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if(!r.ok||!r.body) throw Error('fetch '+r.status);\nconst rd=r.body.getReader(), dec=new TextDecoder(); let buf='';\nwhile(true){const {value,done}=await rd.read(); if(done)break; buf+=dec.decode(value,{stream:true}); let i;\n while((i=buf.indexOf('\\n'))>=0){const line=buf.slice(0,i);buf=buf.slice(i+1);\n if(line.includes('[BSPS_TICK] event=btc-updown-5m-')){\n const m=line.match(/^(\\S+?)\\[INFO\\].*?event=(btc-updown-5m-\\d+).*?rem_s=(\\d+).*?old_d2s=([^ ]+).*?twap_d2s=([^ ]+).*?book=U\\[([0-9.]+)\\]\\/D\\[([0-9.]+)\\].*?top10w=([+\\-0-9.]+).*?imb_delta=([+\\-0-9.]+)/);\n if(m&&Number.isFinite(N(m[4]))&&Number.isFinite(N(m[5]))){const t:Tick={slug:m[2],ts:Date.parse(m[1])/1000,rem:+m[3],old:+m[4],twap:+m[5],u:+m[6],d:+m[7],top:+m[8],imb:+m[9]};if(!ticks.has(t.slug))ticks.set(t.slug,[]);ticks.get(t.slug)!.push(t);}\n }\n if(line.includes('[Event PnL]')&&line.includes('event=btc-updown-5m-')){const m=line.match(/event=(btc-updown-5m-\\d+).*?outcome=(UP|DOWN)/);if(m)outcomes.set(m[1],m[2] as any);}\n }}\nfor(const a of ticks.values())a.sort((a,b)=>a.ts-b.ts);\nconst slugs=[...outcomes.keys()].filter(s=>ticks.has(s)).sort((a,b)=>+a.split('-').at(-1)!-+b.split('-').at(-1)!);\nconsole.log('events',slugs.length,'first',slugs[0],'last',slugs.at(-1));\n\ntype Cand={slug:string,idx:number,ts:number,rem:number,side:'UP'|'DOWN',cheap:number,cheapEff:number,oppNow:number,oppEffNow:number,currentPairCost:number,currentGap:number,pm:number,oldSide:number,twSide:number,oldMag:number,twMag:number,top:number,imb:number,futurePair:boolean,earliestSec:number,bestEdge:number,bestPairCost:number,bestSec:number,settleWin:boolean,realizedPnlEarliest:number,realizedRoiEarliest:number};\nconst cands:Cand[]=[];\nfor(const s of slugs){const a=ticks.get(s)!;const win=outcomes.get(s)!;\n for(let i=0;i270)continue;\n // sample every ~5 seconds to reduce serial duplication\n if(i>0 && (t.ts-a[i-1].ts)<4 && (Math.floor(t.ts/5)===Math.floor(a[i-1].ts/5)))continue;\n const side:'UP'|'DOWN'=t.u<=t.d?'UP':'DOWN'; const cheap=side==='UP'?t.u:t.d; const opp=side==='UP'?t.d:t.u;\n const c1=eff(cheap), c2now=eff(opp), currentPairCost=c1+c2now;\n // first-leg only: no profitable complete set at current asks\n if(currentPairCost<1)continue;\n let earliestSec=NaN,bestEdge=-Infinity,bestPairCost=Infinity,bestSec=NaN;\n for(let j=i+1;j0)earliestSec=sec;\n }\n const futurePair=Number.isFinite(earliestSec); const settleWin=side===win;\n // realistic fixed policy outcome for label: pair at FIRST positive all-in pair edge; else settle first leg\n let pnl:number,roi:number;\n if(futurePair){let oppP=NaN;for(let j=i+1;jx.futurePair);const arr=(k:(x:Cand)=>number)=>z.map(k).filter(Number.isFinite).sort((a,b)=>a-b);const med=(v:number[])=>v.length?v[Math.floor(v.length/2)]:NaN;const mean=(v:number[])=>v.length?v.reduce((a,b)=>a+b,0)/v.length:NaN;const pnl=z.reduce((a,x)=>a+x.realizedPnlEarliest,0),spent=z.reduce((a,x)=>a+x.cheapEff+(x.futurePair?(1-x.realizedPnlEarliest-x.cheapEff):0),0);return{n,pairRate:pair.length/n,settleWinRate:z.filter(x=>x.settleWin).length/n,medianEarliestSec:med(arr(x=>x.earliestSec)),medianBestEdge:med(arr(x=>x.bestEdge)),meanBestEdge:mean(arr(x=>x.bestEdge)),meanPnlPer1:z.reduce((a,x)=>a+x.realizedPnlEarliest,0)/n,meanROI:mean(arr(x=>x.realizedRoiEarliest)),aggregatePnl:pnl,aggregateROI:spent?pnl/spent:NaN};}\nconsole.log('ALL',summarize(cands));\n\n// descriptive quintiles by cheap price and rem: boundaries come from data, not strategy constants.\nfunction quantiles(vals:number[],n=5){const a=vals.slice().sort((x,y)=>x-y);return Array.from({length:n+1},(_,i)=>a[Math.min(a.length-1,Math.floor(i*(a.length-1)/n))]);}\nconst pq=quantiles(cands.map(x=>x.cheap),5), rq=quantiles(cands.map(x=>x.rem),5), gq=quantiles(cands.map(x=>x.currentGap),5);\nconsole.log('cheap quintiles',pq,'rem quintiles',rq,'gap quintiles',gq);\nfor(let b=0;b<5;b++){const lo=pq[b],hi=pq[b+1],z=cands.filter((x,i)=>x.cheap>=lo&&(b===4?x.cheap<=hi:x.cheapx.rem>=lo&&(b===4?x.rem<=hi:x.remtrainS.has(x.slug)),test=cands.filter(x=>testS.has(x.slug));console.log('split',split,slugs.length-split,'rows',train.length,test.length);\n\n// logistic model for futurePair and ridge model for realized pnl. Features are transformed current-only observables.\nfunction feat(x:Cand){const p=x.cheap;const rem=x.rem/300;const old=x.oldMag/Math.sqrt(Math.max(1,x.rem));const tw=x.twapMag/Math.sqrt(Math.max(1,x.rem));return [Math.log((p+.01)/(1-p+.01)),x.currentGap,rem,old,tw,x.top,x.imb, (x.side==='UP'?1:-1)*x.oldSide, (x.side==='UP'?1:-1)*x.twSide];}\nconst invalid=cands.filter(x=>feat(x).some(v=>!Number.isFinite(v)));console.log('invalidFeatures',invalid.length,invalid.slice(0,3).map(x=>({slug:x.slug,cheap:x.cheap,gap:x.currentGap,old:x.oldMag,tw:x.twapMag,top:x.top,imb:x.imb,feat:feat(x)})));\ntrain=train.filter(x=>feat(x).every(Number.isFinite));test=test.filter(x=>feat(x).every(Number.isFinite));console.log('finite rows',train.length,test.length);\nfunction stdfit(data:Cand[]){const X=data.map(feat),k=X[0].length,mu=Array(k).fill(0),sd=Array(k).fill(0);for(const a of X)for(let j=0;jfeat(x).map((v,j)=>(v-mu[j])/sd[j])};}\nfunction sig(z:number){return z>30?1:z<-30?0:1/(1+Math.exp(-z));}\nfunction fitLog(data:Cand[]){const st=stdfit(data),k=feat(data[0]).length,w=Array(k+1).fill(0),lr=.03,lam=.003;for(let it=0;it<3000;it++){const g=Array(k+1).fill(0);for(const x of data){const z=st.z(x);let s=w[0];for(let j=0;j{const z=st.z(x);let s=w[0];for(let j=0;jnumber){const st=stdfit(data),k=feat(data[0]).length,w=Array(k+1).fill(0),lr=.015,lam=.01;for(let it=0;it<5000;it++){const g=Array(k+1).fill(0);for(const x of data){const z=st.z(x);let yhat=w[0];for(let j=0;j{const z=st.z(x);let y=w[0];for(let j=0;jx.realizedPnlEarliest);\nfunction clsMetrics(data:Cand[]){let bs=0,ll=0;for(const x of data){const p=Math.max(.001,Math.min(.999,lm.xpred(x))),y=x.futurePair?1:0;bs+=(p-y)**2;ll+=-(y*Math.log(p)+(1-y)*Math.log(1-p));}return{brier:bs/data.length,logloss:ll/data.length};}\nfunction regMetrics(data:Cand[]){let mae=0,mse=0;for(const x of data){const e=rm.pred(x)-x.realizedPnlEarliest;mae+=Math.abs(e);mse+=e*e;}return{mae:mae/data.length,rmse:Math.sqrt(mse/data.length)};}\nconsole.log('PAIR_MODEL',clsMetrics(train),clsMetrics(test),'w',lm.w.map(x=>+x.toFixed(4)));\nconsole.log('PNL_MODEL',regMetrics(train),regMetrics(test),'w',rm.w.map(x=>+x.toFixed(4)));\n\n// score deciles on TRAIN establish a data-driven execution threshold: choose contiguous top score deciles with positive lower-ish performance.\nfor(const [name,data] of [['TRAIN',train],['TEST',test]] as const){const scored=data.map(x=>({x,score:rm.pred(x),pp:lm.xpred(x)})).sort((a,b)=>a.score-b.score);for(let d=0;d<10;d++){const lo=Math.floor(d*scored.length/10),hi=Math.floor((d+1)*scored.length/10),z=scored.slice(lo,hi).map(v=>v.x);console.log(name,'PNL_DEC',d+1,'scoreRange',[scored[lo]?.score,scored[Math.max(lo,hi-1)]?.score],summarize(z));}}\n\n// Event-level no-lookahead strategy: derive threshold from TRAIN candidate scores by testing unique score quantiles, at most one entry/event, earliest qualifying candidate.\nconst threshCands=quantiles(train.map(rm.pred),20).slice(1,-1);let best:any=null;\nfunction runStrategy(data:Cand[],thr:number){const by=new Map();for(const x of data){if(!by.has(x.slug))by.set(x.slug,[]);by.get(x.slug)!.push(x);}let trades:Cand[]=[];for(const [s,a] of by){a.sort((x,y)=>x.ts-y.ts);const hit=a.find(x=>rm.pred(x)>=thr);if(hit)trades.push(hit);}return summarize(trades);}\nfor(const th of threshCands){const sm=runStrategy(train,th);if(sm.n>=Math.max(10,Math.floor(split*.1))&&(!best||sm.aggregatePnl>best.sm.aggregatePnl))best={th,sm};}\nconsole.log('SELECTED_THRESHOLD_FROM_TRAIN',best);\nconsole.log('OOS_EVENT_STRATEGY',runStrategy(test,best.th));\n\n// Also show a non-ML empirical policy selected only from TRAIN: cheap-price quintile x rem-quintile cells, keep cells with positive train aggregate ROI and >=20 observations.\nfunction binIndex(v:number,q:number[]){for(let 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