gavindiaz/polymarket-analyst_github
1
0
Fork 0
mirror of https://github.com/theodore-song/polymarket-analyst.git synced 2026-08-23 20:48:08 +00:00
Code Issues Packages Projects Releases Wiki Activity

Isolate directional learning from retired pilots

Browse Source
This commit is contained in:
Theodore Song
2026-08-22 08:46:34 -04:00
parent 9e87d1f9f2
commit 605a5f2ae4
2 changed files with 27 additions and 4 deletions
Download Patch File Download Diff File Expand all files Collapse all files
index.html
+25 -4
View File
@@ -2816,9 +2816,19 @@ function tradeReturnForLearning(trade,closed){
const pnl=closed?Number(trade.realized_pnl||0):Number(trade.unrealized_pnl||0)+Number(trade.partial_realized_pnl||0);
return clamp(pnl/basis,-1,2);
}
function generalAdaptiveLearningExclusion(trade){
if(!trade||!["YES","NO"].includes(String(trade.side||"")))return "not-directional";
if(trade.requires_complete_bundle||trade.bundle_id)return "priced-bundle";
if(trade.maker_quote_id||String(trade.signal_type||"").includes("maker"))return "maker-strategy";
if(["shock-fade-pilot","sports-contest-no-pilot","resolution-week-no-pilot"].includes(String(trade.signal_type||"")))return "specialized-learner";
if(trade.jump_risk||Number(trade.days_to_resolution)<0)return "settlement-unsafe";
if(/full-horizon settlement safety gate|settled before its timed exit/i.test(String(trade.close_reason||'')))return "retired-safety-migration";
return null;
}
function buildAdaptiveProfile(p){
const buckets={},currentBuckets={},observations=[],currentClosedObservations=[],currentClosedReturns=[];
const add=(trade,closed)=>{
if(generalAdaptiveLearningExclusion(trade))return;
const version=normalizedStrategyVersion(trade.strategy_version);if(version<34)return;
const age=Math.max(0,Date.now()-new Date(trade.closed_at||trade.opened_at||0).getTime());
const recency=Number.isFinite(age)?Math.exp(-age/(45*86400000)):0.4;
@@ -2838,8 +2848,10 @@ function buildAdaptiveProfile(p){
}
});
};
(p.closed||[]).forEach(t=>add(t,true));
(p.positions||[]).filter(t=>daysHeld(t)>=1).forEach(t=>add(t,false));
const closedRows=(p.closed||[]).filter(t=>normalizedStrategyVersion(t.strategy_version)>=34);
const eligibleClosed=closedRows.filter(t=>!generalAdaptiveLearningExclusion(t));
eligibleClosed.forEach(t=>add(t,true));
(p.positions||[]).filter(t=>daysHeld(t)>=1&&!generalAdaptiveLearningExclusion(t)).forEach(t=>add(t,false));
const learned=Object.fromEntries(Object.entries(buckets).map(([k,b])=>[k,summarizeLearningBucket(b,6)]));
const currentLearned=Object.fromEntries(Object.entries(currentBuckets).map(([k,b])=>[k,summarizeLearningBucket(b,6)]));
const totalWeight=observations.reduce((s,x)=>s+x.weight,0),totalSum=observations.reduce((s,x)=>s+x.ret*x.weight,0);
@@ -2848,7 +2860,7 @@ function buildAdaptiveProfile(p){
const currentClosedSum=currentClosedObservations.reduce((s,x)=>s+x.ret*x.weight,0);
const ranked=Object.entries(learned).filter(([k,v])=>!k.startsWith("side:")&&v.weight>=1)
.sort((a,b)=>b[1].score-a[1].score);
return {version:SUGGESTION_ENGINE_VERSION,samples:(p.closed||[]).filter(t=>normalizedStrategyVersion(t.strategy_version)>=34).length,
return {version:SUGGESTION_ENGINE_VERSION,samples:eligibleClosed.length,excluded_samples:closedRows.length-eligibleClosed.length,
effective_samples:+totalWeight.toFixed(2),global_score:+globalScore.toFixed(4),buckets:learned,current_buckets:currentLearned,
current_samples:currentClosedReturns.length,current_effective_samples:+currentClosedWeight.toFixed(2),
current_global_score:+(currentClosedSum/(currentClosedWeight+4)).toFixed(4),
@@ -4939,7 +4951,7 @@ function decisionSummary(p){
const blockerLabels={historical_prior:"history-tested losing setup",learning:"live learned losing regime",pilot_learning:"sports pilot demoted",shock_learning:"shock pilot unpromoted",resolution_week_learning:"resolution-week pilot demoted",event_overlap:"same event",confidence:"confidence",overlap:"material overlap",already_held:"already held",cooldown:"stop cooldown",focus:"category focus",price:"entry price",edge:"edge",timing:"timing",liquidity:"liquidity",activity:"activity",evidence:"evidence",direction:"direction",portfolio_limit:"portfolio limit"};
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 as historical context, ${(d.learning.global_score*100).toFixed(2)}% all-version shrunk expectancy; ${d.learning.current_samples||0} completed under adaptive strategy ${SUGGESTION_ENGINE_VERSION} with ${((d.learning.current_global_score||0)*100).toFixed(2)}% current-strategy shrunk expectancy. Only current-strategy closed trades can change sizing or personal cohort promotion${d.learning.best?`; historical strongest ${d.learning.best.feature.replace(":"," ")}`:""}${d.learning.worst?`; historical weakest ${d.learning.worst.feature.replace(":"," ")}`:""}.`:"";
const learning=d.learning?` Learning: ${d.learning.samples} eligible directional trades retained as historical context${d.learning.excluded_samples?`; ${d.learning.excluded_samples} bundle, maker, specialized-pilot, or settlement-unsafe trade${d.learning.excluded_samples===1?" was":"s were"} excluded and remains in the visible P&L ledger`:""}, ${(d.learning.global_score*100).toFixed(2)}% all-version shrunk expectancy; ${d.learning.current_samples||0} completed under adaptive strategy ${SUGGESTION_ENGINE_VERSION} with ${((d.learning.current_global_score||0)*100).toFixed(2)}% current-strategy shrunk expectancy. Only eligible current-strategy directional trades can change sizing or personal cohort promotion${d.learning.best?`; historical strongest ${d.learning.best.feature.replace(":"," ")}`:""}${d.learning.worst?`; historical weakest ${d.learning.worst.feature.replace(":"," ")}`:""}.`:"";
let calibration="";
if(d.marketLearning){
const ml=d.marketLearning,hasCounts=Number.isFinite(ml.events)&&Number.isFinite(ml.markets),hasCurrentCounts=Number.isFinite(ml.current_events);
@@ -6910,6 +6922,13 @@ function runEngineSelfTest(){
for(let i=0;i<8;i++)learner.closed.push({strategy_version:34,signal_type:"reversal",quality:"reversal",category:"Sports",side:"NO",entry_price:0.42,original_cost:100,
realized_pnl:-20,opened_at:hoursAgo(72+i),closed_at:closedAt});
const learningProfile=buildAdaptiveProfile(learner);
const isolatedLearningBook=defaultPortfolio();
isolatedLearningBook.closed.push({strategy_version:SUGGESTION_ENGINE_VERSION,signal_type:"trend",quality:"confirmed",category:"Politics",side:"YES",
entry_price:0.42,original_cost:100,realized_pnl:10,opened_at:hoursAgo(24),closed_at:closedAt});
isolatedLearningBook.closed.push({strategy_version:59,signal_type:"shock-fade-pilot",shock_strategy_version:3,quality:"shock-fade-pilot",category:"Sports",side:"YES",
entry_price:0.20,original_cost:100,realized_pnl:328.40,days_to_resolution:-0.05,jump_risk:true,opened_at:hoursAgo(23),closed_at:closedAt,
close_reason:"Shock contract failed the full-horizon settlement safety gate"});
const isolatedLearningProfile=buildAdaptiveProfile(isolatedLearningBook);
const legacyOnlyOpportunity=learnedOpportunity(AGENTS[0],learner,{market_id:"legacy-only-personal",signal_type:"catalyst",quality:"confirmed",
category:"Politics",side:"YES",entry_price:0.42,days_to_resolution:45},learningProfile,{samples:0,pending:0,buckets:{}});
const legacyPositiveDecision=adaptiveDecision(AGENTS[0],learner,1,AGENTS.length,STARTING_BALANCE,buildSignalCalibration(defaultSignalLedger()));
@@ -7544,6 +7563,8 @@ function runEngineSelfTest(){
&&currentPositiveProfile.current_samples===8&&Object.keys(currentPositiveProfile.current_buckets||{}).length>=5,
currentCapitalLearningSurvivesOfflineCompaction:offlineCurrentProfile.current_samples===currentPositiveProfile.current_samples
&&offlineCurrentProfile.current_buckets["signal:catalyst"].score===currentPositiveProfile.current_buckets["signal:catalyst"].score,
specializedUnsafeTradesCannotBiasDirectionalLearning:isolatedLearningProfile.samples===1&&isolatedLearningProfile.excluded_samples===1
&&isolatedLearningProfile.current_samples===1&&isolatedLearningProfile.global_score<0.01,
legacyTradesCannotIncreaseCurrentSizing:legacyPositiveDecision.maxFrac===0.045,
currentProfitsCanIncreaseBoundedSizing:currentPositiveDecision.maxFrac>legacyPositiveDecision.maxFrac
&&currentPositiveDecision.maxFrac<=0.06,
scripts/test-autonomous-runtime.mjs
+2
View File
@@ -76,6 +76,8 @@ assert.match(index, /const BINARY_COMPLEMENT_DEPTH_RESERVE=20;/);
assert.match(index, /bundleRequiresDepthVerification:true/);
assert.match(index, /bundleRequiresClobFeeVerification:true/);
assert.match(index, /function bundleExecutableLeg\(book,units,feeSchedule\)/);
assert.match(index, /function generalAdaptiveLearningExclusion\(trade\)/);
assert.match(index, /specializedUnsafeTradesCannotBiasDirectionalLearning:/);
assert.match(index, /function fetchBundleFeeSchedules\(conditionIds\)/);
assert.match(index, /function bundleFeeSchedulesMatch\(expected,reported\)/);
assert.match(index, /rejectsMismatchedClobFeeCurve:/);