Remove lookahead from historical replay

README.md

@@ -39,6 +39,12 @@ price is known, grades it at least 12 hours later, and combines that broad marke
 calibration with each agent's personal outcomes. This expands the learning sample
 without backfilling future information into old decisions.
 
+The initial seven-day chart seed is an approximate replay, not a live return.
+It uses only prices available on each simulated date, computes daily and weekly
+changes from those historical prices, disables unavailable hourly reversal data,
+and labels the combined number as legacy/replay. Engine-version returns are the
+clean live comparison.
+
 Paper accounts created with a password are also saved through the backend, so a
 user can log in from another device and see the same paper portfolio, activity,
 and value history. Passwordless paper accounts remain local-only.

index.html

@@ -425,7 +425,7 @@ footer{margin-top:34px;padding-top:22px;border-top:1px solid var(--border);color
       <div class="card-h"><h3>Returns — all agents</h3><div><span class="small muted">$10,000 start each</span><div class="rangebar" data-chart-ranges></div></div></div>
       <div class="chart-wrap"><svg id="chart2" viewBox="0 0 960 320" preserveAspectRatio="xMidYMid meet"></svg></div>
       <div class="legend" id="comboLegend2"></div>
-      <div class="small muted" style="margin-top:10px">Past week is a backtest. After that, each live cycle adds another return snapshot for every agent.</div>
+      <div class="small muted" style="margin-top:10px">The initial week is an approximate historical replay using prices available on each day and current liquidity as a proxy. The v36 return starts from live cycles only.</div>
     </div>
   </section>
 
@@ -2195,7 +2195,7 @@ function agentMomentumStats(p){
    so the equity curves show a plausible past week instead of a flat line. */
 function lastNDates(n){const out=[];const now=new Date();for(let i=n-1;i>=0;i--){const x=new Date(now);x.setUTCDate(now.getUTCDate()-i);out.push(x.toISOString().slice(0,10));}return out;}
 async function fetchPriceHistory(tokenId){
-  try{const r=await fetch(`${CLOB}/prices-history?market=${tokenId}&interval=1w&fidelity=1440`);
+  try{const r=await fetch(`${CLOB}/prices-history?market=${tokenId}&interval=1m&fidelity=1440`);
     if(!r.ok)return null;const d=await r.json();const map={};
     (d.history||[]).forEach(h=>{map[new Date(h.t*1000).toISOString().slice(0,10)]=h.p;});
     return Object.keys(map).length?map:null;}catch(e){return null;}
@@ -2207,14 +2207,23 @@ async function fetchClobTokens(marketId){
 function priceOnDay(map,day,fallback){
   if(!map)return fallback;let best=null,bd=null;
   for(const dt in map){if(dt<=day&&(bd===null||dt>bd)){bd=dt;best=map[dt];}}
-  if(best!=null)return best;
-  const ks=Object.keys(map).sort();return ks.length?map[ks[0]]:fallback;
+  return best!=null?best:fallback;
+}
+function offsetIsoDay(day,delta){
+  const d=new Date(`${day}T00:00:00Z`);d.setUTCDate(d.getUTCDate()+delta);return d.toISOString().slice(0,10);
+}
+function historicalPriceFeatures(map,day,currentPrice){
+  const current=Number(currentPrice),previous=priceOnDay(map,offsetIsoDay(day,-1),null),week=priceOnDay(map,offsetIsoDay(day,-7),null);
+  return {price_change_1h:0,
+    price_change_1d:Number.isFinite(previous)?+(current-previous).toFixed(4):0,
+    price_change_1w:Number.isFinite(week)?+(current-week).toFixed(4):0};
 }
 /* Full day-by-day backtest: for each of the past 7 days, rebuild each sampled market's
    state from that day's real price (+ correct time-to-resolution), re-run the
    scoring engine, and step every strategy agent through a day of trading.
    NOTE: volume/liquidity signals use current values as a proxy — Polymarket
-   does not expose historical volume. Price & timing are truly historical. */
+   does not expose historical volume. Daily and weekly price changes use only
+   prices available by the simulated day; hourly reversal signals stay disabled. */
 async function backtestWeek(st){
   const dates=lastNDates(7), start=dates[0];
   AGENTS.forEach(a=>{st.agents[a.id]=defaultPortfolio();});
@@ -2233,7 +2242,7 @@ async function backtestWeek(st){
       if(yp==null||yp<=0.02||yp>=0.98)continue;
       const dtr=m.end_date?(new Date(m.end_date)-new Date(day+"T12:00:00Z"))/86400000:null;
       if(dtr!=null&&dtr<-0.5)continue;
-      snaps.push(Object.assign({},m,{yes_price:+yp.toFixed(4),no_price:+(1-yp).toFixed(4),days_to_resolution:dtr}));
+      snaps.push(Object.assign({},m,historicalPriceFeatures(hist[m.id],day,yp),{yes_price:+yp.toFixed(4),no_price:+(1-yp).toFixed(4),days_to_resolution:dtr}));
     }
     const sugs=generateSuggestions(snaps);
     const priceMap={}; snaps.forEach(s=>priceMap[s.id]={yes_price:s.yes_price,no_price:s.no_price});
@@ -2390,7 +2399,7 @@ function renderOverview(){
   const stats=[
     {ic:lead.c.emoji,label:"Leader",value:lead.c.name.split(" ")[0]},
     {ic:"📈",label:"Leader return",value:fmtPct(lead.ret),cls:signClass(lead.pnl)},
-    {ic:"⚖️",label:"Legacy avg",value:fmtPct(avgRet),cls:signClass(avgRet)},
+    {ic:"⚖️",label:"Legacy / replay avg",value:fmtPct(avgRet),cls:signClass(avgRet)},
     {ic:"🧪",label:`v${SUGGESTION_ENGINE_VERSION} avg`,value:fmtPct(engineAvg),cls:signClass(engineAvg)},
     {ic:"🧠",label:"Core strategy avg",value:fmtPct(coreAvg),cls:signClass(coreAvg)},
     {ic:"⚡",label:"Aggressive avg",value:fmtPct(aggressiveAvg),cls:signClass(aggressiveAvg)},
@@ -4074,6 +4083,7 @@ window.PMA_ENGINE_DIAGNOSTICS=Object.freeze({
   learnedOpportunity,
   tradeLossBudgetPct,
   boundedStakeForRisk,
+  historicalPriceFeatures,
   offlineCachePolicy,
   gainStopTargets:(entry)=>GAIN_STOP_TIERS.map(t=>gainStopTarget({entry_price:Number(entry),cost:1,shares:1,gain_stops:{}},t)),
   rules:Object.freeze({minimumPolicyHoldHours:MIN_POLICY_HOLD_HOURS,exitConfirmationHours:EXIT_CONFIRM_HOURS,maxAgentOverlap:2,materialOverlapPct:1.25,stopLossPct:18,
@@ -4145,6 +4155,10 @@ function runEngineSelfTest(){
   openPositions(rejectBook,AGENTS[0],[trend],"All",{minConv:0,maxNew:1,maxFrac:0.04,reserve:0.1,targetExposure:0.6,learning:buildAdaptiveProfile(rejectBook),marketLearning:{samples:0,pending:0,buckets:{}}},new Set(),{});
   const rejectionAccounting=Number(rejectBook.lastDecision&&rejectBook.lastDecision.rejectionCounts&&rejectBook.lastDecision.rejectionCounts.already_held||0)===1;
   const convictionCfg=AGENTS.find(a=>a.id==="conviction"),convictionCapacityCoversTarget=convictionCfg.maxPositions*MAX_AGGRESSIVE_TRADE_LOSS_PCT>=convictionCfg.targetExposure;
+  const historyFixture={"2026-01-01":0.40,"2026-01-07":0.50,"2026-01-08":0.55,"2026-01-09":0.90};
+  const historicalFeatures=historicalPriceFeatures(historyFixture,"2026-01-08",0.55);
+  const backtestNoLookahead=priceOnDay({"2026-01-09":0.90},"2026-01-08",null)===null
+    &&historicalFeatures.price_change_1h===0&&historicalFeatures.price_change_1d===0.05&&historicalFeatures.price_change_1w===0.15;
   return {version:SUGGESTION_ENGINE_VERSION,
     trend:{ready:trend.trade_ready,quality:trend.quality,side:trend.side,margin:trend.net_edge},
     noSignal:{ready:noSignal.trade_ready,quality:noSignal.quality,signal:noSignal.signal_type,margin:noSignal.net_edge},
@@ -4159,6 +4173,7 @@ function runEngineSelfTest(){
       legacyNormalizedValue:riskPos.value,equityPreserved:+equity(riskBook).toFixed(2),capsBinaryGap:aggressiveGapBudget===0.03&&riskPos.value<=300.01},
     offline:{fresh:offlineCachePolicy(30*60000),staleEntry:offlineCachePolicy(3*3600000),expired:offlineCachePolicy(25*3600000)},
     exits:{youngConflict:exitReason(young,fresh,conflict,AGENTS[0]),matureConflict:exitReason(mature,fresh,conflict,AGENTS[0]),trailing:trailingProfitReason(trailing)},
+    backtest:{noLookahead:backtestNoLookahead,features:historicalFeatures},
     overlapRemaining,immaterialRunnerDoesNotBlock,rejectionAccounting,convictionCapacityCoversTarget,rules:window.PMA_ENGINE_DIAGNOSTICS.rules};
 }
 if(new URLSearchParams(location.search).get("engine_test")==="1"){