Cluster adaptive evidence by market

README.md

@@ -15,7 +15,7 @@ https://polymarket-site-eta.vercel.app/personal.html
 
 The site fetches live Polymarket markets, generates agent suggestions, lets you
 run frequent paper cycles, and syncs the shared arena state through Neon or
-Vercel Blob. Build 50 also installs an offline app shell and caches timestamped
+Vercel Blob. Build 51 also installs an offline app shell and caches timestamped
 market snapshots. During an outage, cycles continue locally; cached entries are
 allowed for 90 minutes, older snapshots become mark-only, and all cached data
 expires after 24 hours.
@@ -27,7 +27,7 @@ The learner shrinks small samples toward neutral, caps sizing changes to
 15% of candidates for deterministic exploration so a stale regime cannot become
 permanent.
 
-Strategy 46 treats each binary stake as capable of falling to zero even when the
+Strategy 47 treats each binary stake as capable of falling to zero even when the
 18% stop cannot fill. New core positions are capped at 2.5%-4% of equity and
 aggressive positions at 3%-5%, with lower limits for near-term, extreme-price,
 reversal, and fast-moving setups. Oversized positions inherited from older
@@ -65,7 +65,7 @@ negative in all three chronological segments. Reversals averaged -3.69%, with a
 market-clustered 90% interval entirely below zero. Crypto and Sports were also
 negative but covered only three and five markets. The 24-hour cohort improved to
 -0.82% row mean and +1.31% market mean, with no rule robustly negative across all
-segments. Strategy 46 therefore keeps reversal entries observation-only until
+segments. Strategy 47 therefore keeps reversal entries observation-only until
 their recent signal and quality cohorts independently earn promotion, retains
 their signals for paper grading, and evaluates adaptation at 24 hours.
 
@@ -74,7 +74,7 @@ markets with no failures and produced 3,597 net-of-cost 24-hour outcomes across
 142 markets. No tested follow or fade rule was robustly positive. Crypto trends
 averaged -3.83% per observation and -3.99% per market; Sports trends averaged
 -5.44% and -6.61%. Both stayed negative in every chronological segment and their
-market-clustered 90% intervals were entirely below zero. Strategy 46 therefore
+market-clustered 90% intervals were entirely below zero. Strategy 47 therefore
 keeps Crypto and Sports trends observation-only while continuing to grade them.
 
 A corrected 200-market audit paged through 197 markets with usable history and
@@ -83,23 +83,23 @@ segment and averaged -4.13%. Sports trends were negative in train and test and
 averaged -3.53% at 72 hours. Politics trends were the sole cohort with positive
 row-level returns in all three 72-hour segments, but its market-cluster interval
 still crossed zero; that supports a longer hold test, not a larger entry bet.
-Strategy 46 gives Politics trend positions that 72-hour observation window before
+Strategy 47 gives Politics trend positions that 72-hour observation window before
 ordinary signal exits. Stops, profit locks, settlement handling, and risk-budget
 reductions remain immediate.
 
-Strategy 46 also subtracts a half-cent round-trip cost when grading each live
+Strategy 47 also subtracts a half-cent round-trip cost when grading each live
 walk-forward signal. Confidence uses the largest independent matching bucket,
 not the sum of five overlapping feature buckets, and evidence from older engine
 versions is down-weighted. This prevents a handful of duplicated observations
 from authorizing larger positions or hiding a modest negative regime.
 
-Strategy 46 adds uncertainty-aware promotion and demotion. A matching setup must
+Strategy 47 adds uncertainty-aware promotion and demotion. A matching setup must
 accumulate at least eight effective observations and agree across at least two
 feature views before repeatable positive evidence can increase size or repeatable
 negative evidence can block a new entry. Mixed evidence stays close to neutral
 instead of being mistaken for an edge.
 
-Build 50 enforces the documented offline boundary end to end. Cached snapshots
+Build 51 enforces the documented offline boundary end to end. Cached snapshots
 under 90 minutes old may continue paper execution. Older snapshots remain usable
 for valuation and chart snapshots for up to 24 hours, but cannot trigger entries,
 stop-losses, gain-stops, risk rebalances, settlements, or policy exits. Network
@@ -112,12 +112,12 @@ adaptive baselines, pending signal grades, and trade evidence remain in one stra
 lineage until the actual entry, sizing, or exit logic changes. Legacy build 40 and 41
 records are migrated into the same strategy lineage without losing evidence.
 
-Build 50 independently refreshes markets for matured pending signals that have
+Build 51 independently refreshes markets for matured pending signals that have
 left the current top-500 activity scan. Unavailable markets remain queued for a
 bounded retry window. This prevents activity-rank survivorship from deciding
 which wins and losses reach the adaptive calibration ledger.
 
-Strategy 46 coordinates high-risk exploration globally. Near-term, extreme-price,
+Strategy 47 coordinates high-risk exploration globally. Near-term, extreme-price,
 and other gap-prone positions may be held materially by only one agent, while
 ordinary independently confirmed markets retain the two-agent cap. The robustly
 negative Sports- and Crypto-trend cohorts cannot enter through exploration.
@@ -139,7 +139,7 @@ whole-event YES or NO bundles using executable best asks/bids, per-leg costs, an
 a minimum-liquidity requirement. The 500-event audit found 33 complete liquid
 negative-risk events and zero positive worst-case bundle returns after costs.
 Midpoint price sums sometimes looked attractive, but executable spreads removed
-the apparent edge, so Strategy 46 does not pretend those snapshots are arbitrage.
+the apparent edge, so Strategy 47 does not pretend those snapshots are arbitrage.
 
 The expanded event-clustered run loaded history for 498 of the 500 highest-volume
 resolved markets with no fetch failures. No side, price band, category, trend,
@@ -150,18 +150,24 @@ static settlement-direction boost from this audit.
 
 The earlier 200-resolved-market audit found short-dated NO entries strongly
 negative, but the 500-market rerun did not reproduce that loss in its newer test
-segment. Strategy 46 therefore treats the result as a provisional prior instead
+segment. Strategy 47 therefore treats the result as a provisional prior instead
 of a permanent ban: NO entries with 21 days or less remain observation-only until
 the recent walk-forward calibration promotes their matching side and duration
 cohorts. Exact numeric-range contracts are excluded from new entries because a
 settlement jump can pass directly through an 18% stop; the live audit found that
 this failure mode caused the largest latest-day loss.
 
-Strategy 46 also excludes path-dependent barriers such as "reach $66,000," "hit
+Strategy 47 also excludes path-dependent barriers such as "reach $66,000," "hit
 $90," and "dip to $62,000." These contracts can resolve abruptly as soon as the
 barrier is touched, so a later hourly stop cannot reliably cap the loss. Fixed-date
 level questions such as "above $66,000 on August 23" remain eligible.
 
+Strategy 47 clusters live walk-forward observations by market before calculating
+confidence. Multiple six-hour snapshots of the same contract are averaged into
+one effective market outcome, so one repeated winner or loser cannot promote or
+demote an entire feature cohort. Promotion still requires at least eight weighted
+distinct markets and agreement across two feature views.
+
 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

@@ -341,7 +341,7 @@ footer{margin-top:34px;padding-top:22px;border-top:1px solid var(--border);color
   <nav class="topnav">
     <div class="brand">
       <div class="logo">🏆</div>
-      <div><div class="brand-name">Polymarket Arena</div><div class="brand-sub">10 agents · 5 core + 5 aggressive</div><div class="build-badge">Adaptive strategy 46 · build 50</div></div>
+      <div><div class="brand-name">Polymarket Arena</div><div class="brand-sub">10 agents · 5 core + 5 aggressive</div><div class="build-badge">Adaptive strategy 47 · build 51</div></div>
     </div>
     <div class="tabs" id="tabs">
       <button class="tab" data-tab="overview">Overview</button>
@@ -363,7 +363,7 @@ footer{margin-top:34px;padding-top:22px;border-top:1px solid var(--border);color
   <div class="personal-banner" id="personalBanner">
     <b>Personal research mode.</b> This copy is for your own analysis, paper tracking, and manual trade research only. It does not pool money, onboard investors, custody funds, bypass eligibility rules, or place orders without your manual approval.
   </div>
-  <div class="live-build-banner"><b>Build 50 active:</b> Crypto and Sports trends are observation-only after a 500-market walk-forward audit found repeatable 24-hour losses. Reversal and short-dated NO signals can return only after their own recent cohorts earn promotion. Exact ranges and path-dependent "reach / hit / dip" barriers are excluded because abrupt resolution can bypass stops. This remains paper trading; profits are not guaranteed.</div>
+  <div class="live-build-banner"><b>Build 51 active:</b> adaptive evidence is clustered by market so repeated snapshots cannot promote a strategy. Crypto and Sports trends remain observation-only; reversals and short-dated NO still require recent proof, while exact ranges and path-dependent barriers remain excluded. This remains paper trading; profits are not guaranteed.</div>
 
   <!-- ============ OVERVIEW ============ -->
   <section class="tabpanel" data-tab="overview">
@@ -745,7 +745,7 @@ footer{margin-top:34px;padding-top:22px;border-top:1px solid var(--border);color
   </section>
 
   <footer>
-    Build 50 · Adaptive strategy 46 · Paper trading only · Live prices from Polymarket's public Gamma API · Not financial advice ·
+    Build 51 · Adaptive strategy 47 · Paper trading only · Live prices from Polymarket's public Gamma API · Not financial advice ·
     <a class="market-link" href="https://github.com/theodore-song/polymarket-analyst" target="_blank" rel="noopener">Source on GitHub</a>
   </footer>
 </div>
@@ -774,9 +774,9 @@ const POLITICS_TREND_MIN_HOLD_HOURS = 72;
 const EXIT_CONFIRM_HOURS = 6;
 const AGENTS_KEY = "pma_agents_v2";
 const SUG_KEY = "pma_suggestions_v5";
-const BUILD_VERSION = 50;
-const SUGGESTION_ENGINE_VERSION = 46;
-const PREVIOUS_STRATEGY_VERSION = 45;
+const BUILD_VERSION = 51;
+const SUGGESTION_ENGINE_VERSION = 47;
+const PREVIOUS_STRATEGY_VERSION = 46;
 const LEGACY_BUILD_STRATEGY_LINEAGE = Object.freeze({40:40,41:40});
 function normalizedStrategyVersion(value){
   const version=Number(value||0);
@@ -1643,7 +1643,7 @@ function summarizeLearningBucket(bucket,shrinkage){
   const pooledVariance=(priorWeight*priorVariance+weight*variance)/(priorWeight+weight||1);
   const stderr=Math.sqrt(pooledVariance/Math.max(1,weight));
   const score=Number(bucket&&bucket.sum||0)/(weight+shrinkage);
-  return {samples:Number(bucket&&bucket.count||0),weight:+weight.toFixed(2),raw:+raw.toFixed(4),
+  return {samples:Number(bucket&&bucket.count||0),observations:Number(bucket&&bucket.observations||bucket&&bucket.count||0),weight:+weight.toFixed(2),raw:+raw.toFixed(4),
     score:+score.toFixed(4),stderr:+stderr.toFixed(4),lower_bound:+(score-1.28*stderr).toFixed(4),
     upper_bound:+(score+1.28*stderr).toFixed(4),win_rate:weight?Number(bucket.wins||0)/weight:0};
 }
@@ -1693,19 +1693,34 @@ function updateSignalLedger(st,markets,suggestions){
   st.signal_ledger=ledger;return ledger;
 }
 function buildSignalCalibration(ledger){
-  const buckets={};
-  for(const outcome of (ledger&&ledger.outcomes)||[]){
+  const clusters={},outcomes=(ledger&&ledger.outcomes)||[];
+  outcomes.forEach((outcome,index)=>{
     const age=Math.max(0,Date.now()-new Date(outcome.evaluated_at||0).getTime()),version=normalizedStrategyVersion(outcome.strategy_version);
     const versionWeight=version===SUGGESTION_ENGINE_VERSION?1:(version===PREVIOUS_STRATEGY_VERSION?0.55:0.25);
     const weight=Math.exp(-age/(30*86400000))*versionWeight;
-    const ret=clamp(Number(outcome.return||0),-1,2);if(!Number.isFinite(ret))continue;
-    learningFeatures(outcome).forEach(key=>{const b=buckets[key]||(buckets[key]={weight:0,sum:0,sumSq:0,wins:0,count:0});
-      b.weight+=weight;b.sum+=ret*weight;b.sumSq+=ret*ret*weight;b.wins+=(ret>0?weight:0);b.count++;});
-  }
+    const ret=clamp(Number(outcome.return||0),-1,2);if(!Number.isFinite(ret)||weight<=0)return;
+    const marketId=String(outcome.market_id||`unidentified-observation-${index}`);
+    learningFeatures(outcome).forEach(key=>{
+      const byMarket=clusters[key]||(clusters[key]={}),cluster=byMarket[marketId]||(byMarket[marketId]={weight:0,sum:0,observations:0});
+      cluster.weight+=weight;cluster.sum+=ret*weight;cluster.observations++;
+    });
+  });
+  const buckets={};
+  Object.entries(clusters).forEach(([key,byMarket])=>{
+    const b=buckets[key]={weight:0,sum:0,sumSq:0,wins:0,count:0,observations:0};
+    Object.values(byMarket).forEach(cluster=>{
+      const clusterWeight=Math.min(1,Number(cluster.weight||0)),ret=Number(cluster.sum||0)/Math.max(0.0001,Number(cluster.weight||0));
+      b.weight+=clusterWeight;b.sum+=ret*clusterWeight;b.sumSq+=ret*ret*clusterWeight;b.wins+=(ret>0?clusterWeight:0);
+      b.count++;b.observations+=Number(cluster.observations||0);
+    });
+  });
   const learned=Object.fromEntries(Object.entries(buckets).map(([key,b])=>[key,summarizeLearningBucket(b,12)]));
   const learnedRows=Object.values(learned);
-  return {version:SUGGESTION_ENGINE_VERSION,samples:((ledger&&ledger.outcomes)||[]).length,
-    current_samples:((ledger&&ledger.outcomes)||[]).filter(x=>normalizedStrategyVersion(x.strategy_version)===SUGGESTION_ENGINE_VERSION).length,buckets:learned,
+  const identifiedMarkets=new Set(outcomes.map((outcome,index)=>String(outcome.market_id||`unidentified-observation-${index}`)));
+  const currentOutcomes=outcomes.filter(x=>normalizedStrategyVersion(x.strategy_version)===SUGGESTION_ENGINE_VERSION);
+  const currentMarkets=new Set(currentOutcomes.map((outcome,index)=>String(outcome.market_id||`unidentified-current-${index}`)));
+  return {version:SUGGESTION_ENGINE_VERSION,samples:outcomes.length,markets:identifiedMarkets.size,
+    current_samples:currentOutcomes.length,current_markets:currentMarkets.size,buckets:learned,
     promoted_buckets:learnedRows.filter(r=>r.weight>=8&&r.lower_bound>0.003).length,
     demoted_buckets:learnedRows.filter(r=>r.weight>=8&&r.upper_bound<-0.003).length,
     expired_ungraded:Number(ledger&&ledger.expired_ungraded||0),
@@ -2728,7 +2743,7 @@ function decisionSummary(p){
   const blockerRows=Object.entries(d.rejectionCounts||{}).filter(([,count])=>count>0).sort((a,b)=>b[1]-a[1]);
   const blockers=blockerRows.length?` Blocks: ${blockerRows.slice(0,4).map(([key,count])=>`${blockerLabels[key]||key} ${count}`).join(", ")}.`:"";
   const learning=d.learning?` Learning: ${d.learning.samples} completed trades retained with older strategies down-weighted, ${(d.learning.global_score*100).toFixed(2)}% shrunk expectancy; ${d.learning.current_samples||0} completed under adaptive strategy ${SUGGESTION_ENGINE_VERSION}${d.learning.best?`; strongest ${d.learning.best.feature.replace(":"," ")}`:""}${d.learning.worst?`; weakest ${d.learning.worst.feature.replace(":"," ")}`:""}.`:"";
-  const calibration=d.marketLearning?` Walk-forward calibration: ${d.marketLearning.samples||0} net-of-cost signals graded after ${SIGNAL_EVAL_HOURS} hours (${d.marketLearning.current_samples||0} under adaptive strategy ${SUGGESTION_ENGINE_VERSION}), ${d.marketLearning.pending||0} awaiting a future price${d.marketLearning.expired_ungraded?`, ${d.marketLearning.expired_ungraded} expired ungraded`:""}; ${d.marketLearning.promoted_buckets||0} feature cohorts promoted and ${d.marketLearning.demoted_buckets||0} demoted. Matured markets are repriced even after leaving the active scan, and confirmed observation-only signals also train the ledger. Confidence counts independent outcomes once and uncertainty gates sizing. Historical prior: Sports and Crypto trends stay observation-only; reversal and short-dated NO require promotion in their own recent cohorts; exact-range contracts are excluded; longshots and YES entries are sized down. Politics trends receive 72 hours before ordinary signal exits.`:"";
+  const calibration=d.marketLearning?` Walk-forward calibration: ${d.marketLearning.samples||0} net-of-cost observations across ${d.marketLearning.markets||0} distinct markets graded after ${SIGNAL_EVAL_HOURS} hours (${d.marketLearning.current_samples||0} observations / ${d.marketLearning.current_markets||0} markets under adaptive strategy ${SUGGESTION_ENGINE_VERSION}), ${d.marketLearning.pending||0} awaiting a future price${d.marketLearning.expired_ungraded?`, ${d.marketLearning.expired_ungraded} expired ungraded`:""}; ${d.marketLearning.promoted_buckets||0} feature cohorts promoted and ${d.marketLearning.demoted_buckets||0} demoted. Repeated snapshots of one market are clustered into one effective outcome, matured markets are repriced after leaving the active scan, and confirmed observation-only signals also train the ledger. Uncertainty gates sizing. Historical prior: Sports and Crypto trends stay observation-only; reversal and short-dated NO require promotion in their own recent cohorts; exact ranges and path-dependent barriers are excluded; longshots and YES entries are sized down. Politics trends receive 72 hours before ordinary signal exits.`:"";
   return `${d.mode} mode: ${d.reason}${emotion} Limits now: ${d.maxNew} new trade${d.maxNew===1?"":"s"}, max ${(d.maxFrac*100).toFixed(1)}% per position${d.minConv?`, conviction ${d.minConv}+`:""}.${learning}${calibration}${exposure}${allocation}${candidates}${blockers}`;
 }
 function renderAgentBrief(cfg,p,st){
@@ -4321,7 +4336,7 @@ window.PMA_ENGINE_DIAGNOSTICS=Object.freeze({
     networkTimeoutSeconds:NETWORK_REQUEST_TIMEOUT_MS/1000,priceTimeoutSeconds:PRICE_REQUEST_TIMEOUT_MS/1000,
     staleCacheIsMarkOnly:true,strategyEvidenceSurvivesBuilds:true,signalEvaluationHours:SIGNAL_EVAL_HOURS,signalRetryHours:SIGNAL_LEDGER_RETRY_HOURS,
     signalDueFetchLimit:SIGNAL_LEDGER_DUE_FETCH_LIMIT,survivorshipSafeSignalGrading:true,
-    signalRoundTripCostCents:SIGNAL_ROUND_TRIP_COST*100,independentConfidence:true,uncertaintyGatedCalibration:true,
+    signalRoundTripCostCents:SIGNAL_ROUND_TRIP_COST*100,independentConfidence:true,marketClusteredCalibration:true,uncertaintyGatedCalibration:true,
     historicalPrior:"Sports and Crypto trends observation-only; reversal and short-dated NO require recent cohort promotion; exact ranges and path-dependent barriers excluded; longshots and YES sized down"}),
 });
 function runEngineSelfTest(){
@@ -4357,8 +4372,8 @@ function runEngineSelfTest(){
     realized_pnl:-20,opened_at:hoursAgo(72+i),closed_at:closedAt});
   const learningProfile=buildAdaptiveProfile(learner);
   const calibrationLedger=defaultSignalLedger();
-  for(let i=0;i<16;i++)calibrationLedger.outcomes.push({signal_type:"trend",quality:"confirmed",category:"Politics",side:"YES",entry_price:0.42,return:0.12,evaluated_at:closedAt});
-  for(let i=0;i<16;i++)calibrationLedger.outcomes.push({signal_type:"reversal",quality:"reversal",category:"Sports",side:"NO",entry_price:0.42,return:-0.12,evaluated_at:closedAt});
+  for(let i=0;i<16;i++)calibrationLedger.outcomes.push({market_id:`trend-market-${i}`,signal_type:"trend",quality:"confirmed",category:"Politics",side:"YES",entry_price:0.42,return:0.12,evaluated_at:closedAt});
+  for(let i=0;i<16;i++)calibrationLedger.outcomes.push({market_id:`reversal-market-${i}`,signal_type:"reversal",quality:"reversal",category:"Sports",side:"NO",entry_price:0.42,return:-0.12,evaluated_at:closedAt});
   const calibrationProfile=buildSignalCalibration(calibrationLedger);
   const learnedTrend=learnedOpportunity(AGENTS[0],learner,{market_id:"learn-trend",signal_type:"trend",quality:"confirmed",category:"Politics",side:"YES",entry_price:0.42},learningProfile,calibrationProfile);
   const learnedReversal=learnedOpportunity(AGENTS[0],learner,{market_id:"learn-reversal",signal_type:"reversal",quality:"reversal",category:"Sports",side:"NO",entry_price:0.42},learningProfile,calibrationProfile);
@@ -4393,8 +4408,11 @@ function runEngineSelfTest(){
   const expiredLedgerState={signal_ledger:{pending:[{key:"expired",market_id:"never-returned",observed_at:hoursAgo(169),side:"YES",entry_price:0.4}],outcomes:[]}};
   updateSignalLedger(expiredLedgerState,[],[]);
   const calibrationCandidate={signal_type:"trend",quality:"confirmed",category:"Politics",side:"YES",entry_price:0.42};
-  const calibrationFromReturns=(returns,candidate=calibrationCandidate)=>buildSignalCalibration({pending:[],outcomes:returns.map(ret=>Object.assign({},candidate,
-    {strategy_version:SUGGESTION_ENGINE_VERSION,return:ret,evaluated_at:closedAt}))});
+  const calibrationFromReturns=(returns,candidate=calibrationCandidate)=>buildSignalCalibration({pending:[],outcomes:returns.map((ret,index)=>Object.assign({},candidate,
+    {market_id:`${candidate.market_id||"calibration"}-${index}`,strategy_version:SUGGESTION_ENGINE_VERSION,return:ret,evaluated_at:closedAt}))});
+  const repeatedMarketCalibration=buildSignalCalibration({pending:[],outcomes:Array.from({length:24},()=>Object.assign({},calibrationCandidate,
+    {market_id:"one-repeated-market",strategy_version:SUGGESTION_ENGINE_VERSION,return:0.12,evaluated_at:closedAt}))});
+  const repeatedMarketState=calibratedOpportunity(calibrationCandidate,repeatedMarketCalibration);
   const singleCalibration=calibratedOpportunity(calibrationCandidate,calibrationFromReturns([0.10]));
   const stablePositiveCalibration=calibratedOpportunity(calibrationCandidate,calibrationFromReturns(Array(24).fill(0.12)));
   const stableNegativeCalibration=calibratedOpportunity(calibrationCandidate,calibrationFromReturns(Array(24).fill(-0.12)));
@@ -4405,6 +4423,10 @@ function runEngineSelfTest(){
   const promotedReversalCalibration=calibrationFromReturns(Array(24).fill(0.12),promotedReversalCandidate);
   const promotedReversal=learnedOpportunity(AGENTS[0],defaultPortfolio(),promotedReversalCandidate,null,promotedReversalCalibration);
   const promotedReversalSuggestion=applyAdaptiveMarketPromotion(Object.assign({},reversal,{entry_candidate:true}),promotedReversalCalibration);
+  const promotedOpenBook=defaultPortfolio(),promotedOpenAgent=AGENTS.find(a=>a.id==="diversifier");
+  openPositions(promotedOpenBook,promotedOpenAgent,[promotedReversalSuggestion],"All",{
+    minConv:0,maxNew:1,maxFrac:0.03,reserve:0.10,targetExposure:0.60,learning:buildAdaptiveProfile(promotedOpenBook),marketLearning:promotedReversalCalibration,
+  },new Set(),{});
   const blockedCryptoPromotion=applyAdaptiveMarketPromotion(Object.assign({},cryptoTrend,{entry_candidate:true}),calibrationFromReturns(Array(24).fill(0.12),{
     market_id:"crypto-positive",signal_type:"trend",quality:"confirmed",category:"Crypto",side:"YES",entry_price:0.42,days_to_resolution:45}));
   const legacyBuildCalibration=buildSignalCalibration({pending:[],outcomes:[Object.assign({},calibrationCandidate,
@@ -4464,12 +4486,16 @@ function runEngineSelfTest(){
   const executableBook=JSON.parse(JSON.stringify(markOnlyBook));
   delete executableBook.positions[0].price_status;
   markToMarket(executableBook,{"offline-mark":market({id:"offline-mark",yes_price:0.8,no_price:0.2})},AGENTS[0],{policyExits:true,executeTrades:true});
+  const staleEntryBook=defaultPortfolio(),staleEntryAgent=AGENTS[0];
+  openPositions(staleEntryBook,staleEntryAgent,[Object.assign({},trend,{trade_ready:false,entry_candidate:false,watch_only:true})],"All",{
+    minConv:0,maxNew:1,maxFrac:0.04,reserve:0.10,targetExposure:0.60,learning:buildAdaptiveProfile(staleEntryBook),marketLearning:{samples:0,pending:0,buckets:{}},
+  },new Set(),{});
   const buildMigrationState=defaultState();
-  buildMigrationState.engine_version=49;buildMigrationState.strategy_version=SUGGESTION_ENGINE_VERSION;
+  buildMigrationState.engine_version=50;buildMigrationState.strategy_version=SUGGESTION_ENGINE_VERSION;
   buildMigrationState.agents.value.engine_baseline={version:SUGGESTION_ENGINE_VERSION,started_at:hoursAgo(2),equity:9876.54};
   reconcileStateVersions(buildMigrationState);
   const strategyMigrationState=defaultState();
-  strategyMigrationState.engine_version=49;strategyMigrationState.strategy_version=PREVIOUS_STRATEGY_VERSION;
+  strategyMigrationState.engine_version=50;strategyMigrationState.strategy_version=PREVIOUS_STRATEGY_VERSION;
   strategyMigrationState.agents.value.cash=9876.54;
   strategyMigrationState.agents.value.engine_baseline={version:PREVIOUS_STRATEGY_VERSION,started_at:hoursAgo(2),equity:10000};
   reconcileStateVersions(strategyMigrationState);
@@ -4486,6 +4512,7 @@ function runEngineSelfTest(){
       historicalPriorBlocksReversal:!priorReversal.allowed&&priorReversal.blocked_by==="historical",
       reversalRemainsBlockedForExplorer:!explorerReversal.allowed&&explorerReversal.blocked_by==="historical",
       recentProofCanUnlockReversal:promotedReversal.allowed&&promotedReversal.market_state==="promoted"&&promotedReversalSuggestion.trade_ready,
+      promotedReversalOpensBoundedPosition:promotedOpenBook.positions.length===1&&promotedOpenBook.positions[0].cost<=300,
       hardBlockedCryptoCannotSelfPromote:!blockedCryptoPromotion.trade_ready,
       enduranceReplacesReversal:agentAcceptsSuggestion(AGENTS.find(a=>a.id==="reversal"),trend)&&!agentAcceptsSuggestion(AGENTS.find(a=>a.id==="reversal"),reversal),
       historicalPriorSizesRisk:!priorCryptoLongshot.blocked&&priorCryptoLongshot.multiplier<1&&priorCryptoLongshot.features.length===2,
@@ -4503,6 +4530,9 @@ function runEngineSelfTest(){
       expiresOnlyAfterRetryWindow:expiredLedgerState.signal_ledger.pending.length===0&&expiredLedgerState.signal_ledger.expired_ungraded===1,
       ledgerIsNetOfCosts:ledgerState.signal_ledger.outcomes[0].gross_return===0.25&&ledgerState.signal_ledger.outcomes[0].estimated_cost_return===0.0125,
       independentCalibrationConfidence:singleCalibration.confidence<0.06,
+      repeatedSnapshotsCountAsOneMarket:repeatedMarketCalibration.markets===1&&repeatedMarketCalibration.buckets["signal:trend"].samples===1
+        &&repeatedMarketCalibration.buckets["signal:trend"].observations===24&&repeatedMarketState.state==="observing",
+      distinctMarketsCanPromote:stablePositiveCalibration.state==="promoted"&&stablePositiveCalibration.supporting_features>=2,
       legacyBuildLineageRemainsHistorical:normalizedStrategyVersion(41)===40,
       previousStrategyIsDownWeighted:legacyBuildCalibration.current_samples===0&&legacyBuildCalibration.buckets["signal:trend"].weight>0.54&&legacyBuildCalibration.buckets["signal:trend"].weight<=0.55,
       currentStrategyKeepsFullWeight:currentStrategyCalibration.current_samples===1&&currentStrategyCalibration.buckets["signal:trend"].weight>0.99,
@@ -4523,6 +4553,7 @@ function runEngineSelfTest(){
     offline:{fresh:offlineCachePolicy(30*60000),staleEntry:offlineCachePolicy(3*3600000),expired:offlineCachePolicy(25*3600000),
       staleMarkUpdatesValue:markOnlyBook.positions.length===1&&markOnlyBook.positions[0].value===800,
       staleMarkPreservesTrades:markOnlyBook.positions.length===1&&markOnlyBook.positions[0].shares===1000&&markOnlyBook.cash===9500&&markOnlyBook.positions[0].price_status==="cached-mark-only",
+      staleCacheBlocksHiddenCandidates:staleEntryBook.positions.length===0&&staleEntryBook.cash===STARTING_BALANCE,
       freshSnapshotExecutesRules:executableBook.positions.length===1&&executableBook.positions[0].shares<1000&&executableBook.cash>9500},
     exits:{youngConflict:exitReason(young,fresh,conflict,AGENTS[0]),matureConflict:exitReason(mature,fresh,conflict,AGENTS[0]),
       politicsEarlyConflict:exitReason(politicsEarly,fresh,conflict,AGENTS[0]),politicsMatureConflict:exitReason(politicsMature,fresh,conflict,AGENTS[0]),trailing:trailingProfitReason(trailing)},

sw.js

@@ -1,4 +1,4 @@
-const CACHE_NAME = "polymarket-arena-build-50";
+const CACHE_NAME = "polymarket-arena-build-51";
 const APP_SHELL = ["/", "/index.html", "/personal.html", "/cycle-worker.js"];
 
 self.addEventListener("install", event => {