SIEMPRE (L-5/L-6) */\n.grid-2x2 { display: grid; grid-template-columns: 1fr 1fr; gap: 16px; min-width: 0; }\n.panel {\n background: var(--surface-container); border: 1px solid var(--border);\n border-radius: var(--radius-panel); padding: 14px 16px; min-width: 0; min-height: 300px;\n display: flex; flex-direction: column;\n}\n.panel-head { display: flex; align-items: center; justify-content: space-between; gap: 8px; margin-bottom: 8px; flex-wrap: wrap; }\n.panel-head h2 { font-size: 14.5px; font-weight: 700; }\n.chart-box { flex: 1; min-height: 230px; }\n.panel-foot { font-size: 10.5px; color: var(--text-2); margin-top: 8px; line-height: 1.4; }\n.seg {\n display: inline-flex; background: var(--surface-card); border-radius: var(--radius-card); padding: 3px; gap: 2px;\n}\n.seg button {\n border: none; background: transparent; font-family: var(--font); font-size: 11px; font-weight: 600;\n color: var(--text-2); padding: 5px 10px; border-radius: 6px; cursor: pointer;\n}\n.seg button.active { background: var(--surface-container); color: var(--text); border: 1px solid var(--border); }\n.select-mini {\n font-family: var(--font); font-size: 12px; border: 1px solid var(--border);\n border-radius: var(--radius-card); padding: 5px 8px; background: var(--surface-container);\n}\n\n/* ---------- Estado / pills ---------- */\n.pill { display: inline-flex; align-items: center; gap: 5px; border-radius: 999px; padding: 3px 10px; font-size: 11px; font-weight: 700; }\n.pill.ok { background: var(--fondo-ok); color: var(--sem-ok); }\n.pill.warn { background: var(--fondo-alerta); color: var(--sem-warn); }\n.pill.err { background: var(--fondo-error); color: var(--sem-error); }\n.pill.na { background: var(--surface-card); color: var(--text-2); border: 1px solid var(--border); }\n.chip-mon { display: inline-block; border: 1px solid var(--border); background: var(--surface-card); color: var(--text-2); border-radius: 4px; padding: 1px 7px; font-size: 10.5px; font-weight: 600; }\n\n/* ---------- Tabla ---------- */\n.tbl-wrap { flex: 1; overflow: auto; }\ntable.tbl { width: 100%; border-collapse: collapse; font-size: 12px; }\n.tbl th { text-align: right; font-weight: 700; padding: 7px 8px; border-bottom: 1px solid var(--border); white-space: nowrap; }\n.tbl th.gh { text-align: center; border-bottom: 1px solid var(--border); color: var(--text-2); font-size: 11px; }\n.tbl th:first-child, .tbl td:first-child { text-align: left; }\n.tbl td { padding: 7px 8px; border-bottom: 1px solid var(--surface-card); text-align: right; white-space: nowrap; }\n.tbl tr.grp td { font-weight: 700; cursor: pointer; }\n.tbl tr.grp:hover td { background: var(--hover); }\n.tbl tr.child td:first-child { padding-left: 26px; color: var(--text-2); }\n.tbl .caret { display: inline-block; width: 14px; color: var(--text-2); font-size: 10px; }\n.btn-export {\n border: 1px solid var(--border); background: var(--surface-container); border-radius: var(--radius-card);\n font-family: var(--font); font-size: 11.5px; font-weight: 600; padding: 5px 12px; cursor: pointer; color: var(--secondary);\n}\n\n/* ---------- Estados UI ---------- */\n.skeleton { border-radius: var(--radius-panel); background: var(--skeleton); animation: pulse 1.4s ease-in-out infinite; min-height: 300px; }\n.skeleton.sm { min-height: 96px; border-radius: var(--radius-card); }\n@keyframes pulse { 0%,100% { opacity: 1; } 50% { opacity: 0.55; } }\n@media (prefers-reduced-motion: reduce) { .skeleton { animation: none; } }\n.state-box { flex: 1; display: flex; flex-direction: column; align-items: center; justify-content: center; gap: 8px; text-align: center; padding: 20px; }\n.state-box .t { font-weight: 700; font-size: 13.5px; }\n.state-box .d { color: var(--text-2); font-size: 12px; max-width: 340px; line-height: 1.45; }\n.state-box .ic { font-size: 26px; }\n.btn-retry {\n margin-top: 6px; border: none; background: var(--primary); color: #fff; font-family: var(--font);\n font-weight: 600; font-size: 12px; padding: 8px 18px; border-radius: var(--radius-card); cursor: pointer;\n}\n\n/* ---------- Placeholder de sección ---------- */\n.placeholder-note {\n background: var(--surface-card); border: 1px dashed var(--border); border-radius: var(--radius-panel);\n padding: 34px; text-align: center; color: var(--text-2); margin-top: 8px;\n}\n.placeholder-note b { color: var(--secondary); display: block; font-size: 15px; margin-bottom: 6px; }\n\n/* ---------- Panel de filtros (derecho) ---------- */\n.filters-overlay { position: fixed; inset: 0; background: rgba(31,42,78,0.25); z-index: 40; }\n.filters-panel {\n position: fixed; top: 0; right: 0; bottom: 0; width: 320px; background: var(--surface-container);\n z-index: 41; padding: 20px; overflow-y: auto; box-shadow: -4px 0 16px rgba(31,42,78,0.15);\n}\n.filters-panel h2 { font-size: 16px; font-weight: 800; color: var(--secondary); margin-bottom: 14px; }\n.f-group { margin-bottom: 16px; }\n.f-group label { display: block; font-size: 11px; font-weight: 700; color: var(--text-2); margin-bottom: 5px; text-transform: uppercase; letter-spacing: 0.4px; }\n.f-group select, .f-group input {\n width: 100%; font-family: var(--font); font-size: 12.5px; border: 1px solid var(--border);\n border-radius: var(--radius-card); padding: 8px 10px; background: var(--surface-container);\n}\n.f-sep { border-top: 1px solid var(--border); margin: 14px 0; }\n.f-note { font-size: 10.5px; color: var(--text-2); line-height: 1.4; }\n\n/* ---------- Switcher de estado del prototipo ---------- */\n.proto-switch {\n position: fixed; bottom: 16px; right: 16px; z-index: 50;\n background: var(--secondary); color: #fff; border-radius: var(--radius-panel);\n padding: 10px 12px; box-shadow: 0 4px 14px rgba(31,42,78,0.35); font-size: 11px;\n}\n.proto-switch .t { font-weight: 700; margin-bottom: 6px; opacity: 0.8; }\n.proto-switch .opts { display: flex; gap: 4px; flex-wrap: wrap; }\n.proto-switch button {\n border: 1px solid rgba(255,255,255,0.3); background: transparent; color: #fff;\n font-family: var(--font); font-size: 10.5px; font-weight: 600; padding: 4px 9px; border-radius: 6px; cursor: pointer;\n}\n.proto-switch button.active { background: #fff; color: var(--secondary); }\n\n@media (max-width: 1100px) {\n .dash { grid-template-columns: 1fr; }\n .kpi-col { flex-direction: row; flex-wrap: wrap; }\n .kpi-card { flex: 1 1 180px; }\n .grid-2x2 { grid-template-columns: 1fr; }\n}\n\n/* F2.3 — Métricas de Riesgo */\n.seg-medida { margin-right: 6px; }\n.seg-medida button { font-weight: 600; min-width: 40px; }\n.seg button[disabled] { opacity: .45; cursor: not-allowed; }\n.mr-nota { grid-column: 1 / -1; margin-top: 10px; padding: 8px 12px; font-size: 11px; color: var(--text-2); background: var(--card-bg); border: 1px dashed var(--border); border-radius: var(--radius); }\n\n/* F2.10 — Backtesting */\n.chip-window { display: inline-flex; align-items: center; border: 1px solid var(--border); background: var(--surface-card); color: var(--text-2); border-radius: 999px; padding: 7px 12px; font-size: 11.5px; font-weight: 600; }\n.bt-val { flex: 1; display: flex; flex-direction: column; gap: 10px; overflow: auto; }\n.bt-winhead { font-size: 12px; font-weight: 700; color: var(--secondary); background: var(--surface-card); border-radius: var(--radius-card); padding: 7px 10px; }\n.bt-block { border: 1px solid var(--border); border-radius: var(--radius-card); padding: 9px 11px; }\n.bt-block h4 { font-size: 12px; font-weight: 700; margin-bottom: 4px; }\n.bt-nd { font-size: 13px; font-weight: 700; color: var(--text-2); }\n.bt-det { font-size: 10.5px; color: var(--text-2); margin-top: 4px; line-height: 1.4; }\n.badge-basilea { display: block; border-radius: 6px; border: 1px solid var(--border); border-left: 4px solid var(--text-2); background: var(--surface-card); padding: 7px 10px; margin-top: 4px; }\n.badge-basilea .z { display: block; font-size: 12.5px; font-weight: 800; }\n.badge-basilea .r { display: block; font-size: 9.5px; color: var(--text-2); margin-top: 2px; font-weight: 600; text-transform: uppercase; letter-spacing: 0.3px; }\n.badge-basilea.arch { border-left-color: var(--sem-ok); background: var(--fondo-ok); }\n.badge-basilea.arch .z { color: var(--sem-ok); }\n.bt-archived { border: 1px dashed var(--border); border-radius: var(--radius-card); padding: 9px 11px; opacity: 0.78; }\n.bt-arch-rot { font-size: 10px; font-weight: 800; text-transform: uppercase; letter-spacing: 0.4px; color: var(--text-2); margin-bottom: 4px; }\n.bt-arch-sub { font-size: 11px; color: var(--text-2); margin-bottom: 6px; }\n.bt-arch-grid { display: grid; grid-template-columns: auto auto 1fr; gap: 3px 10px; font-size: 11.5px; align-items: baseline; }\n.bt-arch-grid b { font-weight: 700; }\n.bt-arch-grid .num { color: var(--text-2); font-size: 10.5px; }\n.bt-sub2 { font-size: 10.5px; color: var(--text-2); line-height: 1.4; margin: -2px 0 6px; }\n.bt-sub2 b { font-weight: 700; }\n.tbl tr.bt-out td { color: var(--text-2); opacity: 0.62; }\n\n/* F2.8 — Factores de Riesgo: subtítulo anti-Gauss del panel TR (cuerpo capturable, no tooltip — X-#2) */\n.fr-sub { font-size: 11px; font-style: italic; color: var(--text-2); padding: 4px 14px 0; }\n\n/* F2.7 — Visión General (arquetipo overview §11) */\n.ov { display: flex; flex-direction: column; gap: 16px; }\n.ov-cards { display: grid; grid-template-columns: repeat(4, 1fr); gap: 14px; }\n.ov-card { min-height: 170px; }\n.ov-card .rows { margin-top: 8px; }\n.ov-mid { display: grid; grid-template-columns: 1.9fr 1fr 1fr; gap: 14px; align-items: stretch; }\n.ov-mid .panel { min-height: 320px; }\n.ov-limits .tbl td, .ov-limits .tbl th { font-size: 11px; padding: 7px 6px; }\n.ov-limits .tbl td:first-child { white-space: normal; }\n.ov-limits .pill { padding: 2px 7px; font-size: 10px; }\n.ov-nav { display: grid; grid-template-columns: repeat(4, 1fr); gap: 14px; }\n.nav-card {\n background: var(--surface-card); border: 1px solid transparent; border-radius: var(--radius-card);\n padding: 13px 15px; text-align: left; font-family: var(--font); cursor: pointer;\n display: flex; flex-direction: column; gap: 5px; min-height: 120px;\n transition: box-shadow .12s ease, transform .12s ease;\n}\n.nav-card:hover { box-shadow: 0 4px 14px rgba(31,42,78,0.16); transform: translateY(-2px); border-color: var(--border); background: var(--surface-container); }\n.nav-card h4 { font-size: 12.5px; font-weight: 700; color: var(--secondary); }\n.nav-card .nv-big { font-size: 14.5px; font-weight: 800; letter-spacing: -0.2px; }\n.nav-card .nv-sub { font-size: 10px; color: var(--text-2); line-height: 1.35; }\n.nav-card .nv-go { margin-top: auto; font-size: 11px; font-weight: 700; color: var(--primary); }\n.nav-card .nv-fix { font-size: 13px; font-weight: 700; }\n.nav-card .nv-nd { font-weight: 700; color: var(--text-2); }\n.nav-card .chip-mon { align-self: flex-start; }\n.nv-muted { color: var(--text-2); font-weight: 500; }\n@media (max-width: 1250px) { .ov-mid { grid-template-columns: 1fr 1fr; } .ov-limits { grid-column: 1 / -1; } }\n@media (max-width: 1100px) { .ov-cards, .ov-nav { grid-template-columns: repeat(2, 1fr); } .ov-mid { grid-template-columns: 1fr; } }\n\n/* F2.5 — Escenarios (arquetipo simulador: riel persistente + área de resultados) */\n.sidebar.esc-mini { width: 64px; padding-left: 12px; }\n.sidebar.esc-mini h1 { font-size: 0; margin: 6px 0 18px 0; }\n.sidebar.esc-mini h1::after { content: \"CR\"; font-size: 16px; color: var(--secondary); font-weight: 800; }\n.sidebar.esc-mini .menu-item { justify-content: center; padding: 11px 8px; font-size: 0; gap: 0; }\n.sidebar.esc-mini .menu-item .ico { font-size: 15px; width: auto; }\n.esc-layout { display: grid; grid-template-columns: 250px 1fr; gap: 16px; align-items: start; }\n.esc-rail { background: var(--surface-card); border-radius: var(--radius-panel); padding: 14px; position: sticky; top: 10px; display: flex; flex-direction: column; gap: 12px; }\n.esc-rail h3 { font-size: 12px; font-weight: 800; color: var(--secondary); text-transform: uppercase; letter-spacing: .4px; }\n.esc-rail .rg { display: flex; flex-direction: column; gap: 5px; }\n.esc-rail .rg > label { font-size: 10.5px; font-weight: 700; color: var(--text-2); text-transform: uppercase; letter-spacing: .3px; }\n.esc-rail .seg { align-self: stretch; }\n.esc-rail .seg button { flex: 1; }\n.esc-rail input[type=\"number\"] { width: 100%; font-family: var(--font); font-size: 12.5px; border: 1px solid var(--border); border-radius: var(--radius-card); padding: 7px 9px; background: var(--surface-container); }\n.esc-rail .radio-row { display: flex; align-items: flex-start; gap: 7px; font-size: 12px; cursor: pointer; line-height: 1.3; }\n.esc-rail .radio-row input { margin-top: 2px; }\n.esc-rail .chk-row { display: flex; align-items: center; gap: 7px; font-size: 12px; cursor: pointer; }\n.esc-sub { border-left: 2px solid var(--border); padding: 6px 0 2px 10px; margin-left: 5px; display: flex; flex-direction: column; gap: 7px; }\n.esc-sub .mini-lbl { font-size: 10px; color: var(--text-2); font-weight: 600; }\n.esc-consol { font-size: 10.5px; color: var(--text-2); line-height: 1.45; border-top: 1px solid var(--border); padding-top: 10px; }\n.esc-actions { display: flex; gap: 8px; }\n.btn-aplicar { flex: 1; border: none; background: var(--primary); color: #fff; font-family: var(--font); font-weight: 700; font-size: 13px; padding: 10px; border-radius: var(--radius-card); cursor: pointer; }\n.btn-aplicar[disabled] { opacity: .45; cursor: not-allowed; }\n.btn-reset { border: 1px solid var(--border); background: var(--surface-container); color: var(--secondary); font-family: var(--font); font-weight: 600; font-size: 12px; padding: 10px 14px; border-radius: var(--radius-card); cursor: pointer; }\n.esc-results { display: flex; flex-direction: column; gap: 12px; min-width: 0; }\n.esc-grid { display: grid; grid-template-columns: 215px 1.35fr 1.25fr; gap: 12px; align-items: start; min-width: 0; }\n.esc-grid .kpi-col { gap: 10px; }\n.esc-panels { display: flex; flex-direction: column; gap: 12px; min-width: 0; }\n.esc-panels .panel { min-height: 240px; }\n.esc-stale-banner { display: flex; align-items: center; gap: 10px; background: var(--fondo-alerta); color: var(--sem-warn); border-radius: var(--radius-card); padding: 9px 14px; font-size: 12px; font-weight: 600; }\n.esc-stale .esc-grid, .esc-stale .esc-strip { opacity: .45; pointer-events: auto; }\n.esc-chips { display: inline-flex; gap: 6px; align-items: center; }\n.esc-chips .lbl { font-size: 11px; font-weight: 700; color: var(--text-2); }\n.esc-chip { border: 1px solid var(--border); background: var(--surface-container); font-family: var(--font); font-size: 11.5px; font-weight: 700; color: var(--text-2); padding: 5px 13px; border-radius: 999px; cursor: pointer; }\n.esc-chip.active { background: var(--secondary); border-color: var(--secondary); color: #fff; }\n.esc-chip[disabled] { opacity: .5; cursor: not-allowed; }\n.esc-strip { background: var(--surface-container); border: 1px solid var(--border); border-radius: var(--radius-panel); padding: 10px 14px; }\n.esc-strip .sh { display: flex; justify-content: space-between; align-items: baseline; gap: 10px; flex-wrap: wrap; margin-bottom: 6px; }\n.esc-strip .sh h4 { font-size: 12px; font-weight: 800; color: var(--secondary); }\n.esc-strip .sh .lim { font-size: 11px; color: var(--text-2); font-weight: 600; }\n.esc-strip .cells { display: grid; grid-template-columns: repeat(3, 1fr); gap: 8px; }\n.esc-strip .cell { background: var(--surface-card); border-radius: var(--radius-card); padding: 8px 12px; }\n.esc-strip .cell.base { outline: 2px solid var(--secondary); }\n.esc-strip .cell .r { font-size: 10.5px; font-weight: 800; color: var(--secondary); }\n.esc-strip .cell .v { display: flex; justify-content: space-between; font-size: 11.5px; margin-top: 2px; }\n.esc-strip .cell .v b { font-weight: 700; }\n.esc-topbar { display: flex; justify-content: space-between; align-items: center; gap: 10px; flex-wrap: wrap; }\n.esc-foot-note { font-size: 10.5px; color: var(--text-2); background: var(--surface-card); border: 1px dashed var(--border); border-radius: var(--radius-card); padding: 8px 12px; line-height: 1.45; }\n.badge-chip-shock { display: inline-flex; align-items: center; gap: 5px; background: var(--surface-card); border: 1px solid var(--secondary); border-radius: 999px; padding: 7px 12px; font-size: 11.5px; font-weight: 700; color: var(--secondary); }\n.gp-soft { color: var(--text-2); }\n.proto-switch .meta { border-top: 1px solid rgba(255,255,255,.25); margin-top: 7px; padding-top: 7px; display: flex; align-items: center; gap: 6px; font-size: 10.5px; }\n@media (max-width: 1250px) { .esc-grid { grid-template-columns: 1fr 1.2fr; } .esc-grid .kpi-col { grid-column: 1 / -1; flex-direction: row; flex-wrap: wrap; } }\n@media (max-width: 1100px) { .esc-layout { grid-template-columns: 1fr; } .esc-rail { position: static; } .esc-grid { grid-template-columns: 1fr; } }\n","createdAt",["D",1787334387634],"branchVersion","branchId","26318b20-79c4-45b1-8b64-9b218f217a44","id","935f65cd-5733-4dbc-b0ca-b5a3502394d7","ri-credito-mock",["D",1787326658800],"deletedAt","legacyEnvVars","privacy","public","httpPrivacy","description","Mock UX/UI seccion Credito de Risk Intelligence (F2.2)","imageUrl","019c346e-384f-704b-b25a-da5eb72ef468","pinnedFileId","64f125fa-9d76-11f1-b549-1607ee4eb77e","pinPreview",true,"pinMigrated","screenshotVersion","likeCount",0,"orgId","019c346e-384f-704b-b25a-dc67b1d14ed5","tursoName","tursoHostname","tursoMeasuredAt","pinned","userPerm","r","valPerm","blobPerm","rw","emailPerm","sqlitePerm","projectPerm","telemetryPerm","user",{"_96":95,"_103":99},"org",{"_96":95,"_97":-5,"_98":99,"_18":54,"_100":101,"_102":25},"branch",{"_13":85,"_32":86,"_42":41,"_87":43,"_88":-5,"_89":-5,"_90":-5,"_91":-5,"_92":-5,"_93":44,"_94":95},"isOwned",110,"main","projectId","forkedBranchId","forkedBranchVersion","forkedProjectPrivacy","forkedProjectId","forkedProjectOrgId","projectName","userHandle","joselier3","handle","displayName","avatar","https://img.clerk.com/eyJ0eXBlIjoicHJveHkiLCJzcmMiOiJodHRwczovL2ltYWdlcy5jbGVyay5kZXYvb2F1dGhfZ2l0aHViL2ltZ18zOUpFemx0ZkZMYnQwNks1d1VoUmR5blBQelUifQ","tier","free","canRestrictVals","profileImageUrl","branchName","","adoptOrgId",{"_42":43,"_32":44,"_37":201,"_46":-5,"_47":25,"_48":49,"_50":49,"_51":52,"_53":-5,"_18":54,"_55":56,"_57":58,"_59":-5,"_60":-5,"_61":62,"_63":64,"_65":-5,"_66":-5,"_67":-5,"_68":-5,"_69":70,"_71":70,"_72":73,"_74":73,"_75":73,"_76":70,"_77":70,"_78":202,"_80":203,"_82":204,"_84":25},"tree",[180,181,182,183,184],"files",[180,181,182,183,184],"counts",{"_170":62,"_171":150,"_172":62,"_173":174,"_175":176},"contents",[126,127,128,129,130],"upstreamProject","upstreamBranch","emptyEnvVars","flags",[],"hasHttpFiles","grants","orgs","customDomains",{},{"_42":162,"_32":163,"_30":164,"_132":-5,"_40":41,"_39":165,"_133":25,"_37":166,"_13":167,"_33":159,"_34":168,"_24":25,"_136":-5,"_27":169},{"_42":153,"_32":154,"_30":155,"_132":-5,"_40":41,"_39":156,"_133":25,"_37":157,"_13":158,"_33":159,"_34":160,"_24":25,"_136":-5,"_27":161},{"_42":145,"_32":146,"_30":147,"_132":-5,"_40":41,"_39":148,"_133":58,"_37":149,"_13":150,"_33":20,"_34":151,"_24":25,"_136":-5,"_27":152},{"_42":138,"_32":139,"_30":56,"_132":-5,"_40":41,"_39":140,"_133":58,"_37":141,"_13":62,"_33":142,"_34":143,"_24":25,"_136":-5,"_27":144},{"_42":131,"_32":28,"_30":31,"_132":-5,"_40":41,"_39":14,"_133":25,"_37":134,"_13":135,"_33":20,"_34":36,"_24":25,"_136":-5,"_27":137},"91b7c1fd-d2ac-4c64-8700-e29a6ff94c95","parentId","latest",["D",1787334387634],7,"label",[28],"291d60c8-c08e-40ea-b565-244e643c6f2d","main.ts",5,["D",1787326725014],"http","import { readFile } from \"https://esm.town/v/std/utils/index.ts\";\n\nexport default async function (req: Request): Promise {\n const path = new URL(req.url).pathname;\n const serve = async (file: string, type: string) =>\n new Response(await readFile(file, import.meta.url), {\n headers: { \"Content-Type\": type + \"; charset=utf-8\" },\n });\n if (path.endsWith(\"styles.css\")) return serve(\"/styles.css\", \"text/css\");\n if (path.endsWith(\"data.js\")) return serve(\"/data.js\", \"text/javascript\");\n if (path.endsWith(\"app.js\")) return serve(\"/app.js\", \"text/javascript\");\n return serve(\"/index.html\", \"text/html\");\n}\n",[139],"ce72ce6a-1f5e-4feb-9ed1-08216645377e","index.html","610320f6-9d76-11f1-8101-1607ee4eb77e",14,["D",1787327075110],1,"\n\n\n \n \n Crédito — Risk Intelligence (mock)\n \n \n \n \n\n\n \n

\n \n

\n \n \n\n\n",[146],"9e9077f7-9ef1-46a6-ace0-c9745ef9ef4d","data.js","5d60d72c-9d76-11f1-bcc0-1607ee4eb77e",88,["D",1787334356848],12,"script","/* Datos mock — deuda dominicana (bonos, SBB, SBB c/ Garantía, CDs), DOP + USD.\n Convención del mock: TC 61.50 (BCRD venta) al as_of 30/01/2026; cortes históricos\n consolidados al TC de su fecha. VM en MM DOP (o MM USD nativo cuando moneda=USD). */\nwindow.RI_DATA = (() => {\n const TC = 61.50, TC_PREV = 61.32;\n /* inst = nombre de instrumento (nivel hoja, export estable). mgF = factor marginal/componental\n por posición (mock determinista, 1.02–1.10: garantiza componental ≤ marginal ≤ standalone en\n contribuidoras). div = diversificadora: componental negativa por la REALIZACIÓN SIMULADA de su\n escenario (consistente con la nota de granularidad §2 — no es atributo del emisor); el excedente\n se redistribuye intra-rating para preservar Σ componental = total de Métricas de Riesgo. */\n const positions = [\n { inst: \"Bono Hacienda 2031\", emisor: \"Ministerio de Hacienda\", rating: \"AA\", tipo: \"Bono\", moneda: \"DOP\", vm: 612.40, prev: 605.10, mgF: 1.07 },\n { inst: \"Bono Global 2033\", emisor: \"Ministerio de Hacienda\", rating: \"AA\", tipo: \"Bono\", moneda: \"USD\", vm: 6.90, prev: 6.90, mgF: 1.09 },\n { inst: \"Bono Hacienda 2028\", emisor: \"Ministerio de Hacienda\", rating: \"AA\", tipo: \"Bono\", moneda: \"DOP\", vm: 291.00, prev: 296.40, mgF: 1.04 },\n { inst: \"Nota BCRD 2030\", emisor: \"Banco Central (BCRD)\", rating: \"AAA\", tipo: \"Bono\", moneda: \"DOP\", vm: 734.20, prev: 741.80, mgF: 1.05 },\n { inst: \"CD BCRD 91d\", emisor: \"Banco Central (BCRD)\", rating: \"AAA\", tipo: \"CD\", moneda: \"DOP\", vm: 210.00, prev: 210.00, mgF: 1.02 },\n { inst: \"Bono Banreservas 2029\", emisor: \"Banreservas\", rating: \"A\", tipo: \"Bono\", moneda: \"DOP\", vm: 498.60, prev: 502.30, mgF: 1.08 },\n { inst: \"CD Banreservas 180d\", emisor: \"Banreservas\", rating: \"A\", tipo: \"CD\", moneda: \"DOP\", vm: 187.50, prev: 172.00, mgF: 1.03 },\n { inst: \"Bono Popular 2027\", emisor: \"Banco Popular\", rating: \"A\", tipo: \"Bono\", moneda: \"DOP\", vm: 402.10, prev: 398.90, mgF: 1.06 },\n { inst: \"SBB Popular 2026\", emisor: \"Banco Popular\", rating: \"A\", tipo: \"SBB\", moneda: \"USD\", vm: 3.20, prev: 3.20, mgF: 1.05 },\n { inst: \"SBB BHD 2027\", emisor: \"Banco BHD\", rating: \"A\", tipo: \"SBB\", moneda: \"DOP\", vm: 356.80, prev: 361.20, mgF: 1.07 },\n { inst: \"CD BHD 90d\", emisor: \"Banco BHD\", rating: \"A\", tipo: \"CD\", moneda: \"DOP\", vm: 122.00, prev: 122.00, mgF: 1.00, div: true },\n { inst: \"SBB Gar. APAP 2028\", emisor: \"APAP\", rating: \"BBB\", tipo: \"SBB c/ Garantía\", moneda: \"DOP\", vm: 310.40, prev: 318.70, mgF: 1.08 },\n { inst: \"CD APAP 120d\", emisor: \"APAP\", rating: \"BBB\", tipo: \"CD\", moneda: \"DOP\", vm: 96.30, prev: 96.30, mgF: 1.02 },\n { inst: \"SBB Santa Cruz 2026\", emisor: \"Banco Santa Cruz\", rating: \"BBB\", tipo: \"SBB\", moneda: \"DOP\", vm: 228.90, prev: 224.10, mgF: 1.05 },\n { inst: \"SBB Gar. ACAP 2027\", emisor: \"ACAP\", rating: \"BBB\", tipo: \"SBB c/ Garantía\", moneda: \"DOP\", vm: 204.50, prev: 209.80, mgF: 1.04 },\n { inst: \"Bono CEPM 2030\", emisor: \"CEPM\", rating: \"BBB\", tipo: \"Bono\", moneda: \"USD\", vm: 5.40, prev: 5.10, mgF: 1.09 },\n { inst: \"Bono EGE Haina 2028\", emisor: \"EGE Haina\", rating: \"BB\", tipo: \"Bono\", moneda: \"DOP\", vm: 246.70, prev: 251.30, mgF: 1.08 },\n { inst: \"Bono EGE Haina 2031\", emisor: \"EGE Haina\", rating: \"BB\", tipo: \"Bono\", moneda: \"USD\", vm: 2.10, prev: 2.10, mgF: 1.06 },\n { inst: \"Bono AES Andrés 2029\", emisor: \"AES Andrés\", rating: \"BB\", tipo: \"Bono\", moneda: \"USD\", vm: 4.60, prev: 4.85, mgF: 1.10 },\n { inst: \"CD Promerica 180d\", emisor: \"Banco Promerica\", rating: \"BB\", tipo: \"CD\", moneda: \"DOP\", vm: 138.20, prev: 138.20, mgF: 1.00, div: true },\n { inst: \"SBB Caribe 2026\", emisor: \"Banco Caribe\", rating: \"B\", tipo: \"SBB\", moneda: \"DOP\", vm: 92.40, prev: 98.60, mgF: 1.09 },\n { inst: \"CD Caribe 90d\", emisor: \"Banco Caribe\", rating: \"B\", tipo: \"CD\", moneda: \"DOP\", vm: 41.00, prev: 41.00, mgF: 1.02 },\n ];\n const RATINGS = [\"AAA\", \"AA\", \"A\", \"BBB\", \"BB\", \"B\"];\n const TIPOS = [\"Bono\", \"SBB\", \"SBB c/ Garantía\", \"CD\"];\n const DATES = [\"04/12/2025\",\"09/12/2025\",\"14/12/2025\",\"19/12/2025\",\"24/12/2025\",\"29/12/2025\",\"03/01/2026\",\"08/01/2026\",\"13/01/2026\",\"18/01/2026\",\"20/01/2026\",\"24/01/2026\",\"28/01/2026\",\"30/01/2026\"];\n const HIST_TOTAL = [6020,6035,6018,6060,6072,6058,6094,6110,6102,6125,6139,6131,6146,0];\n const HIST_SHARE = {\n AAA: [0.20,0.20,0.20,0.20,0.20,0.19,0.19,0.19,0.19,0.19,0.19,0.18,0.18,0],\n AA: [0.21,0.21,0.21,0.21,0.21,0.21,0.21,0.21,0.21,0.22,0.22,0.22,0.22,0],\n A: [0.28,0.28,0.28,0.29,0.29,0.29,0.29,0.29,0.30,0.30,0.30,0.30,0.30,0],\n BBB: [0.17,0.17,0.17,0.16,0.16,0.17,0.17,0.17,0.16,0.16,0.16,0.17,0.17,0],\n BB: [0.11,0.11,0.11,0.11,0.11,0.11,0.11,0.11,0.11,0.10,0.10,0.10,0.10,0],\n B: [0.03,0.03,0.03,0.03,0.03,0.03,0.03,0.03,0.03,0.03,0.03,0.03,0.03,0],\n };\n const LIMITES = { hhiInterno: 0.1800, emisorPctInterno: 15.0, alertaFactor: 0.9 };\n /* Riesgo por medida (mock): tasa standalone (% del VM) y factor de diversificación,\n AMBOS por rating y por medida (X-2: proporciones distintas por medida — ES/VaR crece\n hacia ratings bajos, colas más pesadas). divF≤1 en todas (X-1: ES y σ son subaditivas;\n el beneficio de diversificación del mock es siempre ≥0). */\n const RISK = {\n VaR: { rate: { AAA: 0.0040, AA: 0.0090, A: 0.0180, BBB: 0.0360, BB: 0.0700, B: 0.1250 },\n divF: { AAA: 0.88, AA: 0.85, A: 0.80, BBB: 0.76, BB: 0.72, B: 0.70 } },\n ES: { rate: { AAA: 0.0046, AA: 0.0108, A: 0.0234, BBB: 0.0504, BB: 0.1050, B: 0.2000 },\n divF: { AAA: 0.90, AA: 0.87, A: 0.82, BBB: 0.78, BB: 0.74, B: 0.72 } },\n Std: { rate: { AAA: 0.0016, AA: 0.0034, A: 0.0066, BBB: 0.0126, BB: 0.0235, B: 0.0410 },\n divF: { AAA: 0.86, AA: 0.83, A: 0.79, BBB: 0.75, BB: 0.71, B: 0.69 } },\n };\n const LIM_MEDIDA = { VaR: 220, ES: null, Std: null }; // límite configurado SOLO para VaR (X-10)\n /* Overlays del scatter iso-risk de Marginal (F2.4): h = límite %-riesgo (marginal/VM),\n v = límite de tamaño de exposición (MM DOP), hyp = límite de riesgo absoluto POR POSICIÓN\n (MM DOP marginal; hipérbola X·Y=hyp — la recomendada). Solo VaR tiene h/hyp configurados:\n bajo ES/Std la leyenda muestra \"Límite: N/D\" y el KPI 3 es N/D aunque exista v (regla §10). */\n const MG_LIMITS = {\n VaR: { h: 4.5, v: 600, hyp: 8 },\n ES: { h: null, v: 600, hyp: null },\n Std: { h: null, v: 600, hyp: null },\n };\n const SUPUESTO_MARKERS = [{ fecha: \"03/01/2026\", label: \"Cambio de supuesto: ρ 20%→25% · S&P\" }];\n const RHO_PREV_FACTOR = 0.93; // cortes previos al marcador: ρ=20% → medida menor (discontinuidad visible)\n const SUPUESTO = { fuente: \"S&P\", metodo: \"ρ=25% axiomático\", tc: \"TC 61.50 (BCRD venta, 30/01/2026)\" };\n const AS_OF = \"30/01/2026\";\n const DATASET = \"calc-submit 1782766289\";\n /* F2.10 — Backtesting. Convención del mock (declarada, X-D1): cortes EOD diarios hábiles;\n VaR 99%·1a escalado al horizonte entre cortes por raíz de tiempo (÷√252) — la metodología\n oficial del tenant gobierna la comparación. Historia visible: 250 cortes bajo ρ=20%\n (sub-ventana homogénea CERRADA el 02/01/2026) + 20 cortes bajo ρ=25% (ventana válida\n vigente). El cambio 03/01/2026 (sábado, marcador compartido del mock) es EFECTIVO desde\n el corte hábil siguiente, 05/01/2026 (X-#2). VAR1A ≡ VaR total de Métricas de Riesgo\n (misma fórmula que mrAgg con medida VaR — constante única del mock, X-#9). */\n const BT = (() => {\n const VAR1A = positions.reduce((a, p) => {\n const vmDop = p.moneda === \"USD\" ? p.vm * TC : p.vm;\n return a + vmDop * RISK.VaR.rate[p.rating] * RISK.VaR.divF[p.rating];\n }, 0);\n const SQ = Math.sqrt(252);\n const fmt = d => String(d.getDate()).padStart(2, \"0\") + \"/\" + String(d.getMonth() + 1).padStart(2, \"0\") + \"/\" + d.getFullYear();\n let seed = 20260130;\n const rng = () => { seed = (seed * 1664525 + 1013904223) % 4294967296; return seed / 4294967296; };\n const days = [];\n const d = new Date(2026, 0, 30);\n while (days.length < 270) {\n if (d.getDay() !== 0 && d.getDay() !== 6) days.unshift(new Date(d));\n d.setDate(d.getDate() - 1);\n }\n const EFFECTIVE = \"05/01/2026\";\n const EXC = { \"14/03/2025\": 1.12, \"08/07/2025\": 1.05, \"09/10/2025\": 1.22, \"18/11/2025\": 1.08, \"26/01/2026\": 1.10 };\n let post = false;\n const cortes = days.map((dt, i) => {\n const f = fmt(dt);\n if (f === EFFECTIVE) post = true;\n const drift = 1 + 0.025 * Math.sin(i / 38) + (rng() - 0.5) * 0.012;\n const var1a = VAR1A * (post ? 1 : 0.93) * drift;\n const varEsc = var1a / SQ;\n let pnl = (rng() + rng() + rng() - 1.5) * varEsc * 0.72;\n if (EXC[f]) pnl = -varEsc * EXC[f];\n else if (pnl < -varEsc * 0.96) pnl = -varEsc * 0.9;\n return { f, pnl: +pnl.toFixed(2), varEsc: +varEsc.toFixed(2), valida: post };\n });\n return {\n cortes, EFFECTIVE, VAR1A: +VAR1A.toFixed(2), cambios: 1,\n cambioLabel: \"Cambio de supuesto: ρ 20%→25% · S&P (03/01/2026, efectivo corte 05/01/2026)\",\n prevWin: {\n rot: \"S&P · ρ=20% · 250 cortes (cerrada el 02/01/2026)\", exc: 4,\n kupiec: { lr: 0.755, p: 0.385, v: \"Aceptado\" },\n christo: { lr: 2.47, p: 0.29, v: \"Aceptado\" },\n basilea: { zona: \"Verde\", conteo: \"4/250\", mult: \"3.00\" },\n },\n mcPrecision: 3.2, // semiancho % del VaR @99% — cuadratura con el punto final del BL (X-D6)\n quantiles: { \"1%\": { q: 0.01, nivel: 1.00 }, \"0.5%\": { q: 0.005, nivel: 1.18 }, \"0.1%\": { q: 0.001, nivel: 1.45 } },\n };\n })();\n /* F2.8 — Factores de Riesgo. Atribución Euler por factor (pesos por rating, Σ=1 por fila:\n ratings bajos más default-driven, altos más migración/spread) ⇒ Σ factores×ratings = VaR\n total EXACTO (misma fórmula que mrAgg-VaR / BT.VAR1A — fuente única, X-#3).\n Prob ≥1 default COMPUTADA de las PD de TRANS por posición (coherencia por construcción, X-#9).\n Monotonía de ρ obligatoria (X-#8): RHO_ZERO_FACTOR 0.78 < RHO_PREV_FACTOR 0.93 < 1\n (el VaR crece con ρ: VaR(0) < VaR(20%) < VaR(25%)). */\n const FR = (() => {\n const W = {\n AAA: { mig: 0.52, def: 0.10, rec: 0.05, spr: 0.33 },\n AA: { mig: 0.50, def: 0.14, rec: 0.07, spr: 0.29 },\n A: { mig: 0.44, def: 0.24, rec: 0.10, spr: 0.22 },\n BBB: { mig: 0.36, def: 0.36, rec: 0.13, spr: 0.15 },\n BB: { mig: 0.28, def: 0.48, rec: 0.15, spr: 0.09 },\n B: { mig: 0.20, def: 0.58, rec: 0.16, spr: 0.06 },\n };\n const RHO_ZERO_FACTOR = 0.78; // VaR(ρ=0) = 0.78 · VaR(ρ=25%) ⇒ efecto correlación = 22% del VaR\n /* Matriz de transición mock a 1 año (%). Filas: rating de partida (D excluido — estado\n absorbente, sin migración de salida); columnas: llegada AAA…CCC, D. Cada fila Σ=100.\n PD (última columna) monotónica AAA→CCC: 0.01 → 22.73%. Única fuente de los umbrales Z\n de Merton (TR) y de la Prob ≥1 default (KPI 4). */\n const DEST = [\"AAA\", \"AA\", \"A\", \"BBB\", \"BB\", \"B\", \"CCC\", \"D\"];\n const TRANS = {\n AAA: [90.80, 8.30, 0.70, 0.10, 0.05, 0.03, 0.01, 0.01],\n AA: [0.70, 90.60, 7.80, 0.60, 0.15, 0.09, 0.04, 0.02],\n A: [0.09, 2.30, 91.00, 5.50, 0.70, 0.25, 0.10, 0.06],\n BBB: [0.02, 0.30, 5.90, 86.90, 5.30, 1.10, 0.30, 0.18],\n BB: [0.03, 0.14, 0.65, 7.70, 80.50, 8.80, 1.10, 1.08],\n B: [0.01, 0.11, 0.24, 0.45, 6.90, 83.50, 3.90, 4.89],\n CCC: [0.02, 0.05, 0.20, 0.30, 1.00, 11.20, 64.50, 22.73],\n };\n // Φ⁻¹ (aproximación de Acklam) — deriva los umbrales Z desde TRANS\n const invNorm = p => {\n const a = [-3.969683028665376e+01, 2.209460984245205e+02, -2.759285104469687e+02, 1.383577518672690e+02, -3.066479806614716e+01, 2.506628277459239e+00];\n const b = [-5.447609879822406e+01, 1.615858368580409e+02, -1.556989798598866e+02, 6.680131188771972e+01, -1.328068155288572e+01];\n const c = [-7.784894002430293e-03, -3.223964580411365e-01, -2.400758277161838e+00, -2.549732539343734e+00, 4.374664141464968e+00, 2.938163982698783e+00];\n const dd = [7.784695709041462e-03, 3.224671290700398e-01, 2.445134137142996e+00, 3.754408661907416e+00];\n const pl = 0.02425;\n if (p < pl) { const q = Math.sqrt(-2 * Math.log(p)); return (((((c[0] * q + c[1]) * q + c[2]) * q + c[3]) * q + c[4]) * q + c[5]) / ((((dd[0] * q + dd[1]) * q + dd[2]) * q + dd[3]) * q + 1); }\n if (p > 1 - pl) { const q = Math.sqrt(-2 * Math.log(1 - p)); return -(((((c[0] * q + c[1]) * q + c[2]) * q + c[3]) * q + c[4]) * q + c[5]) / ((((dd[0] * q + dd[1]) * q + dd[2]) * q + dd[3]) * q + 1); }\n const q = p - 0.5, r = q * q;\n return (((((a[0] * r + a[1]) * r + a[2]) * r + a[3]) * r + a[4]) * r + a[5]) * q / (((((b[0] * r + b[1]) * r + b[2]) * r + b[3]) * r + b[4]) * r + 1);\n };\n /* Z[r] = fronteras superiores de banda de llegada, de peor a mejor:\n [{dest:\"D\", zUp:Φ⁻¹(pD)}, {dest:\"CCC\", zUp:Φ⁻¹(pD+pCCC)}, …, {dest:\"AA\", zUp:Φ⁻¹(1−pAAA)}];\n la banda AAA es el resto superior. */\n const Z = {};\n Object.keys(TRANS).forEach(r => {\n const row = TRANS[r].map(x => x / 100);\n let acc = 0; const bnds = [];\n for (let i = row.length - 1; i >= 1; i--) { acc += row[i]; bnds.push({ dest: DEST[i], zUp: +invNorm(Math.min(acc, 1 - 1e-9)).toFixed(3) }); }\n Z[r] = bnds;\n });\n const PD = {}; Object.keys(TRANS).forEach(r => { PD[r] = TRANS[r][7] / 100; });\n // Prob de ≥1 default del libro a 1 año: 1 − Π(1 − PD_rating) sobre las posiciones\n const P_DEFAULT = 1 - positions.reduce((a, p) => a * (1 - PD[p.rating]), 1);\n return {\n W, RHO_ZERO_FACTOR, DEST, TRANS, Z, PD, P_DEFAULT,\n prevComparable: true, // cambio de supuesto efectivo 05/01/2026 < corte anterior 28/01 ⇒ Δ y chips comparables (rama N/D implementada, X-#6)\n RHO_UNIF: 25, // matriz uniforme ρ=25% axiomático (Alt 2): TODAS las celdas — el par intra-rating también es 25 (no es autocorrelación de un activo)\n };\n })();\n /* F2.9 — Sensibilidades. Barridos OAT precomputados del corte EOD con common random\n numbers (CRN), set de la metodología oficial (no editable). Factores multiplicativos\n sobre el VaR base (misma fórmula única mrAgg-VaR ≡ BT.VAR1A ≡ FR total — fuente única).\n Monotonía de ρ coherente con FR (X-#8 heredado): VaR(0)=0.78·b < VaR(15%)=0.885·b <\n VaR(20%)=0.93·b < b(25%) < VaR(35%)=1.13·b. wR = vector de reparto del ΔVaR por rating\n (Σ=1; ρ y σ cargan a ratings bajos, μ recovery carga donde vive la seniority) — el Δ de\n contribución Euler por rating es aditivo por construcción (BL/BR). Signo del barrido\n unilateral (fuente S&P→Moody's): +3.6% — la matriz Moody's del mock tiene PDs speculative-grade\n mayores (convención declarada del mock, X-12).\n prevComparable ÚNICO: se hereda de FR (mismo badge entre cortes). publishedUnderBadge\n gobierna la ancla badge↔barridos y DOMINA sobre prevComparable (X-1); en el mock es true\n y su rama degradada se demuestra con el estado \"partial\" del prototipo (X-7). */\n const SENS = (() => {\n const sweeps = [\n { id: \"rho\", lbl: \"ρ (correlación de activos)\", base: \"25%\", swp: \"15% / 35%\", fLo: 0.885, fHi: 1.130,\n wR: { AAA: 0.04, AA: 0.10, A: 0.24, BBB: 0.26, BB: 0.22, B: 0.14 } },\n { id: \"muSen\", lbl: \"μ recovery — senior\", base: \"45%\", swp: \"40% / 50%\", fLo: 1.072, fHi: 0.938,\n wR: { AAA: 0.08, AA: 0.16, A: 0.30, BBB: 0.24, BB: 0.14, B: 0.08 } },\n { id: \"sigSub\", lbl: \"σ recovery — subordinada\", base: \"28%\", swp: \"21% / 35%\", fLo: 0.962, fHi: 1.055,\n wR: { AAA: 0.02, AA: 0.06, A: 0.22, BBB: 0.30, BB: 0.26, B: 0.14 } },\n { id: \"muSub\", lbl: \"μ recovery — subordinada\", base: \"30%\", swp: \"25% / 35%\", fLo: 1.048, fHi: 0.960,\n wR: { AAA: 0.02, AA: 0.05, A: 0.20, BBB: 0.31, BB: 0.27, B: 0.15 } },\n { id: \"sigSen\", lbl: \"σ recovery — senior\", base: \"22%\", swp: \"16.5% / 27.5%\", fLo: 0.975, fHi: 1.038,\n wR: { AAA: 0.07, AA: 0.15, A: 0.29, BBB: 0.25, BB: 0.15, B: 0.09 } },\n { id: \"fuente\", lbl: \"Fuente de transición\", base: \"S&P\", swp: \"→ Moody's (alternativa única)\", fLo: null, fHi: 1.036, unilateral: true,\n wR: { AAA: 0.03, AA: 0.08, A: 0.22, BBB: 0.27, BB: 0.25, B: 0.15 } },\n ];\n // ΔVaR máx del corte anterior (factor sobre el VaR base anterior) — para la columna Var del BR\n const prevFmax = { rho: 0.126, muSen: 0.069, sigSub: 0.052, muSub: 0.046, sigSen: 0.036, fuente: 0.034 };\n return {\n sweeps, prevFmax,\n publishedUnderBadge: true, // ancla badge↔barridos (§13): true = el centro del tornado ES el supuesto del badge\n prevInfluyente: \"ρ (correlación de activos)\", // chip categórico del KPI 2 (comparable)\n };\n })();\n /* F2.5 — Escenarios (arquetipo simulador §9). Fuente única: VaR base ≡ BT.VAR1A.\n FV = factores VaR por ρ (heredados de SENS/FR: monotonía X-#8 — 0.885/1.0/1.13).\n FE = factores ES por ρ, MÁS empinados que FV (corrección X-1 F2.5: la cola engorda\n relativamente — ES/VaR sube 1.40→1.45→1.50; FE@25%=1.0 preserva la cuadratura con\n el ES total de Métricas de Riesgo). GP_RHO: el VM medio es casi invariante a ρ —\n la lectura del barrido es la franja VaR/ES, no el G/P (§9.7).\n Set de ρ NO editable en el mock (desviación declarada del §9.3 — feedback-log);\n anclas para implementación real: 0.78@ρ0 · 0.885@15 · 1.0@25 · 1.13@35.\n SENS_PD: sensibilidad del precio a +100bp de PD por rating (mock, multiplicador\n de repricing crediticio). REC = recovery base por seniority (μ/σ %). */\n const ESC = {\n RHO_SET: [15, 25, 35],\n FV: { 15: 0.885, 25: 1.0, 35: 1.13 },\n FE: { 15: 0.86, 25: 1.0, 35: 1.17 },\n GP_RHO: { 15: -0.42, 25: -0.51, 35: -0.63 },\n FUENTE_F: 1.036, // S&P → Moody's (convención X-12 de SENS: PDs speculative-grade mayores)\n FUENTE_GP: -14.20, // G/P total del cambio de fuente (repricing por PDs mayores)\n SENS_PD: { AAA: 1.5, AA: 2.2, A: 3.0, BBB: 4.0, BB: 5.2, B: 6.5 }, // % de precio por +100bp PD\n REC: { Senior: { mu: 45, sig: 22 }, Subordinada: { mu: 30, sig: 28 } },\n /* Jorobas de la mixture (silueta multimodal §9.8 — inviolable anti-Gauss):\n centro (VM MM), σ y peso base por nº de defaults; los pesos se recomponen con ρ\n (ρ alto → más masa en jorobas multi-default: la cola engorda, el centro apenas se mueve). */\n HUMPS: [\n { k: 0, mu: 6188, sig: 34 },\n { k: 1, mu: 6020, sig: 42 },\n { k: 2, mu: 5860, sig: 48 },\n { k: 3, mu: 5700, sig: 54 },\n { k: 4, mu: 5520, sig: 62 },\n ],\n W_RHO: {\n 15: [0.855, 0.118, 0.021, 0.005, 0.001],\n 25: [0.820, 0.135, 0.032, 0.010, 0.003],\n 35: [0.775, 0.150, 0.048, 0.019, 0.008],\n },\n };\n return { TC, TC_PREV, positions, RATINGS, TIPOS, DATES, HIST_TOTAL, HIST_SHARE, LIMITES, RISK, LIM_MEDIDA, MG_LIMITS, SUPUESTO_MARKERS, RHO_PREV_FACTOR, SUPUESTO, AS_OF, DATASET, BT, FR, SENS, ESC };\n})();\n",[154],"65c5d16f-7f09-4274-b2c2-a2e34a1ed052","app.js","4e8d6832-9d76-11f1-be1c-1607ee4eb77e",86,["D",1787333595841],64,"/* Risk Intelligence — Crédito (mock F2.2): shell + Portafolio (Global · Concentración)\n Tokens solo vía CSS vars. Riesgo/deltas en NEUTRO; semáforo solo estado de límite. */\n(() => {\n const D = window.RI_DATA;\n\n // ---------- Rutas / navegación ----------\n const SECTIONS = [\n { id: \"vision-general\", label: \"Visión General\", ico: \"◎\", tabs: [], noTabsBar: true, overview: true },\n { id: \"portafolio\", label: \"Portafolio\", ico: \"▤\", tabs: [{ id: \"global\", label: \"Global\" }, { id: \"concentracion\", label: \"Concentración\" }] },\n { id: \"sensibilidades\", label: \"Sensibilidades\", ico: \"≋\", tabs: [{ id: \"supuestos\", label: \"Supuestos\" }] },\n { id: \"metricas-de-riesgo\", label: \"Métricas de Riesgo\", ico: \"∿\", tabs: [{ id: \"a-la-fecha\", label: \"A la Fecha\" }, { id: \"historico\", label: \"Histórico\" }], medida: true },\n { id: \"marginal\", label: \"Marginal\", ico: \"◮\", tabs: [{ id: \"global\", label: \"Global\" }], medida: true },\n { id: \"factores-de-riesgo\", label: \"Factores de Riesgo\", ico: \"❖\", tabs: [{ id: \"mapa-de-factores\", label: \"Mapa de Factores\" }] },\n { id: \"escenarios\", label: \"Escenarios\", ico: \"⇄\", tabs: [{ id: \"impacto-en-riesgo\", label: \"Impacto en Riesgo\" }], placeholder: true },\n { id: \"backtesting\", label: \"Backtesting\", ico: \"◔\", tabs: [{ id: \"resumen-excepciones\", label: \"Resumen de Excepciones\" }] },\n ];\n const S = {\n uiState: \"ok\", // ok | loading | empty | error | partial\n moneda: \"Todas\", // Todas | DOP | USD (filtro F1.10)\n donaVista: \"Calificación\",\n blVista: \"Calificación\",\n concTL: \"pct\", // pct | dop\n concTR: \"hhi\", // hhi | mayor\n expanded: {}, // rating → bool\n medida: \"VaR\", // VaR | ES | Std (solo Métricas de Riesgo y Marginal — cambia datos, nunca layout)\n btQ: \"1%\", // Backtesting BL: cuantil de diagnóstico (no cambia la medida oficial ni KPIs)\n mrDona: \"Emisor\", // vista dona A la Fecha: Emisor (default §8.1) | Tipo de instrumento\n mrBL: \"Calificación\", // dimensión divergentes Histórico\n mrExp: {}, // tabla A la Fecha: rating → bool\n mrExpH: {}, // tabla Histórico: rating → bool\n mgDona: \"Emisor\", // vista dona Marginal (default §10.1) | Calificación | Tipo de instrumento\n mgExp: {}, // tabla Marginal: rating → bool\n mgExpE: {}, // tabla Marginal: \"rating|emisor\" → bool (nivel instrumento)\n frExp: {}, // tabla Factores: factor → bool (drill factor → rating, §12)\n frRating: null, // selector Merton TR: null = predominante por share de VM (§7.1); persiste a través de estados (X-#11)\n sensSel: null, // BL Sensibilidades: supuesto seleccionado (null = más influyente, §13)\n sensExt: null, // BL Sensibilidades: extremo −/+ (null = el de mayor |ΔVaR| del supuesto)\n sensExp: {}, // tabla Sensibilidades: supuesto → bool (drill supuesto → rating)\n filtersOpen: false,\n };\n let charts = [];\n\n function parseHash() {\n const h = location.hash.replace(/^#\\/?/, \"\");\n const [sec, tab] = h.split(\"/\");\n const section = SECTIONS.find(s => s.id === sec) || SECTIONS[0];\n const tabObj = section.tabs.find(t => t.id === tab) || section.tabs[0] || null;\n return { section, tab: tabObj };\n }\n function nav(sec, tab) { location.hash = \"#/\" + sec + (tab ? \"/\" + tab : \"\"); }\n\n // ---------- Formato (paridad producción: $13,476.90MM · M/MM nunca K) ----------\n const nf2 = new Intl.NumberFormat(\"en-US\", { minimumFractionDigits: 2, maximumFractionDigits: 2 });\n const nf1 = new Intl.NumberFormat(\"en-US\", { minimumFractionDigits: 1, maximumFractionDigits: 1 });\n const fMM = v => \"$\" + nf2.format(v) + \"MM\";\n const fPct = (v, d = 2) => (d === 1 ? nf1 : nf2).format(v) + \"%\";\n const fH = v => v.toFixed(4);\n const esc = s => String(s).replace(/&/g, \"&\").replace(//g, \">\").replace(/\"/g, \""\");\n\n // ---------- Agregación (DOP consolidado — L-4) ----------\n const dop = p => p.moneda === \"USD\" ? p.vm * D.TC : p.vm;\n const dopPrev = p => p.moneda === \"USD\" ? p.prev * D.TC_PREV : p.prev;\n const filt = () => D.positions.filter(p => S.moneda === \"Todas\" || p.moneda === S.moneda);\n function groupSum(list, key, val) {\n const m = new Map();\n list.forEach(p => m.set(p[key] ?? key(p), (m.get(p[key]) || 0) + val(p)));\n return m;\n }\n function aggBy(dim) { // dim: 'rating' | 'emisor' | 'tipo' | 'moneda'\n const m = new Map(), mp = new Map();\n filt().forEach(p => {\n const k = p[dim];\n m.set(k, (m.get(k) || 0) + dop(p));\n mp.set(k, (mp.get(k) || 0) + dopPrev(p));\n });\n return { cur: m, prev: mp };\n }\n const total = () => filt().reduce((a, p) => a + dop(p), 0);\n const totalPrev = () => filt().reduce((a, p) => a + dopPrev(p), 0);\n\n function emisorStats() {\n const { cur, prev } = aggBy(\"emisor\");\n const t = total();\n const rows = [...cur.entries()].map(([e, vm]) => {\n const monedas = new Set(filt().filter(p => p.emisor === e).map(p => p.moneda));\n const chip = monedas.size > 1 ? \"Mixta\" : [...monedas][0];\n const pct = t > 0 ? vm / t * 100 : 0;\n return { emisor: e, vm, prev: prev.get(e) || 0, pct, hhi: Math.pow(pct / 100, 2), chip };\n }).sort((a, b) => b.vm - a.vm);\n return rows;\n }\n function hhiOf(rows) { return rows.reduce((a, r) => a + r.hhi, 0); }\n function hhiPrev() {\n const { prev } = aggBy(\"emisor\");\n const tp = totalPrev();\n let h = 0; prev.forEach(v => { h += Math.pow(v / tp, 2); });\n return h;\n }\n function estadoEmisor(pct) { // semáforo SOLO estado de límite (con texto — nunca color solo)\n const lim = D.LIMITES.emisorPctInterno;\n if (pct > lim) return { cls: \"err\", txt: \"Exceso\" };\n if (pct >= lim * D.LIMITES.alertaFactor) return { cls: \"warn\", txt: \"Alerta\" };\n return { cls: \"ok\", txt: \"Ok\" };\n }\n\n // ---------- Paletas (mapping: ordinal azul; jamás semáforo en series) ----------\n const cs = getComputedStyle(document.documentElement);\n const TK = n => cs.getPropertyValue(n).trim();\n const ORDINAL = [\"#1f2a4e\", \"#28497c\", \"#0d77bf\", \"#4da3d8\", \"#8ec4e6\", \"#c4dff1\"]; // AAA→B (escala secuencial azul de colors-reports)\n const CATEG = [\"#0d77bf\", \"#1f2a4e\", \"#4da3d8\", \"#8ec4e6\", \"#6b7fae\", \"#a5b3d1\", \"#c4dff1\", \"#9aa4b8\"];\n const GRAY = \"#9aa4b8\";\n const ratColor = r => ORDINAL[D.RATINGS.indexOf(r)] ?? GRAY;\n\n // ---------- Render raíz ----------\n const $ = sel => document.querySelector(sel);\n function render() {\n charts.forEach(c => c.dispose()); charts = [];\n const { section, tab } = parseHash();\n renderSidebar(section);\n const main = $(\"#main\");\n const degraded = S.uiState === \"empty\" || S.uiState === \"error\";\n main.innerHTML = headHtml(section, tab, degraded) + tabsHtml(section, tab) + bodyHtml(section, tab);\n bindHead(); bindBody(section, tab);\n renderFilters();\n renderSwitch();\n }\n\n function renderSidebar(section) {\n $(\"#menu\").innerHTML = SECTIONS.map(s =>\n ``).join(\"\");\n document.querySelectorAll(\".menu-item\").forEach(b =>\n b.onclick = () => { const s = SECTIONS.find(x => x.id === b.dataset.sec); nav(s.id, s.tabs[0]?.id); });\n }\n\n // Cabecera de sección — badges FUERA de contenedores skeletonizables (X-2 / L-2)\n function headHtml(section, tab, degraded) {\n const sup = degraded\n ? `Supuesto: N/D`\n : `Supuesto: ${D.SUPUESTO.fuente} · ${D.SUPUESTO.metodo} · ${D.SUPUESTO.tc}`;\n const dataBadge = S.uiState === \"error\"\n ? `⚠ Error de datos`\n : S.uiState === \"empty\"\n ? `◌ Dataset no listo`\n : `Datos ${D.AS_OF} ⟳`;\n const crumb = section.noTabsBar\n ? `${section.label}`\n : `${section.label} / ${tab ? tab.label : \"\"}`;\n const selMedida = section.medida\n ? `${[\"VaR\", \"ES\", \"Std\"].map(m =>\n ``).join(\"\")}`\n : \"\";\n const chipVentana = section.id === \"backtesting\" && S.uiState !== \"empty\" && S.uiState !== \"error\"\n ? `Ventana: ${D.BT.cambios} cambio de supuesto`\n : \"\";\n return `

\n \n

\n ${selMedida}\n ⓘ ${sup}\n ${chipVentana}\n ${dataBadge}\n ${D.DATASET} ▾\n ${section.overview ? \"\" : ``}\n

`;\n }\n function tabsHtml(section, tab) {\n if (section.noTabsBar || !section.tabs.length) return `

`;\n return `

` + section.tabs.map(t =>\n ``).join(\"\") + `

`;\n }\n function bindHead() {\n const b = $(\"#btnFiltros\"); if (b) b.onclick = () => { S.filtersOpen = true; renderFilters(); };\n document.querySelectorAll(\"[data-med]\").forEach(x => x.onclick = () => { S.medida = x.dataset.med; render(); });\n document.querySelectorAll(\".tab-pill\").forEach(p =>\n p.onclick = () => { const { section } = parseHash(); nav(section.id, p.dataset.tab); });\n }\n\n // ---------- Cuerpos ----------\n function bodyHtml(section, tab) {\n if (section.overview) return visionHtml();\n if (section.placeholder) return placeholderHtml(section);\n if (section.id === \"portafolio\" && tab.id === \"global\") return globalHtml();\n if (section.id === \"portafolio\" && tab.id === \"concentracion\") return concHtml();\n if (section.id === \"metricas-de-riesgo\" && tab.id === \"a-la-fecha\") return mrFechaHtml();\n if (section.id === \"metricas-de-riesgo\" && tab.id === \"historico\") return mrHistHtml();\n if (section.id === \"marginal\") return mgHtml();\n if (section.id === \"factores-de-riesgo\") return frHtml();\n if (section.id === \"sensibilidades\") return sensHtml();\n if (section.id === \"backtesting\") return btHtml();\n return \"\";\n }\n\n function placeholderHtml(section) {\n if (S.uiState === \"loading\") return `

`;\n if (S.uiState === \"error\") return `

${errBox()}

`;\n if (S.uiState === \"empty\") return `

${emptyBox()}

`;\n return `

\n ${section.label}\n Sección activa del módulo — contenido en la próxima iteración del prototipo.
\n El wireframe aprobado (03-wireframe-specs.md) define esta pantalla; este mock la incorpora incrementalmente.\n

`;\n }\n\n const emptyBox = () => `

◌\n Sin datos para este corte\n El dataset seleccionado aún no tiene resultados. Selecciona otro dataset en el selector superior o ejecuta el cálculo del corte.

`;\n const errBox = () => `

⚠\n No se pudo cargar la información\n Ocurrió un error al consultar los datos del corte. Puedes reintentar la carga.\n

`;\n\n function kpiCard(title, big, sub, rows) {\n return `

${title}

${big}

\n ${sub ? `

${sub}

` : \"\"}\n ${rows && rows.length ? `

` + rows.map(r =>\n `

${r[0]}${r[1]}

`).join(\"\") + `

` : \"\"}\n

`;\n }\n function kpiSkeletons() { return `

`.repeat(5); }\n function panelSkeletons(n = 4) { return `

`.repeat(n); }\n function statePanels(box, n = 4) { return Array(n).fill(`

${box}

`).join(\"\"); }\n\n function subtituloConsolidacion() {\n if (S.moneda === \"Todas\") return \"Consolidado en DOP · TC del corte\";\n return `Solo instrumentos ${S.moneda} · Consolidado en DOP · TC del corte`;\n }\n\n // ====== Portafolio › Global (§7.1) ======\n function globalHtml() {\n if (S.uiState === \"loading\") return `

${kpiSkeletons()}

${panelSkeletons()}

`;\n if (S.uiState === \"empty\") return `

${kpisND(\"N/D\")}

${statePanels(emptyBox())}

`;\n if (S.uiState === \"error\") return `

${kpisND(\"N/D\")}

${statePanels(errBox())}

`;\n\n const t = total(), tp = totalPrev(), dv = t - tp, dvp = tp > 0 ? dv / tp * 100 : 0;\n const pos = filt(), nPos = pos.length, nPosPrev = pos.filter(p => p.prev > 0).length;\n const emis = new Set(pos.map(p => p.emisor)).size;\n const emisPrev = new Set(pos.filter(p => p.prev > 0).map(p => p.emisor)).size;\n const byR = aggBy(\"rating\");\n let predom = null, predomPrev = null;\n byR.cur.forEach((v, k) => { if (!predom || v > byR.cur.get(predom)) predom = k; });\n byR.prev.forEach((v, k) => { if (!predomPrev || v > byR.prev.get(predomPrev)) predomPrev = k; });\n const shareNow = byR.cur.get(predom) / t * 100;\n const sharePrev = totalPrev() > 0 ? (byR.prev.get(predom) || 0) / totalPrev() * 100 : 0;\n const sameCat = predom === predomPrev;\n const arrow = sameCat ? (shareNow >= sharePrev ? \"▲\" : \"▼\") : \"\"; // flecha = Δ share del rating predominante actual (X-19)\n const eRows = emisorStats(); const hhi = hhiOf(eRows);\n const usoHHI = hhi / D.LIMITES.hhiInterno * 100;\n const excG = eRows.filter(r => estadoEmisor(r.pct).txt === \"Exceso\").length;\n const alG = eRows.filter(r => estadoEmisor(r.pct).txt === \"Alerta\").length;\n const worst = excG ? [\"err\", \"Exceso\"] : (alG || usoHHI >= 90) ? [\"warn\", \"Alerta\"] : usoHHI > 100 ? [\"err\", \"Exceso\"] : [\"ok\", \"Ok\"];\n const kpis =\n kpiCard(\"VM Total\", fMM(t), esc(subtituloConsolidacion()), [\n [\"anterior\", fMM(tp)], [\"Δ\", (dv >= 0 ? \"+\" : \"−\") + fMM(Math.abs(dv)).slice(1), \"trend\"], [\"Δ%\", fPct(dvp), \"trend\"]]) +\n kpiCard(\"N° Posiciones\", String(nPos), null, [[\"anterior\", String(nPosPrev)], [\"Δ\", String(nPos - nPosPrev), \"trend\"]]) +\n kpiCard(\"N° Emisores\", String(emis), null, [[\"anterior\", String(emisPrev)], [\"Δ\", String(emis - emisPrev), \"trend\"]]) +\n kpiCard(\"Calificación predominante\", `${predom} ${arrow}`,\n `share ${fPct(shareNow, 1)} (ant. ${sameCat ? fPct(sharePrev, 1) : \"categoría distinta: \" + predomPrev})`, []) +\n kpiCard(\"Límite de concentración\", `${worst[1]}`,\n `HHI ${fH(hhi)} vs límite ${fH(D.LIMITES.hhiInterno)} · uso ${fPct(usoHHI, 1)}${excG || alG ? ` · límites por emisor: ${excG} incumplimiento(s), ${alG} alerta(s) — ver Concentración` : \" · límites por emisor sin excepciones\"}`, []);\n\n return `

${kpis}

Valor de Mercado por Calificación

Temporalidad: Año a la Fecha ▾ · Eje en DOP MM. Cada punto consolidado al TC de su fecha.

${S.uiState === \"partial\" ? errBox() : `\n

Composición del Portafolio

Participación sobre VM Total (DOP consolidado).${S.donaVista === \"Emisor\" ? \" Vista por emisor: top-7 + “Otros”.\" : \"\"}

Cambio en la Composición

Δ VM vs. corte anterior (DOP consolidado); barras en neutro — el signo lo comunica la posición y la etiqueta.

Tabla de Composición

${tablaGlobal()}

Variaciones al TC de cada corte; incluyen efecto FX. “—” = sin posiciones en el grupo; “N/D” = sin corte anterior (nunca 0).

`;\n }\n\n function kpisND(sym) {\n return [\"VM Total\", \"N° Posiciones\", \"N° Emisores\", \"Calificación predominante\", \"Límite de concentración\"]\n .map(t => kpiCard(t, sym, t === \"VM Total\" ? esc(subtituloConsolidacion()) : null, [])).join(\"\");\n }\n\n function tablaGlobal() {\n const t = total();\n const rows = D.RATINGS.map(r => {\n const ps = filt().filter(p => p.rating === r);\n if (!ps.length) return null;\n const agg = list => ({\n dop: list.filter(p => p.moneda === \"DOP\").reduce((a, p) => a + p.vm, 0),\n usd: list.filter(p => p.moneda === \"USD\").reduce((a, p) => a + p.vm, 0),\n tot: list.reduce((a, p) => a + dop(p), 0),\n prev: list.reduce((a, p) => a + dopPrev(p), 0),\n });\n const a = agg(ps);\n const emisores = [...new Set(ps.map(p => p.emisor))].map(e => {\n const l = ps.filter(p => p.emisor === e);\n const ea = agg(l);\n const monedas = new Set(l.map(p => p.moneda));\n return { e, a: ea, chip: monedas.size > 1 ? \"Mixta\" : [...monedas][0] };\n }).sort((x, y) => y.a.tot - x.a.tot);\n return { r, a, emisores };\n }).filter(Boolean);\n\n const cell = (v, unit) => v > 0 ? fMM(v) : \"—\";\n const varCells = a => {\n if (a.prev <= 0) return `N/DN/D`;\n const dv = a.tot - a.prev;\n return `${(dv >= 0 ? \"+\" : \"−\") + fMM(Math.abs(dv)).slice(1)}${fPct(dv / a.prev * 100)}`;\n };\n let html = `\n \n `;\n rows.forEach(({ r, a, emisores }) => {\n const open = !!S.expanded[r];\n html += `\n \n ${varCells(a)}`;\n if (open) emisores.forEach(({ e, a: ea, chip }) => {\n html += `\n \n ${varCells(ea)}`;\n });\n });\n return html + `

Calificación	Valor de Mercado	% Global	Var (DOP)	Var %
DOP	USD	Total (DOP)
${open ? \"▾\" : \"▸\"}${r}	${cell(a.dop)}	${a.usd > 0 ? \"$\" + nf2.format(a.usd) + \"MM\" : \"—\"}	${fMM(a.tot)}	${fPct(a.tot / t * 100)}
${esc(e)} ${chip}	${cell(ea.dop)}	${ea.usd > 0 ? \"$\" + nf2.format(ea.usd) + \"MM\" : \"—\"}	${fMM(ea.tot)}	${fPct(ea.tot / t * 100)}

`;\n }\n\n // ====== Portafolio › Concentración (§7.2) ======\n function concHtml() {\n if (S.uiState === \"loading\") return `

${kpiSkeletons()}

${panelSkeletons()}

`;\n if (S.uiState === \"empty\") return `

${kpisNDConc(\"N/D\")}

${statePanels(emptyBox())}

`;\n if (S.uiState === \"error\") return `

${kpisNDConc(\"N/D\")}

${statePanels(errBox())}

`;\n\n const rows = emisorStats(); const hhi = hhiOf(rows); const hp = hhiPrev();\n const nEff = hhi > 0 ? 1 / hhi : 0;\n const top5 = rows.slice(0, 5).reduce((a, r) => a + r.pct, 0);\n const tp = totalPrev();\n const top5prev = rows.slice(0, 5).reduce((a, r) => a + (tp > 0 ? r.prev / tp * 100 : 0), 0);\n const mayor = rows[0];\n const estM = estadoEmisor(mayor.pct);\n const holg = D.LIMITES.emisorPctInterno - mayor.pct;\n const alertas = rows.filter(r => estadoEmisor(r.pct).txt === \"Alerta\").length;\n const exc = rows.filter(r => estadoEmisor(r.pct).txt === \"Exceso\").length;\n\n const kpis =\n kpiCard(\"HHI\", fH(hhi), `≈ ${nEff.toFixed(1)} emisores efectivos (1/HHI)`, [\n [\"anterior\", fH(hp)], [\"Δ\", (hhi - hp >= 0 ? \"+\" : \"−\") + fH(Math.abs(hhi - hp)), \"trend\"]]) +\n kpiCard(\"Share Top-5 emisores\", fPct(top5, 1), \"% del VM (DOP consolidado)\", [\n [\"anterior\", fPct(top5prev, 1)], [\"Δ\", fPct(top5 - top5prev, 1) + \" pp\", \"trend\"]]) +\n kpiCard(\"Mayor concentración\", esc(mayor.emisor), `${fPct(mayor.pct, 1)} del VM · ${holg >= 0 ? \"Holgura +\" + nf1.format(holg) : \"Exceso \" + nf1.format(Math.abs(holg))} pp vs. límite ${estM.txt}${S.moneda !== \"Todas\" ? \" · límites evaluados sobre el universo filtrado (\" + S.moneda + \"), no sobre el portafolio\" : \"\"}`, []) +\n kpiCard(\"Δ HHI vs. corte anterior\", `${(hhi - hp >= 0 ? \"+\" : \"−\") + fH(Math.abs(hhi - hp))}`, \"puntos de HHI\", []) +\n kpiCard(\"Estado de Límites\", `${exc ? \"Exceso\" : alertas ? \"Alerta\" : \"Ok\"}`,\n `Alertas: ${alertas} · Incumplimientos: ${exc} — límite interno ${fPct(D.LIMITES.emisorPctInterno, 1)} por emisor${S.moneda !== \"Todas\" ? \" · evaluados sobre el universo filtrado (\" + S.moneda + \")\" : \"\"}`, []);\n\n return `

${kpis}

Top Emisores

Top-7 + “Otros” por ${S.concTL === \"pct\" ? \"% del VM\" : \"VM (DOP consolidado)\"}.

${S.uiState === \"partial\" ? errBox() : `\n

Evolución de la Concentración

Línea punteada = límite interno. Cada punto consolidado al TC de su fecha.

Cambio en la Composición por Emisor

Δ VM vs. corte anterior — top-7 por |Δ| + “Otros” + Total; barras en neutro.

Tabla de Concentración por Emisor

${tablaConc(rows, hhi)}

Lista completa (exenta de top-7): un emisor en alerta o exceso jamás queda oculto. Límites de exposición sobre VM observado. Sin límite → “N/D”.

`;\n }\n function kpisNDConc(sym) {\n return [\"HHI\", \"Share Top-5 emisores\", \"Mayor concentración\", \"Δ HHI vs. corte anterior\", \"Estado de Límites\"]\n .map(t => kpiCard(t, sym, null, [])).join(\"\");\n }\n function tablaConc(rows, hhi) {\n let html = ``;\n rows.forEach(r => {\n const st = estadoEmisor(r.pct);\n const holg = D.LIMITES.emisorPctInterno - r.pct;\n html += `\n \n \n `;\n });\n return html + `

Emisor	Moneda	VM (DOP)	% VM	Aporte HHI	Límite interno	Holgura/Exceso
${esc(r.emisor)}	${r.chip}	${fMM(r.vm)}	${fPct(r.pct)}	${r.hhi.toFixed(4)}	${fPct(D.LIMITES.emisorPctInterno, 1)}	${(holg >= 0 ? \"+\" : \"\") + nf1.format(holg)} pp ${st.txt}

`;\n }\n\n // ====== Métricas de Riesgo (§8) ======\n // Las medidas se calculan SIEMPRE sobre la cartera consolidada completa — el filtro de\n // moneda NO aplica aquí (X-3/X-4: partición prohibida por cuotas; VaR no aditivo).\n const RM = () => D.RISK[S.medida];\n function vmFull(getVal) {\n const m = new Map();\n D.positions.forEach(p => m.set(p.rating, (m.get(p.rating) || 0) + getVal(p)));\n return m;\n }\n function mrAgg(prev = false) {\n const vm = vmFull(prev ? dopPrev : dop);\n const rows = D.RATINGS.filter(r => vm.has(r) && vm.get(r) > 0).map(r => {\n const stand = vm.get(r) * RM().rate[r];\n return { r, vm: vm.get(r), stand, contrib: stand * RM().divF[r] };\n });\n return {\n rows,\n total: rows.reduce((a, x) => a + x.contrib, 0),\n standSum: rows.reduce((a, x) => a + x.stand, 0),\n vmTot: rows.reduce((a, x) => a + x.vm, 0),\n };\n }\n function mrEmisores(prev = false) { // prorrateo por exposición dentro del rating (§2)\n const getVal = prev ? dopPrev : dop;\n const vm = vmFull(getVal);\n const m = new Map();\n D.positions.forEach(p => {\n if (!vm.get(p.rating)) return;\n const contribR = vm.get(p.rating) * RM().rate[p.rating] * RM().divF[p.rating];\n m.set(p.emisor, (m.get(p.emisor) || 0) + contribR * getVal(p) / vm.get(p.rating));\n });\n return [...m.entries()].sort((a, b) => b[1] - a[1]);\n }\n function mrTipos() { // contribución prorrateada por tipo de instrumento (misma base rating)\n const vm = vmFull(dop);\n const m = new Map();\n D.positions.forEach(p => {\n const contribR = vm.get(p.rating) * RM().rate[p.rating] * RM().divF[p.rating];\n m.set(p.tipo, (m.get(p.tipo) || 0) + contribR * dop(p) / vm.get(p.rating));\n });\n return [...m.entries()].sort((a, b) => b[1] - a[1]);\n }\n const mrMarkerIdx = () => D.DATES.indexOf(D.SUPUESTO_MARKERS[0].fecha);\n function mrHistSeries() { // ρ=20% antes del marcador → factor RHO_PREV_FACTOR (discontinuidad honesta)\n const mk = mrMarkerIdx();\n const cur = mrAgg();\n return D.RATINGS.map(r => ({\n r,\n data: D.DATES.map((_, i) => {\n if (i === D.DATES.length - 1) { const row = cur.rows.find(x => x.r === r); return row ? +row.contrib.toFixed(2) : 0; }\n const vmT = (D.HIST_SHARE[r][i] || 0) * D.HIST_TOTAL[i];\n return +(vmT * RM().rate[r] * RM().divF[r] * (i < mk ? D.RHO_PREV_FACTOR : 1)).toFixed(2);\n }),\n }));\n }\n function mrHistTotals() {\n const s = mrHistSeries();\n return D.DATES.map((_, i) => s.reduce((a, x) => a + x.data[i], 0));\n }\n const parseFecha = f => { const [d, m, y] = f.split(\"/\").map(Number); return new Date(y, m - 1, d); };\n function volAnualizada() { // σ descriptiva del VM del libro; anualiza por Δt promedio REAL (X-8)\n const vals = [...D.HIST_TOTAL]; vals[vals.length - 1] = mrAgg().vmTot;\n const rets = [];\n for (let i = 1; i < vals.length; i++) rets.push(Math.log(vals[i] / vals[i - 1]));\n const mu = rets.reduce((a, b) => a + b, 0) / rets.length;\n const sd = Math.sqrt(rets.reduce((a, b) => a + (b - mu) ** 2, 0) / (rets.length - 1));\n const spanDias = (parseFecha(D.DATES[D.DATES.length - 1]) - parseFecha(D.DATES[0])) / 86400000;\n const dtProm = spanDias / (D.DATES.length - 1);\n return { vol: sd * Math.sqrt(252 / dtProm) * 100, dtProm };\n }\n const LEYENDA_PRORRATEO = \"Contribución prorrateada por exposición — el modelo opera a nivel rating y no diferencia emisores dentro del rating (§2).\";\n\n function usoLimiteCard(total) {\n const lim = D.LIM_MEDIDA[S.medida];\n if (lim == null) return kpiCard(\"Uso Límite\",\n `N/D`,\n `Sin límite configurado para ${S.medida}`, []);\n const uso = total / lim * 100;\n const st = uso > 100 ? [\"err\", \"Incumplimiento\"] : uso >= 90 ? [\"warn\", \"Advertencia\"] : [\"ok\", \"Ok\"];\n return kpiCard(\"Uso Límite\", `${fPct(uso, 1)} ${st[1]}`,\n `${S.medida} vs. límite interno ${fMM(lim)} · cartera consolidada completa`, []);\n }\n const notaMonedaMR = `

Las medidas de riesgo se calculan sobre la cartera consolidada completa (DOP al TC del corte) y jamás se parten por moneda — el ${esc(S.medida)} no es aditivo entre sub-universos. El filtro de moneda no aplica en esta sección.

`;\n\n // --- Tab A la Fecha (§8.1) ---\n const MR_F_TITLES = () => [`${S.medida} Total`, `Razón ${S.medida}/VM`, \"Top Driver\", \"Beneficio de diversificación\", \"Uso Límite\"];\n function kpisNDMR(titles) { return titles.map(t => kpiCard(t, \"N/D\", null, [])).join(\"\"); }\n\n function mrFechaHtml() {\n if (S.uiState === \"loading\") return `

${kpiSkeletons()}

${panelSkeletons()}

`;\n if (S.uiState === \"empty\") return `

${kpisNDMR(MR_F_TITLES())}

${statePanels(emptyBox())}

`;\n if (S.uiState === \"error\") return `

${kpisNDMR(MR_F_TITLES())}

${statePanels(errBox())}

`;\n\n const a = mrAgg(), ap = mrAgg(true);\n const dv = a.total - ap.total, dvp = ap.total > 0 ? dv / ap.total * 100 : null;\n const razon = a.total / a.vmTot * 100;\n const emis = mrEmisores(), emisPrev = mrEmisores(true);\n const top = emis[0], topPrev = emisPrev[0];\n const ben = a.standSum - a.total, benPct = a.standSum > 0 ? ben / a.standSum * 100 : 0;\n const benTip = ben >= 0\n ? (S.medida === \"VaR\" ? \"Diversificación de cartera: Σ standalone − cartera. El VaR no es subaditivo — bajo concentración la brecha podría ser negativa.\" : `${S.medida} es subaditiva: el beneficio de diversificación es siempre ≥ 0.`)\n : \"El VaR no es subaditivo: penalización por concentración.\";\n const benLabel = ben >= 0 ? \"Beneficio de diversificación\" : \"Penalización por concentración\";\n\n const kpis =\n kpiCard(`${S.medida} Total`, fMM(a.total), \"Consolidado en DOP · TC del corte\", [\n [\"anterior\", fMM(ap.total)],\n [\"Δ\", (dv >= 0 ? \"+\" : \"−\") + fMM(Math.abs(dv)).slice(1), \"trend\"],\n [\"Δ%\", dvp === null ? \"N/D\" : fPct(dvp), \"trend\"]]) +\n kpiCard(`Razón ${S.medida}/VM`, fPct(razon), \"sobre el VM consolidado de la cartera\", [\n [\"anterior\", ap.vmTot > 0 ? fPct(ap.total / ap.vmTot * 100) : \"N/D\"],\n [\"Δ\", ap.vmTot > 0 ? (razon - ap.total / ap.vmTot * 100 >= 0 ? \"+\" : \"−\") + nf2.format(Math.abs(razon - ap.total / ap.vmTot * 100)) + \" pp\" : \"N/D\", \"trend\"]]) +\n kpiCard(\"Top Driver\", esc(top[0]),\n `${fMM(top[1])} · ${fPct(top[1] / a.total * 100, 1)} del ${esc(S.medida)}
${esc(LEYENDA_PRORRATEO)}`, [\n [\"anterior\", esc(topPrev[0])]]) +\n kpiCard(`${benLabel} ⓘ`,\n (ben >= 0 ? \"\" : \"−\") + fMM(Math.abs(ben)),\n `${fPct(Math.abs(benPct), 1)} de la suma standalone (Σ ${esc(S.medida)} standalone − ${esc(S.medida)} de cartera)`, []) +\n usoLimiteCard(a.total);\n\n return `

${kpis}

${S.medida} por Calificación

Contribución a la cartera por rating, orden de escala AAA→B (DOP MM). Cero real = barra en 0; sin dato = barra ausente + “N/D”.

${S.uiState === \"partial\" ? errBox() : `\n

Contribución al ${S.medida}

${S.mrDona === \"Emisor\" ? \"Top-7 + “Otros”. \" : \"\"}${LEYENDA_PRORRATEO}

Standalone vs. Contribución por Calificación

La brecha entre ${S.medida} standalone y contribución a cartera es la diversificación. La vista por posición vive en Marginal.

Descomposición del ${S.medida}

${tablaMrFecha(a)}

Solo el VM se parte por moneda; el ${S.medida} va siempre en DOP consolidado (no aditivo entre monedas). Filas de emisor: ${LEYENDA_PRORRATEO} Las variaciones viven en el tab Histórico.

${notaMonedaMR}

`;\n }\n\n function tablaMrFecha(a) {\n let html = `\n \n `;\n D.RATINGS.forEach(r => {\n const ps = D.positions.filter(p => p.rating === r); if (!ps.length) return;\n const vmDop = ps.filter(p => p.moneda === \"DOP\").reduce((x, p) => x + p.vm, 0);\n const vmUsd = ps.filter(p => p.moneda === \"USD\").reduce((x, p) => x + p.vm, 0);\n const vmTot = ps.reduce((x, p) => x + dop(p), 0);\n const contribR = vmTot * RM().rate[r] * RM().divF[r];\n const open = !!S.mrExp[r];\n html += `\n \n `;\n if (open) {\n const byE = new Map();\n ps.forEach(p => byE.set(p.emisor, [...(byE.get(p.emisor) || []), p]));\n [...byE.entries()].sort((x, y) => y[1].reduce((s, p) => s + dop(p), 0) - x[1].reduce((s, p) => s + dop(p), 0)).forEach(([e, l]) => {\n const eDop = l.filter(p => p.moneda === \"DOP\").reduce((x, p) => x + p.vm, 0);\n const eUsd = l.filter(p => p.moneda === \"USD\").reduce((x, p) => x + p.vm, 0);\n const eTot = l.reduce((x, p) => x + dop(p), 0);\n const eContrib = contribR * eTot / vmTot;\n const chip = new Set(l.map(p => p.moneda)).size > 1 ? \"Mixta\" : l[0].moneda;\n html += `\n \n `;\n });\n }\n });\n return html + `

Calificación	Valor de Mercado	${S.medida} (DOP)	% del ${S.medida}
DOP	USD	Total (DOP)
${open ? \"▾\" : \"▸\"}${r}	${vmDop > 0 ? fMM(vmDop) : \"—\"}	${vmUsd > 0 ? \"$\" + nf2.format(vmUsd) + \"MM\" : \"—\"}	${fMM(vmTot)}	${fMM(contribR)}	${fPct(contribR / mrAgg().total * 100)}
${esc(e)} ${chip}	${eDop > 0 ? fMM(eDop) : \"—\"}	${eUsd > 0 ? \"$\" + nf2.format(eUsd) + \"MM\" : \"—\"}	${fMM(eTot)}	${fMM(eContrib)} prorr.	${fPct(eContrib / mrAgg().total * 100)}

`;\n }\n\n // --- Tab Histórico (§8.2) ---\n const MR_H_TITLES = () => [`${S.medida} Total`, `Rating de mayor Δ ${S.medida}`, \"Volatilidad anualizada del VM\", `Δ Razón ${S.medida}/VM`, \"Uso Límite\"];\n\n function mrHistHtml() {\n if (S.uiState === \"loading\") return `

${kpiSkeletons()}

${panelSkeletons()}

`;\n if (S.uiState === \"empty\") return `

${kpisNDMR(MR_H_TITLES())}

${statePanels(emptyBox())}

`;\n if (S.uiState === \"error\") return `

${kpisNDMR(MR_H_TITLES())}

${statePanels(errBox())}

`;\n\n const a = mrAgg(), ap = mrAgg(true);\n const dv = a.total - ap.total, dvp = ap.total > 0 ? dv / ap.total * 100 : null;\n // Rating de mayor Δ — desempate: |Δ|, luego orden de escala (X-14)\n const deltas = a.rows.map(x => {\n const prev = ap.rows.find(y => y.r === x.r);\n return { r: x.r, d: x.contrib - (prev ? prev.contrib : 0) };\n }).sort((x, y) => Math.abs(y.d) - Math.abs(x.d) || D.RATINGS.indexOf(x.r) - D.RATINGS.indexOf(y.r));\n const mx = deltas[0];\n const razon = a.total / a.vmTot * 100, razonPrev = ap.vmTot > 0 ? ap.total / ap.vmTot * 100 : null;\n const { vol, dtProm } = volAnualizada();\n\n const kpis =\n kpiCard(`${S.medida} Total`, fMM(a.total), \"Consolidado en DOP · TC del corte\", [\n [\"anterior\", fMM(ap.total)],\n [\"Δ\", (dv >= 0 ? \"+\" : \"−\") + fMM(Math.abs(dv)).slice(1), \"trend\"],\n [\"Δ%\", dvp === null ? \"N/D\" : fPct(dvp), \"trend\"]]) +\n kpiCard(`Rating de mayor Δ ${S.medida}`, mx.r,\n `${(mx.d >= 0 ? \"+\" : \"−\") + fMM(Math.abs(mx.d))} vs. corte anterior · desempate por |Δ| y orden de escala`, [\n [\"anterior\", mx.r]]) +\n kpiCard(`Volatilidad anualizada del VM ⓘ`,\n fPct(vol, 1), \"no conmuta con el selector de medida\", []) +\n kpiCard(`Δ Razón ${S.medida}/VM`,\n razonPrev === null ? \"N/D\" : (razon - razonPrev >= 0 ? \"+\" : \"−\") + nf2.format(Math.abs(razon - razonPrev)) + \" pp\",\n \"separa efecto nivel de efecto tamaño del libro\", [\n [\"anterior\", razonPrev === null ? \"N/D\" : fPct(razonPrev)]]) +\n usoLimiteCard(a.total);\n\n return `

${kpis}

Evolución del ${S.medida} por Calificación

Cima del apilado = ${S.medida} Total. Línea vertical = cambio de supuesto — la serie no se lee como continua entre supuestos distintos (§2). Cada punto consolidado al TC de su fecha.

${S.uiState === \"partial\" ? errBox() : `\n

Evolución de la Razón ${S.medida}/VM

Intensidad de riesgo del libro (%). Mismos marcadores de cambio de supuesto que la serie de la izquierda.

Cambio del ${S.medida} vs. Corte Anterior

Δ vs. corte anterior (28/01 — mismo supuesto que el as_of; los cortes previos al 03/01 no son comparables punto a punto por cambio de supuesto). Barras en neutro.${S.mrBL === \"Emisor\" ? \" Top-7 por |Δ| + “Otros”. \" + LEYENDA_PRORRATEO : \"\"}

Comparativa por Calificación

${tablaMrHist(a, ap)}

Variaciones al TC de cada corte; incluyen efecto FX. Cada punto consolidado al TC de su fecha. Δ solo entre cortes con el mismo supuesto — supuesto distinto → “N/D”, nunca 0. Filas de emisor: ${LEYENDA_PRORRATEO}

${notaMonedaMR}

`;\n }\n\n function tablaMrHist(a, ap) {\n let html = `\n \n `;\n D.RATINGS.forEach(r => {\n const ps = D.positions.filter(p => p.rating === r); if (!ps.length) return;\n const vmDop = ps.filter(p => p.moneda === \"DOP\").reduce((x, p) => x + p.vm, 0);\n const vmUsd = ps.filter(p => p.moneda === \"USD\").reduce((x, p) => x + p.vm, 0);\n const vmTot = ps.reduce((x, p) => x + dop(p), 0);\n const cur = a.rows.find(x => x.r === r), prev = ap.rows.find(x => x.r === r);\n const varCells = prev\n ? ``\n : ``;\n const open = !!S.mrExpH[r];\n html += `\n \n ${varCells}`;\n if (open) {\n const byE = new Map();\n ps.forEach(p => byE.set(p.emisor, [...(byE.get(p.emisor) || []), p]));\n [...byE.entries()].forEach(([e, l]) => {\n const eTot = l.reduce((x, p) => x + dop(p), 0), ePrev = l.reduce((x, p) => x + dopPrev(p), 0);\n const eContrib = cur.contrib * eTot / vmTot;\n const eContribPrev = prev && ap.rows.find(x => x.r === r) ? prev.contrib * ePrev / ap.rows.find(x => x.r === r).vm : null;\n const eDop = l.filter(p => p.moneda === \"DOP\").reduce((x, p) => x + p.vm, 0);\n const eUsd = l.filter(p => p.moneda === \"USD\").reduce((x, p) => x + p.vm, 0);\n const chip = new Set(l.map(p => p.moneda)).size > 1 ? \"Mixta\" : l[0].moneda;\n const vCells = eContribPrev && ePrev > 0\n ? ``\n : ``;\n html += `\n \n ${vCells}`;\n });\n }\n });\n return html + `

Calificación	Valor de Mercado	${S.medida} (DOP)	Var (DOP)	Var %
DOP	USD	Total (DOP)
${(cur.contrib - prev.contrib >= 0 ? \"+\" : \"−\") + fMM(Math.abs(cur.contrib - prev.contrib)).slice(1)}	${fPct((cur.contrib - prev.contrib) / prev.contrib * 100)}	N/D	N/D
${open ? \"▾\" : \"▸\"}${r}	${vmDop > 0 ? fMM(vmDop) : \"—\"}	${vmUsd > 0 ? \"$\" + nf2.format(vmUsd) + \"MM\" : \"—\"}	${fMM(vmTot)}	${fMM(cur.contrib)}
${(eContrib - eContribPrev >= 0 ? \"+\" : \"−\") + fMM(Math.abs(eContrib - eContribPrev)).slice(1)}	${fPct((eContrib - eContribPrev) / eContribPrev * 100)}	N/D	N/D
${esc(e)} ${chip}	${eDop > 0 ? fMM(eDop) : \"—\"}	${eUsd > 0 ? \"$\" + nf2.format(eUsd) + \"MM\" : \"—\"}	${fMM(eTot)}	${fMM(eContrib)} prorr.

`;\n }\n\n // ====== Marginal (§10) — salidas directas por posición: leave-one-out (marginal),\n // Euler (componental) y standalone. La cartera es SIEMPRE la consolidada completa.\n const NOTA_GRANULARIDAD = \"En el modelo, los emisores de una misma calificación comparten distribución — las diferencias por posición provienen de su exposición y de la realización simulada de su escenario.\";\n const MG_TITLES = () => [`${S.medida} Marginal promedio`, \"Mayor contribución\", \"Posiciones sobre umbral\", \"HHI de contribuciones\", \"Uso Límite\"];\n function mgRows(prev = false) {\n const getVal = prev ? dopPrev : dop;\n // base: standalone y componental Euler por posición (misma fórmula que Métricas por rating)\n const base = D.positions.map(p => {\n const v = getVal(p);\n const stand = v * RM().rate[p.rating];\n return { p, v, stand, comp: stand * RM().divF[p.rating] };\n });\n // diversificadoras (realización simulada — §2: no es atributo del emisor): componental\n // negativa; el excedente se redistribuye proporcionalmente INTRA-RATING → los subtotales\n // por rating y el total coinciden EXACTO con la pantalla Métricas de Riesgo.\n D.RATINGS.forEach(r => {\n const inR = base.filter(x => x.p.rating === r);\n const divs = inR.filter(x => x.p.div), rest = inR.filter(x => !x.p.div);\n if (!divs.length || !rest.length) return;\n let excess = 0;\n divs.forEach(x => { const nc = -0.10 * x.stand; excess += x.comp - nc; x.comp = nc; });\n const restSum = rest.reduce((a, x) => a + x.comp, 0);\n rest.forEach(x => { x.comp += excess * x.comp / restSum; });\n });\n base.forEach(x => {\n x.marg = x.comp * x.p.mgF;\n x.margPct = x.v > 0 ? x.marg / x.v * 100 : 0;\n });\n return base;\n }\n const fSg = v => (v < 0 ? \"−\" : \"\") + fMM(Math.abs(v));\n\n function mgHtml() {\n if (S.uiState === \"loading\") return `

${kpiSkeletons()}

${panelSkeletons()}

`;\n if (S.uiState === \"empty\") return `

${kpisNDMR(MG_TITLES())}

${statePanels(emptyBox())}

`;\n if (S.uiState === \"error\") return `

${kpisNDMR(MG_TITLES())}

${statePanels(errBox())}

`;\n\n const rows = mgRows();\n const total = rows.reduce((a, x) => a + x.comp, 0); // Σ componental = total de Métricas (Euler)\n const margSum = rows.reduce((a, x) => a + x.marg, 0);\n const mean = margSum / rows.length;\n const meanPrev = mgRows(true).reduce((a, x) => a + x.marg, 0) / rows.length;\n const dMean = mean - meanPrev, dMeanP = meanPrev !== 0 ? dMean / Math.abs(meanPrev) * 100 : null;\n const top = [...rows].sort((a, b) => b.comp - a.comp)[0];\n const lims = D.MG_LIMITS[S.medida];\n const nSobre = lims.hyp != null ? rows.filter(x => x.marg > lims.hyp).length : null;\n const pos = rows.filter(x => x.comp > 0);\n const posSum = pos.reduce((a, x) => a + x.comp, 0);\n const hhi = pos.reduce((a, x) => a + (x.comp / posSum) ** 2, 0);\n const negs = rows.filter(x => x.comp < 0);\n const negNet = negs.reduce((a, x) => a + x.comp, 0);\n\n const kpis =\n kpiCard(`${S.medida} Marginal promedio ⓘ`,\n fSg(mean), subtituloConsolidacion(), [\n [\"anterior\", fSg(meanPrev)],\n [\"Δ\", (dMean >= 0 ? \"+\" : \"−\") + fMM(Math.abs(dMean)).slice(1)],\n [\"Δ%\", dMeanP === null ? \"N/D\" : (dMeanP >= 0 ? \"+\" : \"\") + nf1.format(dMeanP) + \"%\"]]) +\n kpiCard(`Mayor contribución ⓘ`,\n fMM(top.comp),\n `${esc(top.p.inst)} · ${esc(top.p.emisor)}
${fPct(top.comp / total * 100, 1)} del ${esc(S.medida)} (base componental — aditiva)`, []) +\n kpiCard(`Posiciones sobre umbral ⓘ`,\n nSobre === null ? \"N/D\" : String(nSobre),\n nSobre === null ? \"Límite de riesgo absoluto: N/D\" : `Marginal > ${fMM(lims.hyp)} (hipérbola iso-risk)`, []) +\n kpiCard(`HHI de contribuciones ⓘ`,\n fH(hhi), `≈ ${nf0(1 / hhi)} posiciones efectivas (1/HHI) · sobre contribuciones positivas`, []) +\n usoLimiteCard(total);\n\n const glos = `

ⓘ Definiciones — Marginal: riesgo(cartera) − riesgo(cartera sin la posición), leave-one-out; no aditiva (en este corte Σ marginales = ${fMM(margSum)} ≠ ${esc(S.medida)} total ${fMM(total)}). Contribución (componental): descomposición de Euler — Σ componentales = ${esc(S.medida)} total exacto. Standalone: riesgo de la posición en aislamiento; standalone − componental = beneficio de diversificación.

`;\n\n return `${glos}

${kpis}

Iso-risk: ${S.medida} marginal vs. tamaño

Cada punto = instrumento; X·Y = marginal en DOP. Overlays de límite conmutan con la medida; sin límite configurado → “Límite: N/D”. Diversificadoras bajo Y=0. ${NOTA_GRANULARIDAD}

${S.uiState === \"partial\" ? errBox() : `\n

Contribución (componental)

${S.mgDona === \"Emisor\" ? \"Top-7 + “Otros”. \" : \"\"}Solo contribuciones positivas — una dona no representa negativos. Diversificadoras: ${negs.length} posiciones, neto −${fMM(Math.abs(negNet)).slice(1)} (fuera de la dona).

Ranking por ${S.medida} marginal

Top-7 posiciones por |marginal| mostrando signo: añade (+) / diversifica (−). “Otros (+)” y “Otros (−)” separados — un neto ocultaría magnitudes de ambos signos.

Detalle por posición

${tablaMg(rows, total)}

Lista completa (sin colapso top-7). Marginal solo a nivel instrumento — no es aditiva. Los % pueden superar 100% por contribuciones negativas. Var refiere al Marginal; variaciones al TC de cada corte (incluyen efecto FX). Solo el VM se consolida; el ${S.medida} jamás se parte por moneda. ${NOTA_GRANULARIDAD}

${notaMonedaMR}

`;\n }\n\n function tablaMg(rows, total) {\n const prevRows = mgRows(true);\n let html = `\n \n \n \n \n `;\n D.RATINGS.forEach(r => {\n const inR = rows.filter(x => x.p.rating === r); if (!inR.length) return;\n const vmR = inR.reduce((a, x) => a + x.v, 0), compR = inR.reduce((a, x) => a + x.comp, 0);\n const standR = inR.reduce((a, x) => a + x.stand, 0);\n const open = !!S.mgExp[r];\n html += `\n \n \n `;\n if (!open) return;\n const byE = new Map();\n inR.forEach(x => byE.set(x.p.emisor, [...(byE.get(x.p.emisor) || []), x]));\n [...byE.entries()].sort((a, b) => b[1].reduce((s, x) => s + x.v, 0) - a[1].reduce((s, x) => s + x.v, 0)).forEach(([e, l]) => {\n const key = r + \"|\" + e, openE = !!S.mgExpE[key];\n const vmE = l.reduce((a, x) => a + x.v, 0), compE = l.reduce((a, x) => a + x.comp, 0), standE = l.reduce((a, x) => a + x.stand, 0);\n const chip = new Set(l.map(x => x.p.moneda)).size > 1 ? \"Mixta\" : l[0].p.moneda;\n html += `\n \n \n `;\n if (!openE) return;\n l.sort((a, b) => b.v - a.v).forEach(x => {\n const prev = prevRows.find(y => y.p.inst === x.p.inst && y.p.emisor === x.p.emisor);\n const dv = prev ? x.marg - prev.marg : null;\n const dvp = prev && prev.marg !== 0 ? dv / Math.abs(prev.marg) * 100 : null;\n html += `\n \n \n \n \n `;\n });\n });\n });\n return html + `

Calificación / Emisor / Instrumento	Moneda	VM (DOP)	${S.medida} Marginal	Componental	% del total	Standalone	Benef. diversif.	Var Marginal	Var %
${open ? \"▾\" : \"▸\"}${r}	—	${fMM(vmR)}	—	${fSg(compR)}	${fPct(compR / total * 100)}	${fMM(standR)}	${fSg(standR - compR)}	—	—
${openE ? \"▾\" : \"▸\"}${esc(e)}	${chip}	${fMM(vmE)}	—	${fSg(compE)}	${fPct(compE / total * 100)}	${fMM(standE)}	${fSg(standE - compE)}	—	—
${esc(x.p.inst)}	${x.p.moneda}	${fMM(x.v)}	${fSg(x.marg)}	${fSg(x.comp)}	${fPct(x.comp / total * 100)}	${fMM(x.stand)}	${fSg(x.stand - x.comp)}	${dv === null ? \"N/D\" : (dv >= 0 ? \"+\" : \"−\") + fMM(Math.abs(dv)).slice(1)}	${dvp === null ? \"N/D\" : (dvp >= 0 ? \"+\" : \"\") + nf1.format(dvp) + \"%\"}

`;\n }\n\n function chartsMarginal() {\n const rows = mgRows();\n const lims = D.MG_LIMITS[S.medida];\n // TL — scatter iso-risk. Series por rating (paleta ordinal, jamás semáforo) + 3 overlays\n // con entrada de leyenda SIEMPRE presente (layout estable ante el selector — N/D si null).\n const maxX = Math.max(...rows.map(x => x.v)) * 1.12;\n const scatterSeries = D.RATINGS.filter(r => rows.some(x => x.p.rating === r)).map(r => ({\n name: r, type: \"scatter\", symbolSize: 13, itemStyle: { color: ratColor(r), opacity: 0.7 },\n data: rows.filter(x => x.p.rating === r).map(x => ({ value: [+x.v.toFixed(2), +x.margPct.toFixed(3)], meta: x })),\n }));\n const maxY = Math.max(...rows.map(x => x.margPct)) * 1.45;\n const minY = Math.min(0, ...rows.map(x => x.margPct)) * 2.2 - 0.4;\n const hypPts = lims.hyp != null\n ? Array.from({ length: 240 }, (_, i) => { const x = maxX * (i + 1) / 240; const y = 100 * lims.hyp / x; return y <= maxY ? [x, y] : null; }).filter(Boolean)\n : [];\n const nmH = `Límite %-riesgo: ${lims.h != null ? fPct(lims.h, 1) : \"N/D\"}`;\n const nmV = `Límite de tamaño: ${lims.v != null ? fMM(lims.v) : \"N/D\"}`;\n const nmY = `Iso-risk (por posición): ${lims.hyp != null ? fMM(lims.hyp) : \"N/D\"}`;\n mkChart(\"chMG_TL\", {\n grid: { left: 52, right: 14, top: 34, bottom: 74 },\n legend: { bottom: 0, itemWidth: 10, itemHeight: 10, textStyle: { fontSize: 9 } },\n tooltip: { trigger: \"item\", formatter: p => {\n const m = p.data && p.data.meta; if (!m) return p.seriesName;\n return `${esc(m.p.inst)} · ${esc(m.p.emisor)}
Moneda: ${m.p.moneda} · Rating actual: ${m.p.rating}
VM: ${fMM(m.v)}
Marginal: ${fPct(m.margPct)} · ${fSg(m.marg)}
${esc(NOTA_GRANULARIDAD)}`;\n } },\n xAxis: { name: \"VM (DOP MM)\", nameLocation: \"middle\", nameGap: 22, nameTextStyle: { fontSize: 9 }, type: \"value\", max: +maxX.toFixed(0), axisLabel: { fontSize: 9, formatter: v => \"$\" + nf0(v) } },\n yAxis: { name: `${S.medida} marginal / VM (%)`, nameTextStyle: { fontSize: 9, align: \"left\" }, nameGap: 10, type: \"value\", max: +maxY.toFixed(1), min: +minY.toFixed(1), axisLabel: { fontSize: 9, formatter: v => nf1.format(v) + \"%\" } },\n dataZoom: [{ type: \"inside\", xAxisIndex: 0 }, { type: \"inside\", yAxisIndex: 0 }],\n graphic: [\n { type: \"text\", right: 28, top: 40, style: { text: \"C · mayor riesgo absoluto\\n«fallen angels viven aquí»\", fontSize: 9, fill: TK(\"--text-2\"), fontWeight: \"bold\" } },\n { type: \"text\", left: 62, top: 40, style: { text: \"B · mayor % de riesgo\", fontSize: 9, fill: TK(\"--text-2\") } },\n { type: \"text\", right: 28, bottom: 108, style: { text: \"A · mayor tamaño absoluto\", fontSize: 9, fill: TK(\"--text-2\") } },\n ],\n series: [\n ...scatterSeries,\n { name: nmH, type: \"line\", symbol: \"none\", lineStyle: { type: \"dashed\", width: 1.4, color: TK(\"--secondary\") }, color: TK(\"--secondary\"),\n data: lims.h != null ? [[0, lims.h], [maxX, lims.h]] : [],\n markLine: { silent: true, symbol: \"none\", lineStyle: { color: TK(\"--text-2\"), width: 1 }, label: { show: false }, data: [{ yAxis: 0 }] } },\n { name: nmV, type: \"line\", symbol: \"none\", lineStyle: { type: \"dashed\", width: 1.4, color: TK(\"--primary\") }, color: TK(\"--primary\"),\n data: lims.v != null ? [[lims.v, minY], [lims.v, maxY]] : [] },\n { name: nmY, type: \"line\", symbol: \"none\", lineStyle: { width: 2, type: \"dashed\", color: TK(\"--sem-warn\") }, color: TK(\"--sem-warn\"),\n data: hypPts, tooltip: { show: false } },\n ],\n });\n // TR — dona componental (solo positivas)\n if (S.uiState !== \"partial\") {\n const pos = rows.filter(x => x.comp > 0);\n let entries;\n if (S.mgDona === \"Emisor\") {\n const m = new Map(); pos.forEach(x => m.set(x.p.emisor, (m.get(x.p.emisor) || 0) + x.comp));\n entries = [...m.entries()].sort((a, b) => b[1] - a[1]);\n if (entries.length > 8) { const t7 = entries.slice(0, 7), rest = entries.slice(7).reduce((a, e) => a + e[1], 0); entries = [...t7, [\"Otros\", rest]]; }\n } else if (S.mgDona === \"Calificación\") {\n const m = new Map(); pos.forEach(x => m.set(x.p.rating, (m.get(x.p.rating) || 0) + x.comp));\n entries = D.RATINGS.filter(r => m.has(r)).map(r => [r, m.get(r)]);\n } else {\n const m = new Map(); pos.forEach(x => m.set(x.p.tipo, (m.get(x.p.tipo) || 0) + x.comp));\n entries = [...m.entries()].sort((a, b) => b[1] - a[1]);\n }\n const colors = S.mgDona === \"Calificación\" ? entries.map(e => ratColor(e[0]))\n : entries.map((e, i) => e[0] === \"Otros\" ? GRAY : CATEG[i % CATEG.length]);\n mkChart(\"chMG_TR\", {\n tooltip: { trigger: \"item\", valueFormatter: v => fMM(v) },\n legend: { orient: \"vertical\", right: 0, top: \"middle\", textStyle: { fontSize: 10 }, formatter: n => { const e = entries.find(x => x[0] === n); return `${n} ${fMM(e[1])}`; } },\n series: [{ type: \"pie\", radius: [\"52%\", \"74%\"], center: [\"32%\", \"50%\"],\n label: { formatter: p => fPct(p.percent, 1), fontSize: 10 },\n data: entries.map((e, i) => ({ name: e[0], value: +e[1].toFixed(2), itemStyle: { color: colors[i] } })) }],\n });\n }\n // BL — divergentes top-7 |marginal| + Otros(+)/Otros(−) separados (neutro, signo por posición)\n const sorted = [...rows].sort((a, b) => Math.abs(b.marg) - Math.abs(a.marg));\n const t7 = sorted.slice(0, 7), rest = sorted.slice(7);\n const oPos = rest.filter(x => x.marg >= 0).reduce((a, x) => a + x.marg, 0);\n const oNeg = rest.filter(x => x.marg < 0).reduce((a, x) => a + x.marg, 0);\n const items = [\n ...t7.map(x => ({ k: x.p.inst, v: x.marg })),\n { k: \"Otros (+)\", v: oPos }, { k: \"Otros (−)\", v: oNeg },\n ];\n mkChart(\"chMG_BL\", {\n grid: { left: 56, right: 16, top: 24, bottom: 66 },\n tooltip: { trigger: \"axis\", valueFormatter: v => (v >= 0 ? \"+\" : \"−\") + fMM(Math.abs(v)).slice(1) },\n xAxis: { type: \"category\", data: items.map(i => i.k), axisLabel: { fontSize: 8.5, rotate: 36 } },\n yAxis: { type: \"value\", axisLabel: { formatter: v => (v < 0 ? \"−\" : \"\") + \"$\" + nf0(Math.abs(v)) + \"MM\", fontSize: 10 } },\n series: [{ type: \"bar\", barWidth: 20,\n itemStyle: { color: p => items[p.dataIndex].k.startsWith(\"Otros\") ? GRAY : TK(\"--primary\") },\n label: { show: true, position: \"top\", fontSize: 9, color: TK(\"--text-2\"),\n formatter: p => items[p.dataIndex].v === 0 ? \"sin posiciones\" : (items[p.dataIndex].v >= 0 ? \"+\" : \"−\") + nf1.format(Math.abs(items[p.dataIndex].v)) },\n data: items.map(i => +i.v.toFixed(2)) }],\n });\n }\n\n // ---------- Charts ----------\n function mkChart(id, opt) {\n const el = document.getElementById(id);\n if (!el) return;\n const c = echarts.init(el, null, { renderer: \"canvas\" });\n c.setOption(opt); charts.push(c);\n }\n const tipMM = p => (Array.isArray(p) ? p : [p]).map(x => `${x.marker} ${x.seriesName || x.name}: ${fMM(x.value)}`).join(\"
\");\n\n function chartsGlobal() {\n // TL — área apilada VM por rating (paleta ordinal azul, jamás semáforo)\n const shares = D.HIST_SHARE, totals = [...D.HIST_TOTAL];\n const byR = aggBy(\"rating\"); const t = total();\n totals[totals.length - 1] = t;\n const series = D.RATINGS.map(r => ({\n name: r, type: \"line\", stack: \"vm\", areaStyle: { opacity: 0.85 }, symbol: \"none\",\n lineStyle: { width: 1 }, color: ratColor(r),\n data: D.DATES.map((_, i) => i === D.DATES.length - 1\n ? +(byR.cur.get(r) || 0).toFixed(2)\n : +((shares[r][i] || 0) * totals[i]).toFixed(2)),\n }));\n mkChart(\"chTL\", {\n grid: { left: 60, right: 16, top: 24, bottom: 44 },\n tooltip: { trigger: \"axis\", valueFormatter: v => fMM(v) },\n legend: { bottom: 0, itemWidth: 10, itemHeight: 10, textStyle: { fontSize: 10 } },\n xAxis: { type: \"category\", data: D.DATES, axisLabel: { fontSize: 9, rotate: 40 } },\n yAxis: { type: \"value\", axisLabel: { formatter: v => \"$\" + nf0(v) + \"MM\", fontSize: 10 } },\n series,\n });\n // TR — dona con \"Vista por\"\n if (S.uiState !== \"partial\") {\n const dim = { \"Calificación\": \"rating\", \"Emisor\": \"emisor\", \"Tipo de instrumento\": \"tipo\", \"Moneda\": \"moneda\" }[S.donaVista];\n let entries = [...aggBy(dim).cur.entries()].sort((a, b) => b[1] - a[1]);\n if (entries.length > 8) { // máx 8 categorías: top-7 + Otros (L-10)\n const top = entries.slice(0, 7), rest = entries.slice(7).reduce((a, e) => a + e[1], 0);\n entries = [...top, [\"Otros\", rest]];\n }\n const colors = dim === \"rating\" ? entries.map(e => e[0] === \"Otros\" ? GRAY : ratColor(e[0]))\n : entries.map((e, i) => e[0] === \"Otros\" ? GRAY : CATEG[i % CATEG.length]);\n mkChart(\"chTR\", {\n tooltip: { trigger: \"item\", valueFormatter: v => fMM(v) },\n legend: { orient: \"vertical\", right: 0, top: \"middle\", textStyle: { fontSize: 10 }, formatter: n => { const e = entries.find(x => x[0] === n); return `${n} ${fMM(e[1])}`; } },\n series: [{ type: \"pie\", radius: [\"52%\", \"74%\"], center: [\"32%\", \"50%\"],\n label: { formatter: p => fPct(p.percent, 1), fontSize: 10 },\n data: entries.map((e, i) => ({ name: e[0], value: +e[1].toFixed(2), itemStyle: { color: colors[i] } })) }],\n });\n }\n // BL — divergentes Δ (NEUTRO — signo por posición+etiqueta, X-3)\n const dimB = { \"Calificación\": \"rating\", \"Emisor\": \"emisor\", \"Tipo de instrumento\": \"tipo\" }[S.blVista];\n const ag = aggBy(dimB);\n let items = [...ag.cur.keys()].map(k => {\n const c = ag.cur.get(k) || 0, p = ag.prev.get(k) || 0;\n return { k, d: c - p, dp: p > 0 ? (c - p) / p * 100 : null };\n });\n if (dimB === \"emisor\" && items.length > 7) {\n items.sort((a, b) => Math.abs(b.d) - Math.abs(a.d));\n const top = items.slice(0, 7), rest = items.slice(7);\n items = [...top, { k: \"Otros\", d: rest.reduce((a, x) => a + x.d, 0), dp: null }];\n } else if (dimB === \"rating\") {\n items.sort((a, b) => D.RATINGS.indexOf(a.k) - D.RATINGS.indexOf(b.k));\n }\n items.push({ k: \"Total\", d: total() - totalPrev(), dp: totalPrev() > 0 ? (total() - totalPrev()) / totalPrev() * 100 : null });\n mkChart(\"chBL\", {\n grid: { left: 60, right: 16, top: 28, bottom: 54 },\n tooltip: { trigger: \"axis\", valueFormatter: v => (v >= 0 ? \"+\" : \"−\") + fMM(Math.abs(v)).slice(1) },\n xAxis: { type: \"category\", data: items.map(i => i.k), axisLabel: { fontSize: 9, rotate: 32 } },\n yAxis: { type: \"value\", axisLabel: { formatter: v => \"$\" + nf0(v) + \"MM\", fontSize: 10 } },\n series: [{ type: \"bar\", barWidth: 22,\n itemStyle: { color: p => p.dataIndex === items.length - 1 ? TK(\"--secondary\") : TK(\"--primary\") }, // neutro siempre\n label: { show: true, position: \"top\", fontSize: 9, color: TK(\"--text-2\"),\n formatter: p => items[p.dataIndex].dp === null ? \"\" : (items[p.dataIndex].dp >= 0 ? \"+\" : \"\") + nf1.format(items[p.dataIndex].dp) + \"%\" },\n data: items.map(i => +i.d.toFixed(2)) }],\n });\n }\n\n function chartsConc() {\n const rows = emisorStats(); const t = total();\n // TL — top-7 + Otros barras horizontales\n let top = rows.slice(0, 7);\n const rest = rows.slice(7);\n const data = [...top.map(r => ({ name: r.emisor, v: S.concTL === \"pct\" ? r.pct : r.vm }))];\n if (rest.length) data.push({ name: \"Otros\", v: rest.reduce((a, r) => a + (S.concTL === \"pct\" ? r.pct : r.vm), 0) });\n data.reverse();\n mkChart(\"chCTL\", {\n grid: { left: 130, right: 50, top: 8, bottom: 24 },\n tooltip: { trigger: \"axis\", valueFormatter: v => S.concTL === \"pct\" ? fPct(v) : fMM(v) },\n xAxis: { type: \"value\", axisLabel: { formatter: v => S.concTL === \"pct\" ? v + \"%\" : \"$\" + nf0(v) + \"MM\", fontSize: 10 } },\n yAxis: { type: \"category\", data: data.map(d => d.name), axisLabel: { fontSize: 10 } },\n series: [{ type: \"bar\", barWidth: 14,\n itemStyle: { color: p => data[p.dataIndex].name === \"Otros\" ? GRAY : TK(\"--primary\") },\n label: { show: true, position: \"right\", fontSize: 9.5, formatter: p => S.concTL === \"pct\" ? fPct(p.value, 1) : fMM(p.value) },\n data: data.map(d => +d.v.toFixed(2)) }],\n });\n // TR — evolución HHI / mayor% con markLine límite\n if (S.uiState !== \"partial\") {\n const hhiNow = hhiOf(rows);\n const mayorNow = rows[0] ? rows[0].pct : 0;\n const serie = D.DATES.map((_, i) => {\n if (i === D.DATES.length - 1) return S.concTR === \"hhi\" ? +hhiNow.toFixed(4) : +mayorNow.toFixed(2);\n const drift = 1 + Math.sin(i * 1.7) * 0.03 - (D.DATES.length - 1 - i) * 0.004;\n return S.concTR === \"hhi\" ? +(hhiNow * drift).toFixed(4) : +(mayorNow * drift).toFixed(2);\n });\n const lim = S.concTR === \"hhi\" ? D.LIMITES.hhiInterno : D.LIMITES.emisorPctInterno;\n const yMax = Math.max(lim * 1.08, Math.max(...serie) * 1.05);\n mkChart(\"chCTR\", {\n grid: { left: 56, right: 16, top: 24, bottom: 40 },\n tooltip: { trigger: \"axis\", valueFormatter: v => S.concTR === \"hhi\" ? v.toFixed(4) : fPct(v, 1) },\n xAxis: { type: \"category\", data: D.DATES, axisLabel: { fontSize: 9, rotate: 40 } },\n yAxis: { type: \"value\", scale: true, max: +yMax.toFixed(4), axisLabel: { formatter: v => S.concTR === \"hhi\" ? v.toFixed(3) : v + \"%\", fontSize: 10 } },\n series: [{ type: \"line\", symbol: \"circle\", symbolSize: 4, color: TK(\"--primary\"), data: serie,\n markLine: { silent: true, symbol: \"none\",\n lineStyle: { type: \"dashed\", color: TK(\"--sem-warn\") },\n label: { formatter: \"Límite interno\", fontSize: 9, color: TK(\"--sem-warn\") },\n data: [{ yAxis: lim }] } }],\n });\n }\n // BL — divergentes Δ por emisor (top-7 |Δ| + Otros + Total) — NEUTRO\n const tp = totalPrev();\n let items = rows.map(r => ({ k: r.emisor, d: r.vm - r.prev, dp: r.prev > 0 ? (r.vm - r.prev) / r.prev * 100 : null }));\n items.sort((a, b) => Math.abs(b.d) - Math.abs(a.d));\n const topB = items.slice(0, 7), restB = items.slice(7);\n items = [...topB];\n if (restB.length) items.push({ k: \"Otros\", d: restB.reduce((a, x) => a + x.d, 0), dp: null });\n items.push({ k: \"Total\", d: t - tp, dp: tp > 0 ? (t - tp) / tp * 100 : null });\n mkChart(\"chCBL\", {\n grid: { left: 60, right: 16, top: 28, bottom: 62 },\n tooltip: { trigger: \"axis\", valueFormatter: v => (v >= 0 ? \"+\" : \"−\") + fMM(Math.abs(v)).slice(1) },\n xAxis: { type: \"category\", data: items.map(i => i.k), axisLabel: { fontSize: 9, rotate: 38 } },\n yAxis: { type: \"value\", axisLabel: { formatter: v => \"$\" + nf0(v) + \"MM\", fontSize: 10 } },\n series: [{ type: \"bar\", barWidth: 20,\n itemStyle: { color: p => items[p.dataIndex].k === \"Total\" ? TK(\"--secondary\") : items[p.dataIndex].k === \"Otros\" ? GRAY : TK(\"--primary\") },\n label: { show: true, position: \"top\", fontSize: 9, color: TK(\"--text-2\"),\n formatter: p => items[p.dataIndex].dp === null ? \"\" : (items[p.dataIndex].dp >= 0 ? \"+\" : \"\") + nf1.format(items[p.dataIndex].dp) + \"%\" },\n data: items.map(i => +i.d.toFixed(2)) }],\n });\n }\n\n function chartsMRFecha() {\n const a = mrAgg();\n // TL — barras por rating (orden de escala; cero real = 0; sin dato = ausente + N/D)\n const cats = D.RATINGS.filter(r => D.positions.some(p => p.rating === r));\n mkChart(\"chMF_TL\", {\n grid: { left: 60, right: 16, top: 24, bottom: 30 },\n tooltip: { trigger: \"axis\", valueFormatter: v => fMM(v) },\n xAxis: { type: \"category\", data: cats, axisLabel: { fontSize: 10 } },\n yAxis: { type: \"value\", axisLabel: { formatter: v => \"$\" + nf0(v) + \"MM\", fontSize: 10 } },\n series: [{ type: \"bar\", barWidth: 26,\n itemStyle: { color: p => ratColor(cats[p.dataIndex]) },\n label: { show: true, position: \"top\", fontSize: 9, color: TK(\"--text-2\"), formatter: p => fMM(p.value) },\n data: cats.map(r => { const row = a.rows.find(x => x.r === r); return row ? +row.contrib.toFixed(2) : 0; }) }],\n });\n // TR — dona de contribución (Emisor top-7+Otros / Tipo) — prorrateo §2\n if (S.uiState !== \"partial\") {\n let entries = S.mrDona === \"Emisor\" ? mrEmisores() : mrTipos();\n if (entries.length > 8) {\n const top = entries.slice(0, 7), rest = entries.slice(7).reduce((x, e) => x + e[1], 0);\n entries = [...top, [\"Otros\", rest]];\n }\n mkChart(\"chMF_TR\", {\n tooltip: { trigger: \"item\", valueFormatter: v => fMM(v) },\n legend: { orient: \"vertical\", right: 0, top: \"middle\", textStyle: { fontSize: 10 },\n formatter: n => { const e = entries.find(x => x[0] === n); return `${n} ${fMM(e[1])}`; } },\n series: [{ type: \"pie\", radius: [\"52%\", \"74%\"], center: [\"32%\", \"50%\"],\n label: { formatter: p => fPct(p.percent, 1), fontSize: 10 },\n data: entries.map((e, i) => ({ name: e[0], value: +e[1].toFixed(2), itemStyle: { color: e[0] === \"Otros\" ? GRAY : CATEG[i % CATEG.length] } })) }],\n });\n }\n // BL — standalone vs contribución por rating (agrupadas; la brecha = diversificación)\n const cats2 = a.rows.map(x => x.r);\n mkChart(\"chMF_BL\", {\n grid: { left: 60, right: 16, top: 28, bottom: 46 },\n tooltip: { trigger: \"axis\", valueFormatter: v => fMM(v) },\n legend: { bottom: 0, itemWidth: 10, itemHeight: 10, textStyle: { fontSize: 10 } },\n xAxis: { type: \"category\", data: cats2, axisLabel: { fontSize: 10 } },\n yAxis: { type: \"value\", axisLabel: { formatter: v => \"$\" + nf0(v) + \"MM\", fontSize: 10 } },\n series: [\n { name: S.medida + \" standalone\", type: \"bar\", barWidth: 14, color: TK(\"--secondary\"), data: a.rows.map(x => +x.stand.toFixed(2)) },\n { name: \"Contribución a cartera\", type: \"bar\", barWidth: 14, color: TK(\"--primary\"), data: a.rows.map(x => +x.contrib.toFixed(2)) },\n ],\n });\n }\n\n function chartsMRHist() {\n const series = mrHistSeries();\n const mk = mrMarkerIdx();\n const markLine = { silent: true, symbol: \"none\",\n lineStyle: { type: \"dashed\", color: TK(\"--text-2\"), width: 1.4 },\n label: { formatter: D.SUPUESTO_MARKERS[0].label, fontSize: 9, color: TK(\"--text-2\"), position: \"insideEndTop\" },\n data: [{ xAxis: D.DATES[mk] }] };\n // TL — área apilada por rating + marcador de cambio de supuesto\n mkChart(\"chMH_TL\", {\n grid: { left: 60, right: 16, top: 24, bottom: 44 },\n tooltip: { trigger: \"axis\", valueFormatter: v => fMM(v) },\n legend: { bottom: 0, itemWidth: 10, itemHeight: 10, textStyle: { fontSize: 10 } },\n xAxis: { type: \"category\", data: D.DATES, axisLabel: { fontSize: 9, rotate: 40 } },\n yAxis: { type: \"value\", axisLabel: { formatter: v => \"$\" + nf0(v) + \"MM\", fontSize: 10 } },\n series: series.map((s, i) => ({\n name: s.r, type: \"line\", stack: \"mr\", areaStyle: { opacity: 0.85 }, symbol: \"none\",\n lineStyle: { width: 1 }, color: ratColor(s.r), data: s.data,\n ...(i === 0 ? { markLine } : {}),\n })),\n });\n // TR — razón /VM (%) + mismo marcador\n if (S.uiState !== \"partial\") {\n const totals = mrHistTotals();\n const vmSerie = [...D.HIST_TOTAL]; vmSerie[vmSerie.length - 1] = mrAgg().vmTot;\n const razon = D.DATES.map((_, i) => +(totals[i] / vmSerie[i] * 100).toFixed(3));\n mkChart(\"chMH_TR\", {\n grid: { left: 52, right: 16, top: 24, bottom: 40 },\n tooltip: { trigger: \"axis\", valueFormatter: v => fPct(v) },\n xAxis: { type: \"category\", data: D.DATES, axisLabel: { fontSize: 9, rotate: 40 } },\n yAxis: { type: \"value\", scale: true, axisLabel: { formatter: v => v + \"%\", fontSize: 10 } },\n series: [{ type: \"line\", symbol: \"circle\", symbolSize: 4, color: TK(\"--primary\"), data: razon, markLine }],\n });\n }\n // BL — divergentes Δ (Calificación / Emisor top-7 |Δ| + Otros) — NEUTRO\n const a = mrAgg(), ap = mrAgg(true);\n let items;\n if (S.mrBL === \"Calificación\") {\n items = a.rows.map(x => {\n const prev = ap.rows.find(y => y.r === x.r);\n const d = x.contrib - (prev ? prev.contrib : 0);\n return { k: x.r, d, dp: prev ? d / prev.contrib * 100 : null };\n });\n } else {\n const cur = new Map(mrEmisores()), prev = new Map(mrEmisores(true));\n items = [...cur.keys()].map(k => {\n const d = cur.get(k) - (prev.get(k) || 0);\n return { k, d, dp: prev.get(k) ? d / prev.get(k) * 100 : null };\n }).sort((x, y) => Math.abs(y.d) - Math.abs(x.d));\n const top = items.slice(0, 7), rest = items.slice(7);\n items = [...top];\n if (rest.length) items.push({ k: \"Otros\", d: rest.reduce((x, y) => x + y.d, 0), dp: null });\n }\n items.push({ k: \"Total\", d: a.total - ap.total, dp: ap.total > 0 ? (a.total - ap.total) / ap.total * 100 : null });\n mkChart(\"chMH_BL\", {\n grid: { left: 60, right: 16, top: 28, bottom: 56 },\n tooltip: { trigger: \"axis\", valueFormatter: v => (v >= 0 ? \"+\" : \"−\") + fMM(Math.abs(v)).slice(1) },\n xAxis: { type: \"category\", data: items.map(i => i.k), axisLabel: { fontSize: 9, rotate: 32 } },\n yAxis: { type: \"value\", axisLabel: { formatter: v => (v < 0 ? \"−\" : \"\") + \"$\" + (Math.abs(v) < 10 ? nf1.format(Math.abs(v)) : nf0(Math.abs(v))) + \"MM\", fontSize: 10 } },\n series: [{ type: \"bar\", barWidth: 22,\n itemStyle: { color: p => items[p.dataIndex].k === \"Total\" ? TK(\"--secondary\") : items[p.dataIndex].k === \"Otros\" ? GRAY : TK(\"--primary\") },\n label: { show: true, position: \"top\", fontSize: 9, color: TK(\"--text-2\"),\n formatter: p => items[p.dataIndex].dp === null ? \"\" : (items[p.dataIndex].dp >= 0 ? \"+\" : \"\") + nf1.format(items[p.dataIndex].dp) + \"%\" },\n data: items.map(i => +i.d.toFixed(2)) }],\n });\n }\n\n const nf0v = new Intl.NumberFormat(\"en-US\", { maximumFractionDigits: 0 });\n function nf0(v) { return nf0v.format(v); }\n\n // ---------- Backtesting › Resumen de Excepciones (§14) ----------\n const BT_TITLES = [\"Excepciones — VaR 99% · 1 año\", \"Kupiec POF\", \"Christoffersen\", \"Precisión MC de la cola\", \"Uso Límite\"];\n const BT_CONV = \"VaR 99%·1a escalado al horizonte entre cortes (raíz de tiempo, cortes EOD diarios) — convención del mock: la metodología oficial del tenant gobierna la comparación\";\n const BT_ROT_BASILEA = \"Veredicto estadístico de validación del modelo — no es cumplimiento de límites\";\n const ND_WIN = n => `N/D — ventana incompleta (${n}/250)`;\n function btWin() {\n const cs = D.BT.cortes;\n const val = cs.filter(c => c.valida);\n const excAll = cs.filter(c => c.pnl < -c.varEsc);\n return { cs, val, n: val.length, excAll, excVal: excAll.filter(c => c.valida) };\n }\n function btUsoLimite() {\n // VaR base FORZADO (§14): mismo total que Métricas de Riesgo bajo medida VaR — no sigue el selector global\n const lim = D.LIM_MEDIDA.VaR, total = D.BT.VAR1A;\n const uso = total / lim * 100;\n const st = uso > 100 ? [\"err\", \"Incumplimiento\"] : uso >= 90 ? [\"warn\", \"Advertencia\"] : [\"ok\", \"Ok\"];\n return kpiCard(\"Uso Límite\", `${fPct(uso, 1)} ${st[1]}`,\n `VaR base vs. límite interno ${fMM(lim)} · cartera consolidada completa · medida VaR fija — no sigue al selector de otras secciones`, []);\n }\n function btHtml() {\n if (S.uiState === \"loading\") return `

${kpiSkeletons()}

${panelSkeletons()}

`;\n if (S.uiState === \"empty\") return `

${kpisNDMR(BT_TITLES)}

${statePanels(emptyBox())}

`;\n if (S.uiState === \"error\") return `

${kpisNDMR(BT_TITLES)}

${statePanels(errBox())}

`;\n const w = btWin();\n const esp = (w.n * 0.01).toFixed(2);\n const excPrev = w.excVal.filter(c => c.f !== D.AS_OF).length; // ventana del corte anterior (mismo supuesto)\n const kpis =\n kpiCard(`Excepciones — VaR 99% · 1 año ⓘ`,\n `${w.excVal.length} en ${w.n} cortes`,\n `ventana válida, objetivo 250 · esperadas ~${esp} al 99% en ${w.n} · Consolidado en DOP · TC del corte`,\n [[\"anterior\", `${excPrev} (${w.n - 1}/250)`]]) +\n kpiCard(`Kupiec POF ⓘ`,\n \"N/D\", ND_WIN(w.n), [[\"anterior\", `N/D (${w.n - 1}/250)`]]) +\n kpiCard(`Christoffersen ⓘ`,\n \"N/D\", ND_WIN(w.n), [[\"anterior\", `N/D (${w.n - 1}/250)`]]) +\n kpiCard(`Precisión MC de la cola ⓘ`,\n `±${nf1.format(D.BT.mcPrecision)}%`,\n `del VaR @99% (cuantil oficial) · colas más profundas requieren ~1/q escenarios`, []) +\n btUsoLimite();\n return `

${kpis}

Serie de excepciones ⓘ

${BT_CONV}.

Series en neutro; la excepción se marca por forma (rombo) en un único color de alerta rotulado — nunca la terna semafórica. Cada punto consolidado al TC de su fecha.

${S.uiState === \"partial\" ? errBox() : btTRHtml(w)}

Convergencia del estimador MC ⓘ

\n ${[\"1%\", \"0.5%\", \"0.1%\"].map(q =>\n ``).join(\"\")}

Colas profundas: la banda de confianza escala ~1/q en escenarios.
Bandas del estimador Monte Carlo — no es la distribución de valor del portafolio.

Cuantil de diagnóstico: ${S.btQ} · eje Y fijo común entre cuantiles, a escala real — el ensanchamiento de la banda es el caveat.

Excepciones del VaR — 99% · 1 año (DOP consolidado)

${tablaBt(w)}

Historia visible completa — las excepciones fuera de la ventana válida van atenuadas y rotuladas (el KPI cuenta solo la ventana válida; la diferencia es legible, no un descuadre). ${BT_CONV}. Cada punto consolidado al TC de su fecha. Variaciones al TC de cada corte; incluyen efecto FX.

La unidad de análisis es el corte del portafolio completo — no hay vistas por emisor y la leyenda de prorrateo no aplica. VaR y P&L en DOP consolidado, jamás partidos por moneda; el filtro de moneda no aplica en esta sección.

`;\n }\n function btTRHtml(w) {\n const pv = D.BT.prevWin;\n return `

Validación estadística ⓘ

Ventana válida: ${w.n} cortes desde ${w.val[0].f} (objetivo 250)

Kupiec POF

${ND_WIN(w.n)}

LR: N/D · χ²(1) · p-value: N/D · veredicto: N/D

Christoffersen (conjunto: independencia + cobertura)

${ND_WIN(w.n)}

LR conjunto: N/D · χ²(2) · p-value: N/D · veredicto: N/D

Semáforo de Basilea

${ND_WIN(w.n)}${BT_ROT_BASILEA}

Zonas normalizadas a 250 cortes: verde 0–4 · amarilla 5–9 · roja 10+ · multiplicador base 3 + recargo (referencia ilustrativa del marco de mercado)

Ventana anterior (cerrada) — referencia histórica, no es el veredicto vigente

${pv.rot} · ${pv.exc} excepciones

\n Kupiec POF${pv.kupiec.v}LR ${pv.kupiec.lr} · χ²(1) · p=${pv.kupiec.p}\n Christoffersen (conjunto)${pv.christo.v}LR ${pv.christo.lr} · χ²(2) · p=${pv.christo.p}\n

Zona ${pv.basilea.zona} · ${pv.basilea.conteo}${BT_ROT_BASILEA}

Multiplicador ${pv.basilea.mult} (referencia ilustrativa del marco de mercado)

Excepciones contadas bajo la convención de escala del mock. Las pruebas se computan solo sobre la sub-ventana homogénea vigente — jamás cruzan un cambio de supuesto (§2).

`;\n }\n function tablaBt(w) {\n const rows = w.excAll.map(c => {\n const exceso = -(c.pnl + c.varEsc);\n const sup = c.valida ? \"S&P · ρ=25%\" : \"S&P · ρ=20%\";\n return `\n ${c.f}${c.valida ? \"\" : ' fuera de ventana'}\n −${nf2.format(Math.abs(c.pnl))}MM\n ${nf2.format(c.varEsc)}MM\n ${nf2.format(exceso)}MM\n ${sup}${c.valida ? \"Sí\" : \"No\"}`;\n }).join(\"\");\n return `\n \n ${rows}

Fecha	P&L realizado (DOP MM)	VaR 99%·1a escalado (DOP MM)	Exceso (DOP MM)	Supuesto vigente	Ventana válida

`;\n }\n function chartsBt() {\n const w = btWin();\n const dates = w.cs.map(c => c.f);\n const excPts = w.cs.map((c, i) => [c, i]).filter(([c]) => c.pnl < -c.varEsc);\n mkChart(\"chBT_TL\", {\n grid: { left: 56, right: 16, top: 30, bottom: 64 },\n tooltip: { trigger: \"axis\", valueFormatter: v => (v < 0 ? \"−\" : \"\") + \"$\" + nf1.format(Math.abs(v)) + \"MM\" },\n legend: { top: 0, itemWidth: 10, itemHeight: 10, textStyle: { fontSize: 10 }, data: [\"P&L realizado\", \"−VaR escalado\", \"Excepción\"] },\n dataZoom: [{ type: \"slider\", height: 14, bottom: 4 }],\n xAxis: { type: \"category\", data: dates, axisLabel: { fontSize: 9, rotate: 40 } },\n yAxis: { type: \"value\", axisLabel: { formatter: v => (v < 0 ? \"−\" : \"\") + \"$\" + nf0(Math.abs(v)) + \"MM\", fontSize: 10 } },\n series: [\n { name: \"P&L realizado\", type: \"line\", symbol: \"none\", lineStyle: { width: 1.1 }, color: TK(\"--primary\"), data: w.cs.map(c => c.pnl) },\n { name: \"−VaR escalado\", type: \"line\", symbol: \"none\", lineStyle: { width: 1.4, type: \"dashed\" }, color: TK(\"--secondary\"), data: w.cs.map(c => -c.varEsc),\n markLine: { silent: true, symbol: \"none\", lineStyle: { type: \"dashed\", color: TK(\"--text-2\"), width: 1.4 },\n label: { formatter: D.BT.cambioLabel, fontSize: 9, color: TK(\"--text-2\"), position: \"insideEndTop\" },\n data: [{ xAxis: D.BT.EFFECTIVE }] } },\n { name: \"Excepción\", type: \"scatter\", symbol: \"diamond\", symbolSize: 11, color: TK(\"--sem-warn\"), data: excPts.map(([c, i]) => [i, c.pnl]) },\n ],\n });\n // BL — convergencia MC: eje Y fijo COMÚN entre cuantiles (min/max globales, sin recorte)\n const Ns = [5, 10, 15, 20, 30, 40, 50, 65, 80, 100]; // miles de escenarios\n const base = D.BT.VAR1A, K = 1.017;\n let yMin = Infinity, yMax = -Infinity;\n Object.values(D.BT.quantiles).forEach(({ q, nivel }) => {\n const v = base * nivel;\n const h0 = K * v * Math.sqrt((1 - q) / (q * Ns[0] * 1000));\n yMin = Math.min(yMin, v - h0 - 6); yMax = Math.max(yMax, v + h0 + 6);\n });\n const sel = D.BT.quantiles[S.btQ], nivel = base * sel.nivel;\n const est = Ns.map((n, i) => +(nivel * (1 + 0.02 * Math.sin(i * 2.1) * Math.exp(-i / 3.2))).toFixed(2));\n const hw = Ns.map(n => K * nivel * Math.sqrt((1 - sel.q) / (sel.q * n * 1000)));\n const lower = est.map((e, i) => +(e - hw[i]).toFixed(2));\n const band = hw.map(h => +(2 * h).toFixed(2));\n mkChart(\"chBT_BL\", {\n grid: { left: 56, right: 16, top: 30, bottom: 40 },\n tooltip: { trigger: \"axis\", formatter: ps => {\n const i = ps[0].dataIndex;\n return `${Ns[i]}k escenarios
VaR estimado: ${fMM(est[i])}
Banda: ±${fMM(hw[i]).slice(1)} (±${nf1.format(hw[i] / est[i] * 100)}%)`;\n } },\n legend: { top: 0, itemWidth: 10, itemHeight: 10, textStyle: { fontSize: 10 }, data: [`VaR estimado @${S.btQ}`, \"Banda de confianza\"] },\n xAxis: { type: \"category\", data: Ns.map(n => n + \"k\"), axisLabel: { fontSize: 10 }, name: \"escenarios\", nameLocation: \"middle\", nameGap: 26, nameTextStyle: { fontSize: 9 } },\n yAxis: { type: \"value\", min: Math.floor(yMin), max: Math.ceil(yMax), axisLabel: { formatter: v => \"$\" + nf0(v) + \"MM\", fontSize: 10 } },\n series: [\n { name: \"límite inferior\", type: \"line\", stack: \"band\", symbol: \"none\", lineStyle: { opacity: 0 }, color: \"transparent\", data: lower, silent: true },\n { name: \"Banda de confianza\", type: \"line\", stack: \"band\", symbol: \"none\", lineStyle: { opacity: 0 }, areaStyle: { color: TK(\"--primary\"), opacity: 0.16 }, color: TK(\"--primary\"), data: band },\n { name: `VaR estimado @${S.btQ}`, type: \"line\", symbol: \"circle\", symbolSize: 5, color: TK(\"--secondary\"), lineStyle: { width: 1.6 }, data: est },\n ],\n });\n }\n\n // ---------- Export CSV (pies + supuesto serializados — X-8d) ----------\n function exportCSV(which) {\n const lines = [];\n if (which === \"backtesting\") {\n const w = btWin();\n lines.push(`\"Risk Intelligence — Crédito · Backtesting (Excepciones del VaR — 99% · 1 año, DOP consolidado)\";\"as_of ${D.AS_OF}\";\"Supuesto: ${D.SUPUESTO.fuente} · ${D.SUPUESTO.metodo} · ${D.SUPUESTO.tc}\";\"Ventana válida: ${w.n} cortes desde ${w.val[0].f} (objetivo 250)\"`);\n lines.push(`\"Fecha\";\"P&L realizado (DOP MM)\";\"VaR 99%·1a escalado (DOP MM)\";\"Exceso (DOP MM)\";\"Supuesto vigente\";\"Ventana válida\"`);\n w.excAll.forEach(c => {\n lines.push(`\"${c.f}\";${c.pnl.toFixed(2)};${c.varEsc.toFixed(2)};${(-(c.pnl + c.varEsc)).toFixed(2)};\"${c.valida ? \"S&P · ρ=25%\" : \"S&P · ρ=20%\"}\";\"${c.valida ? \"Sí\" : \"No\"}\"`);\n });\n lines.push(`\"Nota\";\"${BT_CONV}.\"`);\n lines.push(`\"Nota\";\"El KPI de excepciones cuenta solo la ventana válida; esta tabla lista la historia visible completa — las filas fuera de ventana van rotuladas.\"`);\n lines.push(`\"Nota\";\"Cada punto consolidado al TC de su fecha. Variaciones al TC de cada corte; incluyen efecto FX. VaR y P&L jamás se parten por moneda.\"`);\n lines.push(`\"Nota\";\"Colas profundas: la banda de confianza escala ~1/q en escenarios. Bandas del estimador Monte Carlo — no es la distribución de valor del portafolio.\"`);\n const blobB = new Blob([\"\\uFEFF\" + lines.join(\"\\n\")], { type: \"text/csv;charset=utf-8\" });\n const aB = document.createElement(\"a\");\n aB.href = URL.createObjectURL(blobB); aB.download = \"credito-backtesting-excepciones.csv\"; aB.click();\n return;\n }\n if (which === \"sens\") {\n const a = sensAgg(), comp = sensComparable();\n lines.push(`\"Risk Intelligence — Crédito · Sensibilidades (Sensibilidad del VaR — 99% · 1 año, DOP consolidado)\";\"as_of ${D.AS_OF}\";\"Supuesto: ${D.SUPUESTO.fuente} · ${D.SUPUESTO.metodo} · ${D.SUPUESTO.tc}\"`);\n lines.push(`\"Supuesto\";\"Calificación\";\"Valor base\";\"Barrido (−/+)\";\"VaR− (DOP MM)\";\"VaR+ (DOP MM)\";\"ΔVaR máx (DOP MM)\";\"ΔVaR máx (% base)\";\"Var vs corte ant. (DOP MM)\"`);\n a.rows.forEach(s => {\n const varC = comp ? (Math.abs(s.dMax) - s.prevDMax).toFixed(2) : '\"N/D\"';\n lines.push(`\"${s.lbl}\";\"—\";\"${s.base}\";\"${s.swp}\";${s.lo == null ? '\"—\"' : s.lo.toFixed(2)};${s.hi.toFixed(2)};${s.dMax.toFixed(2)};${(Math.abs(s.dMax) / a.base * 100).toFixed(2)};${varC}`);\n sensDeltaByRating(s, s.extMax).forEach(({ r, v }) => {\n lines.push(`\"${s.lbl}\";\"${r}\";\"\";\"\";\"\";\"\";${v.toFixed(2)};${(Math.abs(v) / a.base * 100).toFixed(2)};${comp ? '\"\"' : '\"N/D\"'}`);\n });\n });\n lines.push(`\"Nota\";\"${SENS_CONV}.\"`);\n lines.push(`\"Nota\";\"${SENS_MICRO}. El centro del tornado ES el supuesto del badge (§2 auditable).\"`);\n lines.push(`\"Nota\";\"Base y barridos del corte consolidados al mismo TC del as_of. La columna Var compara el |ΔVaR máx| entre cortes, cada corte a su TC — incluye efecto FX. El VaR va en DOP consolidado y jamás se parte por moneda. Δ solo entre cortes con el mismo supuesto (N/D nunca 0).\"`);\n const blobS = new Blob([\"\\uFEFF\" + lines.join(\"\\n\")], { type: \"text/csv;charset=utf-8\" });\n const aS = document.createElement(\"a\");\n aS.href = URL.createObjectURL(blobS); aS.download = \"credito-sensibilidades-supuestos.csv\"; aS.click();\n return;\n }\n if (which === \"factores\") {\n const a = frAgg(), ap = frAgg(true), comp = D.FR.prevComparable;\n const dc = (cur, prev) => comp && prev > 0 ? [(cur - prev).toFixed(2), ((cur - prev) / prev * 100).toFixed(2)] : ['\"N/D\"', '\"N/D\"'];\n lines.push(`\"Risk Intelligence — Crédito · Factores de Riesgo (Contribución al VaR — 99% · 1 año, DOP consolidado)\";\"as_of ${D.AS_OF}\";\"Supuesto: ${D.SUPUESTO.fuente} · ${D.SUPUESTO.metodo} · ${D.SUPUESTO.tc}\"`);\n lines.push(`\"Factor\";\"Calificación\";\"Contribución (DOP MM)\";\"% del VaR\";\"Var (DOP MM)\";\"Var %\";\"Convención\"`);\n FR_FACTORES.forEach(([f, lbl]) => {\n const d1 = dc(a.fact[f], ap.fact[f]);\n lines.push(`\"${lbl}\";\"—\";${a.fact[f].toFixed(2)};${(a.fact[f] / a.total * 100).toFixed(2)};${d1[0]};${d1[1]};\"Euler (aditiva)\"`);\n a.rows.forEach(x => {\n const p = ap.rows.find(y => y.r === x.r);\n const d2 = dc(x.cells[f], p ? p.cells[f] : 0);\n lines.push(`\"${lbl}\";\"${x.r}\";${x.cells[f].toFixed(2)};${(x.cells[f] / a.total * 100).toFixed(2)};${d2[0]};${d2[1]};\"Euler (aditiva)\"`);\n });\n });\n const dcor = dc(a.corr, ap.corr);\n lines.push(`\"Efecto correlación\";\"—\";${a.corr.toFixed(2)};${(a.corr / a.total * 100).toFixed(2)};${dcor[0]};${dcor[1]};\"Incremental (no aditiva — fuera del subtotal Euler)\"`);\n const dtot = dc(a.total, ap.total);\n lines.push(`\"Total (Σ Euler)\";\"—\";${a.total.toFixed(2)};100.00;${dtot[0]};${dtot[1]};\"Euler (aditiva)\"`);\n lines.push(`\"Nota\";\"${FR_CONV}.\"`);\n lines.push(`\"Nota\";\"${FR_GAUSS}.\"`);\n lines.push(`\"Nota\";\"Variaciones al TC de cada corte; incluyen efecto FX. La contribución va en DOP consolidado y jamás se parte por moneda. Totales calculados sobre valores sin redondear. Δ solo entre cortes con el mismo supuesto.\"`);\n const blobF = new Blob([\"\\uFEFF\" + lines.join(\"\\n\")], { type: \"text/csv;charset=utf-8\" });\n const aF = document.createElement(\"a\");\n aF.href = URL.createObjectURL(blobF); aF.download = \"credito-factores-mapa.csv\"; aF.click();\n return;\n }\n if (which === \"marginal\") {\n lines.push(`\"Risk Intelligence — Crédito · Marginal (${S.medida})\";\"as_of ${D.AS_OF}\";\"Supuesto: ${D.SUPUESTO.fuente} · ${D.SUPUESTO.metodo} · ${D.SUPUESTO.tc}\"`);\n lines.push(`\"Calificación\";\"Emisor\";\"Instrumento\";\"Moneda\";\"VM DOP (MM)\";\"${S.medida} Marginal (DOP MM)\";\"Componental (DOP MM)\";\"% del total (base componental)\";\"Standalone (DOP MM)\";\"Benef. diversificación (DOP MM)\";\"Var Marginal (DOP MM)\";\"Var %\"`);\n const rows = mgRows(), prevRows = mgRows(true);\n const total = rows.reduce((a, x) => a + x.comp, 0);\n D.RATINGS.forEach(r => rows.filter(x => x.p.rating === r).sort((a, b) => b.v - a.v).forEach(x => {\n const prev = prevRows.find(y => y.p.inst === x.p.inst && y.p.emisor === x.p.emisor);\n const dv = prev ? (x.marg - prev.marg).toFixed(2) : '\"N/D\"';\n const dvp = prev && prev.marg !== 0 ? ((x.marg - prev.marg) / Math.abs(prev.marg) * 100).toFixed(2) : '\"N/D\"';\n lines.push(`\"${x.p.rating}\";\"${x.p.emisor}\";\"${x.p.inst}\";\"${x.p.moneda}\";${x.v.toFixed(2)};${x.marg.toFixed(2)};${x.comp.toFixed(2)};${(x.comp / total * 100).toFixed(2)};${x.stand.toFixed(2)};${(x.stand - x.comp).toFixed(2)};${dv};${dvp}`);\n }));\n lines.push(`\"Nota\";\"${NOTA_GRANULARIDAD}\"`);\n lines.push(`\"Nota\";\"Marginal = leave-one-out, NO aditiva (Σ marginales ≠ ${S.medida} total). Componental = Euler, aditiva (Σ = ${S.medida} total). Los % pueden superar 100% por contribuciones negativas.\"`);\n lines.push(`\"Nota\";\"Var refiere al Marginal; variaciones al TC de cada corte, incluyen efecto FX. El ${S.medida} va en DOP consolidado y jamás se parte por moneda.\"`);\n const blobM = new Blob([\"\\uFEFF\" + lines.join(\"\\n\")], { type: \"text/csv;charset=utf-8\" });\n const aM = document.createElement(\"a\");\n aM.href = URL.createObjectURL(blobM); aM.download = `credito-marginal-${S.medida.toLowerCase()}.csv`; aM.click();\n return;\n }\n if (which === \"mr-fecha\" || which === \"mr-hist\") {\n // X-13: el export histórico serializa el supuesto de AMBOS cortes\n const supHist = which === \"mr-hist\" ? `;\"Supuesto corte anterior (28/01/2026): idéntico — ${D.SUPUESTO.fuente} · ${D.SUPUESTO.metodo}\"` : \"\";\n lines.push(`\"Risk Intelligence — Crédito · Métricas de Riesgo (${S.medida})\";\"as_of ${D.AS_OF}\";\"Supuesto: ${D.SUPUESTO.fuente} · ${D.SUPUESTO.metodo} · ${D.SUPUESTO.tc}\"${supHist}`);\n const a = mrAgg(), ap = mrAgg(true);\n if (which === \"mr-fecha\") {\n lines.push(`\"Calificación\";\"VM DOP (MM)\";\"VM USD (MM)\";\"VM Total DOP (MM)\";\"${S.medida} (DOP MM)\";\"% del ${S.medida}\"`);\n a.rows.forEach(x => {\n const ps = D.positions.filter(p => p.rating === x.r);\n const vmDop = ps.filter(p => p.moneda === \"DOP\").reduce((s, p) => s + p.vm, 0);\n const vmUsd = ps.filter(p => p.moneda === \"USD\").reduce((s, p) => s + p.vm, 0);\n lines.push(`\"${x.r}\";${vmDop ? vmDop.toFixed(2) : '\"—\"'};${vmUsd ? vmUsd.toFixed(2) : '\"—\"'};${x.vm.toFixed(2)};${x.contrib.toFixed(2)};${(x.contrib / a.total * 100).toFixed(2)}`);\n });\n } else {\n lines.push(`\"Calificación\";\"VM Total DOP (MM)\";\"${S.medida} (DOP MM)\";\"Var (DOP MM)\";\"Var %\"`);\n a.rows.forEach(x => {\n const prev = ap.rows.find(y => y.r === x.r);\n const dv = prev ? (x.contrib - prev.contrib).toFixed(2) : '\"N/D\"';\n const dvp = prev ? ((x.contrib - prev.contrib) / prev.contrib * 100).toFixed(2) : '\"N/D\"';\n lines.push(`\"${x.r}\";${x.vm.toFixed(2)};${x.contrib.toFixed(2)};${dv};${dvp}`);\n });\n lines.push(`\"Nota\";\"Variaciones al TC de cada corte; incluyen efecto FX. Δ solo entre cortes con el mismo supuesto.\"`);\n }\n lines.push(`\"Nota\";\"El ${S.medida} va en DOP consolidado y jamás se parte por moneda (no aditivo). Contribuciones por emisor: prorrateo por exposición — el modelo opera a nivel rating.\"`);\n const blob0 = new Blob([\"\\uFEFF\" + lines.join(\"\\n\")], { type: \"text/csv;charset=utf-8\" });\n const a0 = document.createElement(\"a\");\n a0.href = URL.createObjectURL(blob0); a0.download = `credito-metricas-${S.medida.toLowerCase()}-${which}.csv`; a0.click();\n return;\n }\n lines.push(`\"Risk Intelligence — Crédito · Portafolio\";\"as_of ${D.AS_OF}\";\"Supuesto: ${D.SUPUESTO.fuente} · ${D.SUPUESTO.metodo} · ${D.SUPUESTO.tc}\"`);\n if (which === \"global\") {\n lines.push(`\"Calificación\";\"VM DOP (MM)\";\"VM USD (MM)\";\"VM Total DOP (MM)\";\"% Global\";\"Var (DOP MM)\";\"Var %\"`);\n const t = total();\n D.RATINGS.forEach(r => {\n const ps = filt().filter(p => p.rating === r); if (!ps.length) return;\n const dopV = ps.filter(p => p.moneda === \"DOP\").reduce((a, p) => a + p.vm, 0);\n const usdV = ps.filter(p => p.moneda === \"USD\").reduce((a, p) => a + p.vm, 0);\n const tot = ps.reduce((a, p) => a + dop(p), 0), prev = ps.reduce((a, p) => a + dopPrev(p), 0);\n lines.push(`\"${r}\";${dopV ? dopV.toFixed(2) : '\"—\"'};${usdV ? usdV.toFixed(2) : '\"—\"'};${tot.toFixed(2)};${(tot / t * 100).toFixed(2)};${prev > 0 ? (tot - prev).toFixed(2) : '\"N/D\"'};${prev > 0 ? ((tot - prev) / prev * 100).toFixed(2) : '\"N/D\"'}`);\n });\n lines.push(`\"Nota\";\"Variaciones al TC de cada corte; incluyen efecto FX.\"`);\n } else {\n lines.push(`\"Emisor\";\"Moneda\";\"VM DOP (MM)\";\"% VM\";\"Aporte HHI\";\"Límite interno %\";\"Holgura/Exceso pp\";\"Estado\"`);\n emisorStats().forEach(r => {\n const st = estadoEmisor(r.pct);\n lines.push(`\"${r.emisor}\";\"${r.chip}\";${r.vm.toFixed(2)};${r.pct.toFixed(2)};${r.hhi.toFixed(4)};${D.LIMITES.emisorPctInterno.toFixed(1)};${(D.LIMITES.emisorPctInterno - r.pct).toFixed(1)};\"${st.txt}\"`);\n });\n lines.push(`\"Nota\";\"Límites de exposición sobre VM observado; sin límite → N/D.\"`);\n }\n const blob = new Blob([\"\\uFEFF\" + lines.join(\"\\n\")], { type: \"text/csv;charset=utf-8\" });\n const a = document.createElement(\"a\");\n a.href = URL.createObjectURL(blob); a.download = `credito-portafolio-${which}.csv`; a.click();\n }\n\n // ---------- Bind + estados ----------\n // ---------- Factores de Riesgo (F2.8, §12) — medida canónica VaR 99%·1a FORZADA (X-#1/#3): jamás S.medida ----------\n const FR_FACTORES = [[\"mig\", \"Migración (non-default)\"], [\"def\", \"Default\"], [\"rec\", \"Recovery\"], [\"spr\", \"Spread\"]];\n const FR_CONV = \"Convención de atribución: las barras/filas Euler (migración · default · recovery · spread) son ADITIVAS — Σ = VaR total. El Efecto correlación es INCREMENTAL (VaR(ρ activo) − VaR(ρ=0), método de diferencias) y jamás se suma con las barras: la correlación es la estructura que acopla los factores, no un sumando\";\n const FR_GAUSS = \"Retorno de activo estandarizado bajo Alt 2 — no es la distribución de valor del portafolio\";\n function frAgg(prev = false) {\n const getVal = prev ? dopPrev : dop;\n const vm = new Map();\n D.positions.forEach(p => vm.set(p.rating, (vm.get(p.rating) || 0) + getVal(p)));\n const rows = D.RATINGS.filter(r => (vm.get(r) || 0) > 0).map(r => {\n const contrib = vm.get(r) * D.RISK.VaR.rate[r] * D.RISK.VaR.divF[r]; // fórmula única sin redondear (≡ mrAgg-VaR ≡ BT.VAR1A)\n const cells = {}; FR_FACTORES.forEach(([f]) => { cells[f] = contrib * D.FR.W[r][f]; });\n return { r, contrib, cells };\n });\n const total = rows.reduce((s, x) => s + x.contrib, 0);\n const fact = {}; FR_FACTORES.forEach(([f]) => { fact[f] = rows.reduce((s, x) => s + x.cells[f], 0); });\n return { rows, total, fact, corr: total * (1 - D.FR.RHO_ZERO_FACTOR) };\n }\n function frPredominante() { // misma definición que §7.1 KPI 4: share de VM, cartera completa (X-#4)\n const m = new Map();\n D.positions.forEach(p => m.set(p.rating, (m.get(p.rating) || 0) + dop(p)));\n const top = [...m.entries()].sort((a, b) => b[1] - a[1])[0][0];\n return [\"CCC\", \"D\"].includes(top) ? \"CCC\" : top; // grupo predominante CCC–D → CCC (§12)\n }\n const frRatingSel = () => S.frRating || frPredominante();\n const FR_TITLES = [\"VaR de Crédito Total — 99% · 1 año\", \"Factor dominante\", \"Efecto correlación\", \"Probabilidad de ≥1 default\", \"Uso Límite\"];\n const kpisNDFR = () => FR_TITLES.map(t => kpiCard(t, \"N/D\", \"\", [])).join(\"\");\n function frUsoLimite(total) { // límite del VaR, nunca S.medida (X-#1; precedente btUsoLimite)\n const lim = D.LIM_MEDIDA.VaR;\n if (lim == null) return kpiCard(\"Uso Límite\", \"N/D\", \"Sin límite configurado para VaR\", []);\n const uso = total / lim * 100;\n const st = uso > 100 ? [\"err\", \"Incumplimiento\"] : uso >= 90 ? [\"warn\", \"Advertencia\"] : [\"ok\", \"Ok\"];\n return kpiCard(\"Uso Límite\", `${fPct(uso, 1)} ${st[1]}`,\n `VaR 99%·1a vs. límite interno ${fMM(lim)} · cartera consolidada completa`, []);\n }\n function frLeyendaTL(a) { // conmutación §12: jamás se afirma Σ=VaR con datos incompletos (rama no demostrable en el mock — feedback-log)\n const resid = a.total - FR_FACTORES.reduce((s, [f]) => s + (Number.isFinite(a.fact[f]) ? a.fact[f] : 0), 0);\n return Math.abs(resid) < 0.005\n ? \"Leyenda: Atribución Euler — Σ barras = VaR total.\"\n : `Leyenda: Atribución parcial — residual no atribuido: ${fMM(resid)}. Barra sin dato: ausente + “N/D”.`;\n }\n function frHtml() {\n if (S.uiState === \"loading\") return `

${kpiSkeletons()}

${panelSkeletons()}

`;\n if (S.uiState === \"empty\") return `

${kpisNDFR()}

${statePanels(emptyBox())}

`;\n if (S.uiState === \"error\") return `

${kpisNDFR()}

${statePanels(errBox())}

`;\n const a = frAgg(), ap = frAgg(true), comp = D.FR.prevComparable;\n const dv = a.total - ap.total, dvp = ap.total > 0 ? dv / ap.total * 100 : null;\n const orden = FR_FACTORES.slice();\n const dom = orden.sort((x, y) => a.fact[y[0]] - a.fact[x[0]])[0];\n const domPrev = FR_FACTORES.slice().sort((x, y) => ap.fact[y[0]] - ap.fact[x[0]])[0];\n const tipComp = \"Comparabilidad de cortes (§11): si el supuesto del corte anterior difiere, el valor anterior pasa a N/D — un factor dominante calculado bajo otro ρ no es comparable.\";\n const kpis =\n kpiCard(\"VaR de Crédito Total — 99% · 1 año\", fMM(a.total), \"Consolidado en DOP · TC del corte\", comp ? [\n [\"anterior\", fMM(ap.total)],\n [\"Δ\", (dv >= 0 ? \"+\" : \"−\") + fMM(Math.abs(dv)).slice(1), \"trend\"],\n [\"Δ%\", dvp === null ? \"N/D\" : fPct(dvp), \"trend\"]] : [[\"anterior\", \"N/D\"], [\"Δ\", \"N/D\", \"trend\"], [\"Δ%\", \"N/D\", \"trend\"]]) +\n kpiCard(\"Factor dominante\", esc(dom[1].replace(\" (non-default)\", \"\")),\n `${fPct(a.fact[dom[0]] / a.total * 100, 1)} del VaR · atribución Euler`, [\n [\"anterior\", comp ? `${esc(domPrev[1].replace(\" (non-default)\", \"\"))}` : `N/D`]]) +\n kpiCard(`Efecto correlación ⓘ`,\n \"+\" + fMM(a.corr), `${fPct(a.corr / a.total * 100, 1)} del VaR · vs. ρ=0`, comp ? [\n [\"anterior\", \"+\" + fMM(ap.corr)],\n [\"Δ\", (a.corr - ap.corr >= 0 ? \"+\" : \"−\") + fMM(Math.abs(a.corr - ap.corr)).slice(1), \"trend\"]] : [[\"anterior\", \"N/D\"], [\"Δ\", \"N/D\", \"trend\"]]) +\n (comp\n ? kpiCard(`Probabilidad de ≥1 default ⓘ`,\n fPct(D.FR.P_DEFAULT * 100, 1), \"horizonte 1 año · libro completo\", [])\n : kpiCard(`Probabilidad de ≥1 default ⓘ`, \"N/D\", \"supuesto del corte anterior distinto\", [])) +\n frUsoLimite(a.total);\n const r0 = frRatingSel();\n return `

${kpis}

Contribución por factor — Atribución Euler (VaR, DOP MM)

${frLeyendaTL(a)} El “Efecto correlación” es el marcador anotado — nunca una barra. ${FR_CONV}.

${S.uiState === \"partial\" ? errBox() : `\n

Umbrales de Merton — variable latente

\n ${[\"AAA\", \"AA\", \"A\", \"BBB\", \"BB\", \"B\", \"CCC\"].map(r =>\n ``).join(\"\")}

${FR_GAUSS} — la silueta multimodal del valor vive en Escenarios.

Densidad normal estándar del retorno de activo con las fronteras Z del rating de partida ${r0} (default del selector: calificación predominante por share de VM). Bandas de llegada AAA…CCC y cola de default sombreada (inferior). D excluido del selector: estado absorbente, sin migración de salida. Umbrales derivados de la matriz de transición del supuesto.

Matriz ρ asumida (correlación de activos)

Matriz uniforme — ρ=25% axiomático (Alt 2). Escala secuencial neutra: la correlación no es estado de límite. Función del panel: auditar el supuesto — uniforme ⇒ método axiomático vigente; bajo cópula empírica (Alt 1) mostraría la co-migración por par de ratings y esta anotación conmutaría.

Contribución al VaR — 99% · 1 año (DOP consolidado)

${tablaFr(a, ap)}

Variaciones al TC de cada corte; incluyen efecto FX — la contribución va en DOP consolidado y jamás se parte por moneda. Totales calculados sobre valores sin redondear. ${FR_CONV}.

`;\n }\n function tablaFr(a, ap) {\n const comp = D.FR.prevComparable;\n const varCells = (cur, prev) => {\n if (!comp || !(prev > 0)) return `N/DN/D`;\n const d = cur - prev;\n return `${(d >= 0 ? \"+\" : \"−\") + fMM(Math.abs(d)).slice(1)}${fPct(d / prev * 100)}`;\n };\n let rows = \"\";\n FR_FACTORES.forEach(([f, lbl]) => {\n const open = S.frExp[f];\n rows += `${open ? \"▾\" : \"▸\"} ${lbl}\n ${fMM(a.fact[f])}${fPct(a.fact[f] / a.total * 100, 1)}${varCells(a.fact[f], ap.fact[f])}`;\n if (open) a.rows.forEach(x => {\n const p = ap.rows.find(y => y.r === x.r);\n rows += `${x.r}\n ${fMM(x.cells[f])}${fPct(x.cells[f] / a.total * 100, 1)}${varCells(x.cells[f], p ? p.cells[f] : 0)}`;\n });\n });\n rows += `Efecto correlación incremental\n +${fMM(a.corr)}${fPct(a.corr / a.total * 100, 1)}${varCells(a.corr, ap.corr)}`;\n rows += `Total (Σ Euler)${fMM(a.total)}100.0%${varCells(a.total, ap.total)}`;\n return `${rows}

Factor / Calificación	Contribución (DOP MM)	% del VaR	Var (DOP MM)	Var %

`;\n }\n function chartsFr() {\n const a = frAgg();\n mkChart(\"chFR_TL\", {\n grid: { left: 56, right: 16, top: 40, bottom: 30 },\n tooltip: { trigger: \"axis\", valueFormatter: v => fMM(v) },\n xAxis: { type: \"category\", data: FR_FACTORES.map(x => x[1].replace(\" (non-default)\", \"\")), axisLabel: { fontSize: 10, interval: 0 } },\n yAxis: { type: \"value\", name: \"DOP MM\", axisLabel: { formatter: v => \"$\" + nf0(v) } },\n series: [{\n type: \"bar\", name: \"Contribución Euler\", data: FR_FACTORES.map(([f]) => +a.fact[f].toFixed(2)), barWidth: \"46%\",\n itemStyle: { color: TK(\"--primary\") },\n label: { show: true, position: \"top\", fontSize: 10, formatter: p => fMM(p.value) },\n markLine: {\n symbol: \"none\", lineStyle: { type: \"dashed\", color: TK(\"--text-2\"), width: 1.5 },\n label: { formatter: `Efecto correlación: +${fMM(a.corr)} (incremental, no aditivo)`, fontSize: 10, position: \"insideEndTop\", color: TK(\"--text-2\") },\n data: [{ yAxis: +a.corr.toFixed(2) }],\n },\n }],\n });\n if (S.uiState !== \"partial\") {\n const bnds = D.FR.Z[frRatingSel()]; // peor→mejor: D, CCC, …, AA (zUp crecientes)\n const xs = []; for (let z = -4; z <= 4.0001; z += 0.05) xs.push(+z.toFixed(2));\n const areas = []; let lo = -4;\n bnds.forEach(b => { if (b.zUp > -4) { areas.push({ name: b.dest, lo, hi: Math.min(b.zUp, 4) }); lo = b.zUp; } });\n areas.push({ name: \"AAA\", lo, hi: 4 });\n mkChart(\"chFR_TR\", {\n grid: { left: 30, right: 16, top: 24, bottom: 30 },\n tooltip: { show: false },\n xAxis: { type: \"value\", min: -4, max: 4, name: \"Z\", nameGap: 6, axisLabel: { fontSize: 10 } },\n yAxis: { type: \"value\", axisLabel: { show: false }, splitLine: { show: false } },\n series: [{\n type: \"line\", data: xs.map(z => [z, +(Math.exp(-z * z / 2) / Math.sqrt(2 * Math.PI)).toFixed(5)]),\n showSymbol: false, lineStyle: { color: TK(\"--primary\"), width: 2 },\n areaStyle: { color: TK(\"--primary\"), opacity: 0.05 },\n markArea: {\n silent: true,\n data: areas.map((ar, i) => [\n { xAxis: ar.lo, itemStyle: { color: ar.name === \"D\" ? GRAY : \"transparent\", opacity: ar.name === \"D\" ? 0.45 : 0 },\n label: { formatter: ar.name === \"D\" ? \"D (default)\" : ar.name, fontSize: 8, rotate: 90,\n position: (ar.hi - ar.lo) < 0.45 ? (i % 2 ? \"insideTop\" : \"insideBottom\") : \"insideBottom\",\n color: TK(\"--text-2\") } },\n { xAxis: ar.hi }]),\n },\n markLine: {\n symbol: \"none\", lineStyle: { color: TK(\"--text-2\"), width: 1, opacity: 0.5 },\n label: { show: false },\n data: bnds.filter(b => b.zUp > -4 && b.zUp < 4).map(b => ({ xAxis: b.zUp })),\n },\n }],\n });\n }\n const L7 = [\"AAA\", \"AA\", \"A\", \"BBB\", \"BB\", \"B\", \"CCC–D\"];\n const hm = []; for (let i = 0; i < 7; i++) for (let j = 0; j < 7; j++) hm.push([j, i, D.FR.RHO_UNIF]);\n mkChart(\"chFR_BL\", {\n grid: { left: 56, right: 16, top: 10, bottom: 30 },\n tooltip: { formatter: p => `${L7[p.value[1]]} × ${L7[p.value[0]]}: ρ = ${p.value[2]}%
Correlación entre pares de emisores de los ratings — no es autocorrelación de un activo (≠1 por diseño)` },\n xAxis: { type: \"category\", data: L7, axisLabel: { fontSize: 10 } },\n yAxis: { type: \"category\", data: L7, axisLabel: { fontSize: 10 } },\n visualMap: { show: false, min: 0, max: 50, inRange: { color: [\"#eef3fa\", \"#a9c7ea\", TK(\"--primary\")] } },\n series: [{ type: \"heatmap\", data: hm, label: { show: true, fontSize: 9, formatter: p => p.value[2] }, itemStyle: { borderColor: \"#fff\", borderWidth: 1 } }],\n });\n }\n\n // ---------- Sensibilidades (F2.9, §13) — medida canónica VaR 99%·1a FORZADA: jamás S.medida ----------\n // Barridos OAT+CRN precomputados del corte oficial (set no editable — frontera con Escenarios §9:\n // aquí no hay histogramas, ni G/P, ni Aplicar). ΔVaR = medida de riesgo → NEUTRO siempre.\n const SENS_CONV = \"Barridos one-at-a-time con números aleatorios comunes (OAT+CRN) — cada barra mueve un supuesto; el resto permanece en base. Supuestos categóricos (fuente de transición): barra unilateral desde el centro, alternativa única\";\n const SENS_MICRO = \"Barridos OAT alrededor del supuesto oficial del badge; el corte se calcula con ρ=25%\";\n function sensAgg() {\n const base = frAgg().total; // fuente única: ≡ mrAgg-VaR ≡ BT.VAR1A ≡ FR total (coherencia entre secciones)\n const basePrev = frAgg(true).total;\n const rows = D.SENS.sweeps.map(s => {\n const lo = s.fLo == null ? null : base * s.fLo;\n const hi = base * s.fHi;\n const dLo = lo == null ? null : lo - base, dHi = hi - base;\n const dMax = lo == null ? dHi : (Math.abs(dLo) >= Math.abs(dHi) ? dLo : dHi);\n const extMax = lo == null ? \"hi\" : (Math.abs(dLo) >= Math.abs(dHi) ? \"lo\" : \"hi\");\n const prevDMax = D.SENS.prevFmax[s.id] * basePrev; // |ΔVaR máx| del corte anterior\n return { ...s, lo, hi, dLo, dHi, dMax, extMax, prevDMax };\n }).sort((a, b) => Math.abs(b.dMax) - Math.abs(a.dMax));\n return { base, basePrev, rows };\n }\n const sensComparable = () => D.FR.prevComparable && D.SENS.publishedUnderBadge; // flag único heredado del badge; publishedUnderBadge domina (X-1)\n const sensSelRow = a => a.rows.find(r => r.id === S.sensSel) || a.rows[0]; // default = más influyente\n const sensExtSel = row => S.sensExt && !(row.unilateral && S.sensExt === \"lo\") ? S.sensExt : row.extMax;\n function sensDeltaByRating(row, ext) { // Δ contribución Euler por rating — aditiva: Σ = ΔVaR del extremo (mismo run EOD, CRN)\n const d = ext === \"lo\" ? row.dLo : row.dHi;\n return D.RATINGS.map(r => ({ r, v: d * row.wR[r] }));\n }\n const SENS_TITLES = [\"VaR de Crédito Total — 99% · 1 año\", \"Supuesto más influyente\", \"Supuestos que cruzan el límite\", \"Rango del barrido de ρ (15%→35%)\", \"Uso Límite\"];\n const kpisNDSens = () => SENS_TITLES.map(t => kpiCard(t, \"N/D\", \"\", [])).join(\"\");\n const sensBanner = `

Barridos calculados bajo otro supuesto — pendiente de recálculo del corte.\n Los KPIs 2–4 y los paneles derivados de barridos pasan a N/D: el centro del tornado debe ser el supuesto del badge (§2 auditable) y el badge jamás se altera para cuadrar.\n El VaR base y el Uso Límite provienen del corte oficial válido y sobreviven. Ver el corte oficial en Métricas de Riesgo →

`;\n function sensHtml() {\n if (S.uiState === \"loading\") return `

${kpiSkeletons()}

${panelSkeletons()}

`;\n if (S.uiState === \"empty\") return `

${kpisNDSens()}

${statePanels(emptyBox())}

`;\n if (S.uiState === \"error\") return `

${kpisNDSens()}

${statePanels(errBox())}

`;\n const a = sensAgg();\n const comp = sensComparable();\n // Estado \"Error parcial\" del prototipo = rama badge↔barridos (X-7): demuestra el desfase de publicación\n const published = S.uiState === \"partial\" ? false : D.SENS.publishedUnderBadge;\n const dv = a.base - a.basePrev, dvp = a.basePrev > 0 ? dv / a.basePrev * 100 : null;\n const kpi1 = kpiCard(\"VaR de Crédito Total — 99% · 1 año\", fMM(a.base), \"Consolidado en DOP · TC del corte\", D.FR.prevComparable ? [\n [\"anterior\", fMM(a.basePrev)],\n [\"Δ\", (dv >= 0 ? \"+\" : \"−\") + fMM(Math.abs(dv)).slice(1), \"trend\"],\n [\"Δ%\", dvp === null ? \"N/D\" : fPct(dvp), \"trend\"]] : [[\"anterior\", \"N/D\"], [\"Δ\", \"N/D\", \"trend\"], [\"Δ%\", \"N/D\", \"trend\"]]);\n const kpi5 = (() => { // Uso Límite literal §13: \"sobre VaR base\" (R-#1) — misma regla y dato que frUsoLimite\n const lim = D.LIM_MEDIDA.VaR;\n if (lim == null) return kpiCard(\"Uso Límite\", \"N/D\", \"sobre VaR base · sin límite configurado para VaR\", []);\n const uso = a.base / lim * 100;\n const st = uso > 100 ? [\"err\", \"Incumplimiento\"] : uso >= 90 ? [\"warn\", \"Advertencia\"] : [\"ok\", \"Ok\"];\n return kpiCard(\"Uso Límite\", `${fPct(uso, 1)} ${st[1]}`,\n `sobre VaR base · vs. límite interno ${fMM(lim)} · el cruce del límite por los barridos se lee en la curva de ρ y en el KPI 3`, []);\n })();\n if (!published) {\n return `${sensBanner}

${kpi1 + SENS_TITLES.slice(1, 4).map(t => kpiCard(t, \"N/D\", \"pendiente de recálculo del corte\", [])).join(\"\") + kpi5}

${statePanels(`

◌\n Barridos no publicados bajo el supuesto del badge\n El panel se calcula del set de barridos oficial; se repobla al recalcular el corte bajo el supuesto vigente.

`)}

`;\n }\n const top = a.rows[0];\n const nCruzan = D.LIM_MEDIDA.VaR == null ? null : a.rows.filter(r => (r.lo != null && r.lo > D.LIM_MEDIDA.VaR) || r.hi > D.LIM_MEDIDA.VaR).length;\n const rho = a.rows.find(r => r.id === \"rho\");\n const amp = rho.hi - rho.lo;\n const tipComp = \"Comparabilidad de cortes (§11): si el supuesto del corte anterior difiere, el valor anterior pasa a N/D — un barrido calculado bajo otro supuesto no es comparable.\";\n const tipAmp = \"Distinto del “Efecto correlación” de Factores de Riesgo (+\" + fMM(frAgg().corr) + \" = VaR(ρ activo) − VaR(ρ=0), incremental); este rango es la amplitud del barrido oficial de ρ entre 15% y 35%.\";\n const kpis = kpi1 +\n kpiCard(\"Supuesto más influyente\", esc(top.lbl),\n `|ΔVaR| máx ${fMM(Math.abs(top.dMax))} · ${fPct(Math.abs(top.dMax) / a.base * 100, 1)} del VaR base`, [\n [\"anterior\", comp ? `${esc(D.SENS.prevInfluyente)}` : `N/D`]]) +\n kpiCard(\"Supuestos que cruzan el límite\", nCruzan == null ? \"N/D\" : String(nCruzan),\n nCruzan == null ? \"Límite de VaR: N/D\" : `de ${a.rows.length} barridos vs. límite ${fMM(D.LIM_MEDIDA.VaR)} · conteo neutro — el semáforo vive en Uso Límite; el cruce se lee en la curva de ρ y en la tabla`, []) +\n kpiCard(`Rango del barrido de ρ (15%→35%) ⓘ`,\n fMM(amp), `${fPct(amp / a.base * 100, 1)} del VaR base · @base ρ=25%`, comp ? [\n [\"VaR@15%\", fMM(rho.lo)], [\"VaR@35%\", fMM(rho.hi)]] : [[\"anterior\", \"N/D\"]]) +\n kpi5;\n const selRow = sensSelRow(a), ext = sensExtSel(selRow);\n const dSel = ext === \"lo\" ? selRow.dLo : selRow.dHi;\n return `

${kpis}

Tornado de supuestos — impacto en el VaR 99%·1a (DOP MM)

${SENS_CONV}. ${SENS_MICRO}.

Eje en VaR absoluto (DOP MM); la línea central es el VaR base ${fMM(a.base)} — el centro del tornado ES el supuesto del badge (§2). Leyenda −/+ referida al valor del supuesto, no al VaR (μ recovery a la baja SUBE el VaR). Signo del barrido de fuente: la matriz Moody's del mock tiene PDs speculative-grade mayores. Barra sin dato → ausente + “N/D”.

Curva VaR vs ρ — 99% · 1 año

Set oficial de ρ {15% · 25% · 35%}; marcador relleno = ρ base 25% (supuesto del badge). Límite de VaR ${D.LIM_MEDIDA.VaR == null ? \"N/D\" : fMM(D.LIM_MEDIDA.VaR)} fuera de escala del eje — holgura mínima ${D.LIM_MEDIDA.VaR == null ? \"N/D\" : fMM(D.LIM_MEDIDA.VaR - rho.hi)} en VaR@35% (eje ajustado a los datos para leer la pendiente). Explorar un barrido configurable → Escenarios

Δ de contribución Euler por calificación — ${esc(selRow.lbl)}

\n \n \n ${[\"lo\", \"hi\"].map(x => ``).join(\"\")}

Aditiva: Σ barras = ΔVaR del extremo mostrado (${(dSel >= 0 ? \"+\" : \"−\") + fMM(Math.abs(dSel)).slice(1)}) — Δ de la contribución componental (Euler) por rating, mismo run EOD con CRN.

Extremo ${ext === \"lo\" ? \"− (supuesto a la baja)\" : \"+ (supuesto al alza)\"} del barrido; default = extremo de mayor |ΔVaR|. Barras en neutro; barra sin dato → ausente + “N/D”.${selRow.unilateral ? \" Barrido unilateral: solo existe el extremo +.\" : \"\"}

Sensibilidad del VaR — 99% · 1 año (DOP consolidado)

${tablaSens(a, comp)}

Base y barridos del corte consolidados al mismo TC del as_of; la columna Var compara el |ΔVaR máx| entre cortes, cada corte a su TC — incluye efecto FX (F1.10). ${SENS_CONV}. “—” = lado inexistente (no aplica); “N/D” = no comparable (nunca 0).

`;\n }\n function tablaSens(a, comp) {\n let rows = \"\";\n a.rows.forEach(s => {\n const open = S.sensExp[s.id];\n const varCell = comp ? (() => { const d = Math.abs(s.dMax) - s.prevDMax; return `${(d >= 0 ? \"+\" : \"−\") + fMM(Math.abs(d)).slice(1)}`; })()\n : `N/D`;\n rows += `${open ? \"▾\" : \"▸\"} ${esc(s.lbl)}\n ${esc(s.base)}${esc(s.swp)}\n ${s.lo == null ? \"—\" : fMM(s.lo)}${fMM(s.hi)}\n ${(s.dMax >= 0 ? \"+\" : \"−\") + fMM(Math.abs(s.dMax)).slice(1)}\n ${fPct(Math.abs(s.dMax) / a.base * 100, 1)}${varCell}`;\n if (open) sensDeltaByRating(s, s.extMax).forEach(({ r, v }) => {\n rows += `${r}\n ${(v >= 0 ? \"+\" : \"−\") + fMM(Math.abs(v)).slice(1)}\n ${fPct(Math.abs(v) / a.base * 100, 2)}${comp ? \"\" : \"N/D\"}`;\n });\n });\n return `\n ${rows}

Supuesto / Calificación	Valor base	Barrido (−/+)	VaR− (DOP MM)	VaR+ (DOP MM)	ΔVaR máx (DOP MM)	ΔVaR máx (% base)	Var vs corte ant. (DOP MM)

`;\n }\n function chartsSens() {\n const a = sensAgg();\n // TL — tornado: barras flotantes en eje de VaR absoluto. Segmentos por GEOMETRÍA (izq/der del\n // VaR base) con color por DIRECCIÓN DEL INPUT (−/+): en μ recovery el input − SUBE el VaR,\n // así el color sigue siendo veraz aunque el lado se invierta (X-6).\n const cats = a.rows.slice().reverse(); // ECharts y-category pinta de abajo hacia arriba → arriba = mayor |Δ|\n const NEU_LO = \"#8ea3c4\", NEU_HI = TK(\"--primary\") || \"#0d77bf\";\n const geo = cats.map(r => {\n const vals = [r.hi, ...(r.lo == null ? [] : [r.lo])];\n const minV = Math.min(a.base, ...vals), maxV = Math.max(a.base, ...vals);\n const leftInput = r.lo != null && r.lo < a.base ? \"lo\" : (r.hi < a.base ? \"hi\" : null);\n const rightInput = r.hi > a.base ? \"hi\" : (r.lo != null && r.lo > a.base ? \"lo\" : null);\n return { r, minV, maxV, leftInput, rightInput,\n leftSpan: a.base - minV, rightSpan: maxV - a.base,\n leftDelta: leftInput ? (leftInput === \"lo\" ? r.dLo : r.dHi) : null,\n rightDelta: rightInput ? (rightInput === \"lo\" ? r.dLo : r.dHi) : null };\n });\n const colIn = inp => inp === \"lo\" ? NEU_LO : NEU_HI;\n const minX = Math.min(...geo.map(g => g.minV)) - 8;\n const maxX = Math.max(...geo.map(g => g.maxV)) + 8;\n const fD = d => (d >= 0 ? \"+\" : \"−\") + fMM(Math.abs(d)).slice(1);\n mkChart(\"chSN_TL\", {\n grid: { left: 150, right: 46, top: 26, bottom: 26 },\n legend: { top: 0, itemWidth: 12, itemHeight: 8, textStyle: { fontSize: 10 },\n data: [{ name: \"− (supuesto a la baja)\", itemStyle: { color: NEU_LO } }, { name: \"+ (supuesto al alza)\", itemStyle: { color: NEU_HI } }] },\n tooltip: { trigger: \"axis\", axisPointer: { type: \"shadow\" }, formatter: ps => {\n const row = a.rows.find(r => r.lbl === ps[0].name); if (!row) return \"\";\n const l1 = row.lo == null ? \"VaR−: — (barrido unilateral — alternativa única)\" : `VaR− (input a la baja): ${fMM(row.lo)} (Δ ${fD(row.dLo)})`;\n return `${row.lbl} · base ${row.base} · barrido ${row.swp}
${l1}
VaR+ (input al alza): ${fMM(row.hi)} (Δ ${fD(row.dHi)})`;\n } },\n xAxis: { type: \"value\", min: +minX.toFixed(0), max: +maxX.toFixed(0), name: \"VaR (DOP MM)\", nameLocation: \"middle\", nameGap: 22, nameTextStyle: { fontSize: 9 }, axisLabel: { fontSize: 9, formatter: v => \"$\" + nf0(v) } },\n yAxis: { type: \"category\", data: cats.map(r => r.lbl), axisLabel: { fontSize: 10 } },\n series: [\n // series-leyenda (vacías): fijan nombre+color de la leyenda con independencia de la geometría\n { type: \"bar\", name: \"− (supuesto a la baja)\", stack: \"t\", itemStyle: { color: NEU_LO }, data: [] },\n { type: \"bar\", name: \"+ (supuesto al alza)\", stack: \"t\", itemStyle: { color: NEU_HI }, data: [] },\n { type: \"bar\", stack: \"t\", silent: true, itemStyle: { color: \"transparent\" }, tooltip: { show: false },\n data: geo.map(g => +g.minV.toFixed(2)) },\n { type: \"bar\", stack: \"t\", barWidth: 14,\n label: { show: true, position: \"left\", fontSize: 9, formatter: p => { const g = geo[p.dataIndex]; return g.leftSpan > 0.01 ? fD(g.leftDelta) : \"\"; } },\n data: geo.map(g => ({ value: +g.leftSpan.toFixed(2), itemStyle: { color: g.leftInput ? colIn(g.leftInput) : \"transparent\" } })) },\n { type: \"bar\", stack: \"t\", barWidth: 14,\n label: { show: true, position: \"right\", fontSize: 9, formatter: p => { const g = geo[p.dataIndex]; return g.rightSpan > 0.01 ? fD(g.rightDelta) : \"\"; } },\n data: geo.map(g => ({ value: +g.rightSpan.toFixed(2), itemStyle: { color: g.rightInput ? colIn(g.rightInput) : \"transparent\" } })),\n markLine: { symbol: \"none\", lineStyle: { type: \"solid\", color: TK(\"--text-1\") || \"#1f2a4e\", width: 1.5 },\n label: { formatter: `VaR base ${fMM(a.base)}`, fontSize: 10, position: \"end\", distance: 4 },\n data: [{ xAxis: +a.base.toFixed(2) }] } },\n ],\n });\n // TR — curva VaR vs ρ (eje ajustado a datos; límite como anotación fuera de escala — X-4)\n const rho = a.rows.find(r => r.id === \"rho\");\n const pts = [[15, rho.lo], [25, a.base], [35, rho.hi]];\n mkChart(\"chSN_TR\", {\n grid: { left: 56, right: 24, top: 26, bottom: 34 },\n tooltip: { trigger: \"axis\", formatter: ps => ps.map(p => `ρ = ${p.value[0]}%${p.value[0] === 25 ? \" (base)\" : \"\"}: ${fMM(p.value[1])}`).join(\"
\") },\n xAxis: { type: \"value\", min: 10, max: 40, name: \"ρ (%)\", nameLocation: \"middle\", nameGap: 22, nameTextStyle: { fontSize: 9 }, axisLabel: { fontSize: 10, formatter: v => v + \"%\" } },\n yAxis: { type: \"value\", min: Math.floor(rho.lo - 6), max: Math.ceil(rho.hi + 8), name: \"VaR (DOP MM)\", axisLabel: { fontSize: 9, formatter: v => \"$\" + nf0(v) } },\n series: [{\n type: \"line\", data: pts.map(p => [p[0], +p[1].toFixed(2)]), lineStyle: { color: TK(\"--primary\"), width: 2 },\n symbolSize: (v, p) => p.data[0] === 25 ? 12 : 8,\n itemStyle: { color: p => p.data[0] === 25 ? (TK(\"--text-1\") || \"#1f2a4e\") : TK(\"--primary\") },\n label: { show: true, fontSize: 9, position: \"top\", formatter: p => p.data[0] === 25 ? `base · ${fMM(p.data[1])}` : fMM(p.data[1]) },\n }],\n });\n // BL — Δ contribución Euler por rating del supuesto/extremo seleccionado\n const selRow = sensSelRow(a), ext = sensExtSel(selRow);\n const dr = sensDeltaByRating(selRow, ext);\n mkChart(\"chSN_BL\", {\n grid: { left: 64, right: 16, top: 14, bottom: 30 },\n tooltip: { trigger: \"axis\", formatter: ps => ps.map(p => `${p.name}: ${(p.value >= 0 ? \"+\" : \"−\") + fMM(Math.abs(p.value)).slice(1)}`).join(\"
\") },\n xAxis: { type: \"category\", data: dr.map(x => x.r), axisLabel: { fontSize: 10 } },\n yAxis: { type: \"value\", axisLabel: { fontSize: 9, formatter: v => (v < 0 ? \"−\" : \"\") + \"$\" + nf0(Math.abs(v)) } },\n series: [{ type: \"bar\", barWidth: \"50%\", itemStyle: { color: TK(\"--primary\") },\n label: { show: true, position: dr[0].v >= 0 ? \"top\" : \"bottom\", fontSize: 9, formatter: p => (p.value >= 0 ? \"+\" : \"−\") + fMM(Math.abs(p.value)).slice(1) },\n data: dr.map(x => +x.v.toFixed(2)) }],\n });\n }\n\n // ====== Visión General (§11) — overview ejecutivo; medida PINNEADA a VaR 99%·1a (no sigue al selector, patrón §14) ======\n const pinVaR = fn => { const m = S.medida; S.medida = \"VaR\"; try { return fn(); } finally { S.medida = m; } };\n // Comparabilidad de cortes = CONDICIÓN DE DATOS (FR.prevComparable); \"Error parcial\" solo la simula rota (X-2)\n const ovComparable = () => S.uiState !== \"partial\" && D.FR.prevComparable;\n const OV_TT_COMP = \"Corte anterior calculado bajo otro supuesto (S&P · ρ=20%) — un Δ jamás mezcla efecto de cartera con efecto metodológico (§2).\";\n const ovND = () => `N/D`;\n const OV_TT_VAR = \"Medida fija del overview: VaR — 99% · 1 año (metodología oficial). No sigue al selector de medida de otras secciones.\";\n const OV_TT_GRAN = \"El marginal es salida directa del modelo por posición — no es emisor-específico (§2).\";\n const ovBanner = `

Corte anterior no comparable — supuesto distinto.\n El corte anterior fue calculado bajo otro supuesto (S&P · ρ=20%): todos los Δ vs. corte anterior de esta pantalla pasan a N/D — un Δ jamás mezcla efecto de cartera con efecto metodológico (§2 auditable). Los niveles del corte vigente y sus límites sobreviven.

`;\n function ovEmisores(prev = false) {\n const getVal = prev ? dopPrev : dop; // cartera completa, sin filtro de moneda (el overview ignora S.moneda)\n const m = new Map();\n D.positions.forEach(p => m.set(p.emisor, (m.get(p.emisor) || 0) + getVal(p)));\n const t = [...m.values()].reduce((a, b) => a + b, 0);\n return [...m.entries()].map(([e, vm]) => ({ e, vm, pct: t > 0 ? vm / t * 100 : 0 })).sort((a, b) => b.vm - a.vm);\n }\n const ovHHI = rows => rows.reduce((a, r) => a + Math.pow(r.pct / 100, 2), 0);\n const OV_GRUPOS = [\"AAA\", \"AA\", \"A\", \"BBB\", \"BB\", \"B\", \"CCC–D\"];\n const ovEstado = uso => uso > 100 ? [\"err\", \"Incumplimiento\"] : uso >= 90 ? [\"warn\", \"Advertencia\"] : [\"ok\", \"Ok\"];\n function ovCard(title, big, sub, rows) {\n return `

${title}

${big}

\n ${sub ? `

${sub}

` : \"\"}\n ${rows && rows.length ? `

` + rows.map(r => `

${r[0]}${r[1]}

`).join(\"\") + `

` : \"\"}

`;\n }\n function ovNavCard(go, label, big, sub, extra) {\n return ``;\n }\n function ovNavCards(nd) {\n const comp = !nd && ovComparable();\n let d = null;\n if (!nd) {\n const a = frAgg(), ap = frAgg(true);\n const vmTot = D.positions.reduce((s, p) => s + dop(p), 0);\n const vmPrev = D.positions.reduce((s, p) => s + dopPrev(p), 0);\n const em = ovEmisores();\n const hhi = ovHHI(em);\n const topR = [...a.rows].sort((x, y) => y.contrib - x.contrib)[0];\n const topPos = pinVaR(() => [...mgRows()].sort((x, y) => y.comp - x.comp)[0]);\n const topF = FR_FACTORES.map(([f, lbl]) => ({ f, lbl, v: a.fact[f] })).sort((x, y) => y.v - x.v)[0];\n const sa = sensAgg();\n const w = btWin();\n const usoH = hhi / D.LIMITES.hhiInterno * 100;\n const stH = ovEstado(usoH);\n const dVM = vmTot - vmPrev, dVMp = vmPrev > 0 ? dVM / vmPrev * 100 : null;\n d = { a, vmTot, dVM, dVMp, hhi, stH, topR, topPos, topF, sa, w };\n }\n const ND = `N/D`;\n return `

` +\n ovNavCard(\"portafolio/global\", \"Portafolio\",\n nd ? ND : (comp ? `${d.dVM >= 0 ? \"+\" : \"−\"}${fMM(Math.abs(d.dVM)).slice(1)} (${d.dVMp >= 0 ? \"+\" : \"\"}${nf1.format(d.dVMp)}%)` : ovND()),\n \"Δ VM vs corte anterior · DOP\") +\n ovNavCard(\"portafolio/concentracion\", \"Concentración\",\n nd ? ND : `${fH(d.hhi)} ${d.stH[1]}`,\n `HHI por emisor · límite interno ${nd ? \"0.1800\" : fH(D.LIMITES.hhiInterno)}`) +\n ovNavCard(\"metricas-de-riesgo/a-la-fecha\", \"Métricas de Riesgo\",\n nd ? ND : `${d.topR.r} · ${fMM(d.topR.contrib)}`,\n `Rating de mayor aporte — VaR total del rating, DOP ⓘ`) +\n ovNavCard(\"marginal/global\", \"Marginal\",\n nd ? ND : `${esc(d.topPos.p.inst)} · ${fMM(d.topPos.comp)}`,\n `Mayor contribución (componental) — por posición, no emisor-específico ⓘ`) +\n ovNavCard(\"escenarios/impacto-en-riesgo\", \"Escenarios\",\n `Simulador de estrés`,\n \"Configura un shock y aplícalo — resultados efímeros por sesión, sin último run\") +\n ovNavCard(\"factores-de-riesgo/mapa-de-factores\", \"Factores de Riesgo\",\n nd ? ND : `${d.topF.lbl} · ${fPct(d.topF.v / d.a.total * 100, 1)}`,\n `Factor dominante — % de contribución al VaR (Euler) ⓘ`) +\n ovNavCard(\"sensibilidades/supuestos\", \"Sensibilidades\",\n nd ? ND : `${esc(d.sa.rows[0].lbl)} · ${fMM(Math.abs(d.sa.rows[0].dMax))}`,\n \"Supuesto más influyente — |ΔVaR máx| del barrido, DOP\",\n nd ? \"\" : `vs corte anterior: ${comp ? esc(D.SENS.prevInfluyente) : \"N/D\"}`) +\n ovNavCard(\"backtesting/resumen-excepciones\", \"Backtesting\",\n nd ? ND : `Excepciones: ${d.w.excVal.length} en ${d.w.n} cortes`,\n nd ? \"Kupiec: N/D\" : `esperadas ~${nf1.format(d.w.n * 0.01)} al 99% en ${d.w.n} · Kupiec: N/D — ventana incompleta (${d.w.n}/250)`) +\n `

`;\n }\n function visionHtml() {\n if (S.uiState === \"loading\")\n return `

${`

`.repeat(4)}

${`

`.repeat(3)}

${`

`.repeat(8)}

`;\n if (S.uiState === \"empty\" || S.uiState === \"error\") {\n const box = S.uiState === \"empty\" ? emptyBox() : errBox();\n const cardsND = [\n ovCard(\"Portafolio\", \"N/D\", subtituloConsolidacion(), []),\n ovCard(\"Composición por Calificación\", \"N/D\", \"VM (DOP) · % del portafolio\", []),\n ovCard(\"Exposición por Tipo de Instrumento\", \"N/D\", \"VM (DOP) · % del portafolio\", []),\n ovCard(`VaR de Crédito Total — 99% · 1 año ⓘ`, \"N/D\", \"Sin datos del corte\", []),\n ].join(\"\");\n return `

${cardsND}

${box}

\n ${ovNavCards(true)}

`;\n }\n const comp = ovComparable();\n const a = frAgg(), ap = frAgg(true);\n const vmTot = D.positions.reduce((s, p) => s + dop(p), 0);\n const nEmis = new Set(D.positions.map(p => p.emisor)).size;\n const byR = new Map();\n D.positions.forEach(p => byR.set(p.rating, (byR.get(p.rating) || 0) + dop(p)));\n const pred = [...byR.entries()].sort((x, y) => y[1] - x[1])[0];\n const usd = D.positions.filter(p => p.moneda === \"USD\").reduce((s, p) => s + dop(p), 0);\n const byT = new Map();\n D.positions.forEach(p => byT.set(p.tipo, (byT.get(p.tipo) || 0) + dop(p)));\n const dV = a.total - ap.total, dVp = ap.total > 0 ? dV / ap.total * 100 : null;\n const usoV = a.total / D.LIM_MEDIDA.VaR * 100, stV = ovEstado(usoV);\n const card1 = ovCard(\"Portafolio\", fMM(vmTot), subtituloConsolidacion(), [\n [\"Posiciones\", String(D.positions.length)],\n [\"Emisores\", String(nEmis)],\n [`Calificación predominante ⓘ`, `${pred[0]} · ${fPct(pred[1] / vmTot * 100, 1)}`],\n [\"Exposición en USD (equiv. DOP)\", `${fMM(usd)} · ${fPct(usd / vmTot * 100, 1)}`],\n ]);\n const card2 = ovCard(\"Composición por Calificación\", \" \", \"VM (DOP) · % del portafolio — rating agrupado a letra\",\n OV_GRUPOS.map(g => {\n const v = g === \"CCC–D\" ? 0 : (byR.get(g) || 0);\n if (v === 0 && !byR.has(g))\n return [g, `— · Sin posiciones`];\n return [g, `${fMM(v)} · ${fPct(v / vmTot * 100, 1)}`];\n }));\n const card3 = ovCard(\"Exposición por Tipo de Instrumento\", \" \", \"VM (DOP) · % del portafolio — dominio de la capa de datos\",\n D.TIPOS.map(t => [t, `${fMM(byT.get(t) || 0)} · ${fPct((byT.get(t) || 0) / vmTot * 100, 1)}`]));\n const card4 = ovCard(`VaR de Crédito Total — 99% · 1 año ⓘ`, fMM(a.total),\n `${stV[1]} vs. límite interno ${fMM(D.LIM_MEDIDA.VaR)}`, [\n [\"% VM\", fPct(a.total / vmTot * 100)],\n [`% Patrimonio ⓘ`, \"N/D\"],\n [\"Δ% vs corte anterior\", comp ? `${dVp >= 0 ? \"+\" : \"\"}${nf1.format(dVp)}%` : ovND()],\n ]);\n const em = ovEmisores();\n const hhi = ovHHI(em);\n const usoH = hhi / D.LIMITES.hhiInterno * 100, stH = ovEstado(usoH);\n const usoE = em[0].pct / D.LIMITES.emisorPctInterno * 100, stE = ovEstado(usoE);\n const maxMarg = pinVaR(() => Math.max(...mgRows().map(x => x.marg)));\n const usoM = maxMarg / D.MG_LIMITS.VaR.hyp * 100, stM = ovEstado(usoM);\n const limRows = [\n [`VaR de Crédito Total — 99% · 1 año ⓘ`, fMM(a.total), fMM(D.LIM_MEDIDA.VaR), usoV, stV],\n [\"Concentración HHI (por emisor)\", fH(hhi), fH(D.LIMITES.hhiInterno), usoH, stH],\n [`Mayor emisor (% del VM) ⓘ`, fPct(em[0].pct), fPct(D.LIMITES.emisorPctInterno), usoE, stE],\n [`Riesgo marginal por posición (VaR) ⓘ`, fMM(maxMarg), fMM(D.MG_LIMITS.VaR.hyp), usoM, stM],\n ];\n const tabla = `

Límites y Métricas

\n \n ${limRows.map(r => ``).join(\"\")}

Métrica	Valor	Lím. Interno	Lím. Reg. ⓘ	Uso	Estado
${r[0]}	${r[1]}	${r[2]}	N/D	${fPct(r[3], 1)}	${r[4][1]}

`;\n const drivers = `

Top Drivers del VaR — contribución prorrateada por emisor

Ranking de exposición ponderada por el riesgo de su rating — VaR 99% · 1a, nivel rating

${LEYENDA_PRORRATEO}

`;\n const variacion = comp\n ? `

Variación vs corte anterior — Δ VaR (99% · 1a) por rating

Δ en DOP (MM), etiquetas Δ% — neutro; eje primario rating (§2).

`\n : `

Variación vs corte anterior — Δ VaR (99% · 1a) por rating

ⓘN/D — cortes no comparables\n ${OV_TT_COMP} Ver el banner superior.

`;\n return `

${comp ? \"\" : ovBanner}\n

${card1}${card2}${card3}${card4}

${tabla}${drivers}${variacion}

\n ${ovNavCards(false)}

`;\n }\n function chartsOv() {\n const top = pinVaR(() => mrEmisores()).slice(0, 5).reverse();\n mkChart(\"chOV_DRV\", {\n grid: { left: 130, right: 60, top: 10, bottom: 10 },\n tooltip: { trigger: \"axis\", valueFormatter: v => fMM(v) },\n xAxis: { type: \"value\", axisLabel: { show: false }, splitLine: { show: false } },\n yAxis: { type: \"category\", data: top.map(t => t[0]), axisLabel: { fontSize: 10 } },\n series: [{ type: \"bar\", barWidth: 16, color: TK(\"--primary\"),\n label: { show: true, position: \"right\", fontSize: 9.5, color: TK(\"--text-2\"), formatter: p => fMM(top[p.dataIndex][1]) },\n data: top.map(t => +t[1].toFixed(2)) }],\n });\n if (!ovComparable())\n return;\n const a = frAgg(), ap = frAgg(true);\n const items = a.rows.map(x => {\n const prev = ap.rows.find(y => y.r === x.r);\n const dd = x.contrib - (prev ? prev.contrib : 0);\n return { k: x.r, d: dd, dp: prev && prev.contrib > 0 ? dd / prev.contrib * 100 : null };\n });\n items.push({ k: \"Total\", d: a.total - ap.total, dp: ap.total > 0 ? (a.total - ap.total) / ap.total * 100 : null });\n mkChart(\"chOV_VAR\", {\n grid: { left: 56, right: 12, top: 26, bottom: 34 },\n tooltip: { trigger: \"axis\", valueFormatter: v => (v >= 0 ? \"+\" : \"−\") + fMM(Math.abs(v)).slice(1) },\n xAxis: { type: \"category\", data: items.map(i => i.k), axisLabel: { fontSize: 9.5 } },\n yAxis: { type: \"value\", axisLabel: { formatter: v => (v < 0 ? \"−\" : \"\") + \"$\" + nf1.format(Math.abs(v)) + \"MM\", fontSize: 9.5 } },\n series: [{ type: \"bar\", barWidth: 18,\n itemStyle: { color: p => items[p.dataIndex].k === \"Total\" ? TK(\"--secondary\") : TK(\"--primary\") },\n label: { show: true, position: \"top\", fontSize: 9, color: TK(\"--text-2\"),\n formatter: p => items[p.dataIndex].dp === null ? \"\" : (items[p.dataIndex].dp >= 0 ? \"+\" : \"\") + nf1.format(items[p.dataIndex].dp) + \"%\" },\n data: items.map(i => +i.d.toFixed(2)) }],\n });\n }\n\n function bindBody(section, tab) {\n document.querySelectorAll(\"[data-retry]\").forEach(b => b.onclick = () => { S.uiState = \"ok\"; render(); });\n document.querySelectorAll(\"[data-go]\").forEach(b => b.onclick = () => { const [s, t] = b.dataset.go.split(\"/\"); nav(s, t); });\n document.querySelectorAll(\"[data-export]\").forEach(b => b.onclick = () => exportCSV(b.dataset.export));\n if (S.uiState === \"loading\" || S.uiState === \"empty\" || S.uiState === \"error\") return;\n if (section.id === \"vision-general\") { chartsOv(); return; }\n if (section.id === \"metricas-de-riesgo\") {\n if (tab.id === \"a-la-fecha\") {\n const sd = $(\"#selMrDona\"); if (sd) sd.onchange = e => { S.mrDona = e.target.value; render(); };\n document.querySelectorAll(\"tr.grp[data-mrf]\").forEach(r => r.onclick = () => { S.mrExp[r.dataset.mrf] = !S.mrExp[r.dataset.mrf]; render(); });\n chartsMRFecha();\n } else {\n const sb = $(\"#selMrBL\"); if (sb) sb.onchange = e => { S.mrBL = e.target.value; render(); };\n document.querySelectorAll(\"tr.grp[data-mrh]\").forEach(r => r.onclick = () => { S.mrExpH[r.dataset.mrh] = !S.mrExpH[r.dataset.mrh]; render(); });\n chartsMRHist();\n }\n return;\n }\n if (section.id === \"marginal\") {\n const sd = $(\"#selMgDona\"); if (sd) sd.onchange = e => { S.mgDona = e.target.value; render(); };\n document.querySelectorAll(\"tr.grp[data-mgr]\").forEach(r => r.onclick = () => { S.mgExp[r.dataset.mgr] = !S.mgExp[r.dataset.mgr]; render(); });\n document.querySelectorAll(\"tr.child[data-mge]\").forEach(r => r.onclick = () => { S.mgExpE[r.dataset.mge] = !S.mgExpE[r.dataset.mge]; render(); });\n chartsMarginal();\n return;\n }\n if (section.id === \"factores-de-riesgo\") {\n document.querySelectorAll(\"[data-frr]\").forEach(b => b.onclick = () => { S.frRating = b.dataset.frr; render(); });\n document.querySelectorAll(\"tr.grp[data-frf]\").forEach(r => r.onclick = () => { S.frExp[r.dataset.frf] = !S.frExp[r.dataset.frf]; render(); });\n chartsFr();\n return;\n }\n if (section.id === \"sensibilidades\") {\n const ss = $(\"#selSens\"); if (ss) ss.onchange = e => { S.sensSel = e.target.value; S.sensExt = null; render(); };\n document.querySelectorAll(\"[data-sext]\").forEach(b => b.onclick = () => { S.sensExt = b.dataset.sext; render(); });\n document.querySelectorAll(\"tr.grp[data-sw]\").forEach(r => r.onclick = () => { S.sensExp[r.dataset.sw] = !S.sensExp[r.dataset.sw]; render(); });\n document.querySelectorAll(\"[data-goesc]\").forEach(a => a.onclick = e => { e.preventDefault(); nav(\"escenarios\", \"impacto-en-riesgo\"); });\n if (S.uiState !== \"partial\") chartsSens();\n return;\n }\n if (section.id === \"backtesting\") {\n document.querySelectorAll(\"[data-btq]\").forEach(b => b.onclick = () => { S.btQ = b.dataset.btq; render(); });\n chartsBt();\n return;\n }\n if (section.id !== \"portafolio\") return;\n if (tab.id === \"global\") {\n const sd = $(\"#selDona\"); if (sd) sd.onchange = e => { S.donaVista = e.target.value; render(); };\n const sb = $(\"#selBL\"); if (sb) sb.onchange = e => { S.blVista = e.target.value; render(); };\n document.querySelectorAll(\"tr.grp\").forEach(r => r.onclick = () => { S.expanded[r.dataset.rat] = !S.expanded[r.dataset.rat]; render(); });\n chartsGlobal();\n } else {\n document.querySelectorAll(\"[data-tl]\").forEach(b => b.onclick = () => { S.concTL = b.dataset.tl; render(); });\n document.querySelectorAll(\"[data-tr]\").forEach(b => b.onclick = () => { S.concTR = b.dataset.tr; render(); });\n chartsConc();\n }\n }\n\n // ---------- Panel de filtros (orden inviolable del contrato) ----------\n function renderFilters() {\n const host = $(\"#filters\");\n if (!S.filtersOpen) { host.innerHTML = \"\"; return; }\n host.innerHTML = `

Filtros

Fecha de corte

Portafolio

Dataset

Calificación

Emisor

Tipo de instrumento

Seniority

Moneda\n ${[\"metricas-de-riesgo\", \"marginal\", \"factores-de-riesgo\", \"sensibilidades\"].includes(parseHash().section.id)\n ? `${[\"Todas\", \"DOP\", \"USD\"].map(m => ``).join(\"\")}\n

No aplica en esta sección: las medidas se calculan sobre la cartera consolidada completa (el ${[\"factores-de-riesgo\", \"sensibilidades\"].includes(parseHash().section.id) ? \"VaR\" : S.medida} no es aditivo entre monedas${parseHash().section.id === \"marginal\" ? \"; el marginal leave-one-out se define contra la cartera completa\" : parseHash().section.id === \"factores-de-riesgo\" ? \"; la atribución por factor opera sobre el VaR consolidado y jamás se parte por moneda\" : parseHash().section.id === \"sensibilidades\" ? \"; los barridos se computan sobre el VaR consolidado y jamás se parten por moneda\" : \"\"}).

`\n : `${[\"Todas\", \"DOP\", \"USD\"].map(m => ``).join(\"\")}`}

Vista por\n

Dimensión de agregación (no es filtro) — sincronizada con el selector del gráfico de composición.

Dominios autoritativos: los valores válidos provienen de la capa de datos (mock: declarados del contrato backend). Controles no interactivos en esta iteración salvo Moneda y Vista por.

`;\n $(\"#fOverlay\").onclick = () => { S.filtersOpen = false; renderFilters(); };\n host.querySelectorAll(\"[data-mon]\").forEach(b => b.onclick = () => { S.moneda = b.dataset.mon; render(); S.filtersOpen = true; renderFilters(); });\n const fv = $(\"#fVista\"); if (fv) fv.onchange = e => { S.donaVista = e.target.value; render(); S.filtersOpen = true; renderFilters(); };\n }\n\n // ---------- Switcher de estado del prototipo ----------\n const STATES = [[\"ok\", \"Éxito\"], [\"loading\", \"Cargando\"], [\"empty\", \"Vacío\"], [\"error\", \"Error\"], [\"partial\", \"Error parcial\"]];\n function renderSwitch() {\n $(\"#protoSwitch\").innerHTML = `

Estado del prototipo

` +\n STATES.map(([k, l]) => ``).join(\"\") + `

`;\n document.querySelectorAll(\"[data-st]\").forEach(b => b.onclick = () => { S.uiState = b.dataset.st; render(); });\n }\n\n window.addEventListener(\"hashchange\", render);\n window.addEventListener(\"resize\", () => charts.forEach(c => c.resize()));\n if (!location.hash) location.hash = \"#/vision-general\";\n render();\n})();\n",[163],"pulls","branches","forks","envVars",{"_177":62,"_179":62},"connections",{"_177":62,"_178":62},"count","unfilledCount","emptyCount",{"_42":162,"_32":163,"_30":164,"_132":-5,"_40":41,"_39":165,"_133":25,"_37":198,"_13":167,"_33":159,"_34":168,"_24":25,"_136":-5,"_186":199,"_27":200},{"_42":153,"_32":154,"_30":155,"_132":-5,"_40":41,"_39":156,"_133":25,"_37":195,"_13":158,"_33":159,"_34":160,"_24":25,"_136":-5,"_186":196,"_27":197},{"_42":145,"_32":146,"_30":147,"_132":-5,"_40":41,"_39":148,"_133":58,"_37":192,"_13":150,"_33":20,"_34":151,"_24":25,"_136":-5,"_186":193,"_27":194},{"_42":138,"_32":139,"_30":56,"_132":-5,"_40":41,"_39":140,"_133":58,"_37":189,"_13":62,"_33":142,"_34":143,"_24":25,"_136":-5,"_186":190,"_27":191},{"_42":131,"_32":28,"_30":31,"_132":-5,"_40":41,"_39":14,"_133":25,"_37":185,"_13":135,"_33":20,"_34":36,"_24":25,"_136":-5,"_186":187,"_27":188},["D",1787334387634],"children",[],[28],["D",1787326725014],[],[139],["D",1787327075110],[],[146],["D",1787334356848],[],[154],["D",1787333595841],[],[163],["D",1787326658800],{"_96":95,"_103":99},{"_96":95,"_97":-5,"_98":99,"_18":54,"_100":101,"_102":25},{"_13":85,"_32":86,"_42":41,"_87":43,"_88":-5,"_89":-5,"_90":-5,"_91":-5,"_92":-5,"_93":44,"_94":95},"ctx",{"_78":-5,"_123":238,"_239":240,"_241":242,"_243":25,"_244":25,"_245":25,"_246":58,"_247":-5,"_248":-7,"_249":-7,"_250":62,"_251":25,"_252":25,"_253":-5,"_254":25,"_255":25,"_256":25,"_257":-5},"ENV",{"_209":210,"_211":212,"_213":86,"_214":215,"_216":217,"_218":219,"_220":221,"_222":223,"_224":225,"_226":227,"_228":229,"_230":231,"_232":233,"_234":235,"_236":237},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","e87eb04e707cf64e7e532c8e8ec395f209e17f15","RENDER_GIT_BRANCH","POSTHOG_API_TOKEN","phc_nmoyuAkStEZuUp69rYlg1DZgrIt19Gx0Y4Hwf8tGgJP","POSTHOG_API_HOST","https://wart.val.town","WEB_API_TEMPLATE","https://{val}.web.val.run","APP_URL","https://www.val.town","MODULE_URL","https://esm.town","VANITY_WEB_API_TEMPLATE","https://{label}.val.run/","DENOLS_URL","https://lsp.val.town","NODE_ENV","production","CLOUDFLARE_TURNSTILE_SITE_KEY","0x4AAAAAACtaIZJH7s9rBMZ6","GOOGLE_CLIENT_ID","875989696899-jtsqkhlbdv5jrlsk8631p7ipjg3c6o62.apps.googleusercontent.com","STRIPE_PUBLISHABLE_KEY","pk_live_51N2zvWEpZTTLipIkVEwXrUG9AT0yeOOEYxszarZT1jpsZV58Ly6wlg3SltZpHN26CUalOBmUSY7adQRQiSkCZz2500qSXNkf8Y","API_URL","https://api.val.town",[],"preferencesKeybindings","default","preferencesTheme","light","preferencesFixers","preferencesCopilot","preferencesSelectionAi","preferencesCloseBrackets","preferencesChatPanelState","preferencesDprint","preferencesDenofmt","notificationCount","flagDenols","isBusinessOrgMember","businessOrgHandle","isBusinessOrgAdmin","isHigherTownieTier","navCollapsed","currentOrgId"]

${title}

Valor de Mercado por Calificación

Composición del Portafolio

Cambio en la Composición

Tabla de Composición

Top Emisores

Evolución de la Concentración

Cambio en la Composición por Emisor

Tabla de Concentración por Emisor

${S.medida} por Calificación

Contribución al ${S.medida}

Standalone vs. Contribución por Calificación

Descomposición del ${S.medida}

Evolución del ${S.medida} por Calificación

Evolución de la Razón ${S.medida}/VM

Cambio del ${S.medida} vs. Corte Anterior

Comparativa por Calificación

Iso-risk: ${S.medida} marginal vs. tamaño

Contribución (componental)

Ranking por ${S.medida} marginal

Detalle por posición

Serie de excepciones ⓘ

Convergencia del estimador MC ⓘ

Excepciones del VaR — 99% · 1 año (DOP consolidado)

Validación estadística ⓘ

Kupiec POF

Christoffersen (conjunto: independencia + cobertura)

Semáforo de Basilea

Contribución por factor — Atribución Euler (VaR, DOP MM)

Umbrales de Merton — variable latente

Matriz ρ asumida (correlación de activos)

Contribución al VaR — 99% · 1 año (DOP consolidado)

Tornado de supuestos — impacto en el VaR 99%·1a (DOP MM)

Curva VaR vs ρ — 99% · 1 año

Δ de contribución Euler por calificación — ${esc(selRow.lbl)}

Sensibilidad del VaR — 99% · 1 año (DOP consolidado)

${title}

${label}

Límites y Métricas

Top Drivers del VaR — contribución prorrateada por emisor

Variación vs corte anterior — Δ VaR (99% · 1a) por rating

Variación vs corte anterior — Δ VaR (99% · 1a) por rating

Filtros

Diff · v89