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Quarantine losing signals and add bundle arbitrage

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Theodore Song
2026-08-18 16:40:18 -04:00
parent c7abdf8d4d
commit a5441e8659
4 changed files with 268 additions and 65 deletions
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scripts/evaluate-signals.mjs
+44 -12
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@@ -118,7 +118,7 @@ function evaluateMarket(market, points) {
const netReturn = grossReturn - (COST_CENTS / 100) / entry;
const fadeNetReturn = fadeEntry > 0.02 && fadeEntry < 0.98
? fadeExit / fadeEntry - 1 - (COST_CENTS / 100) / fadeEntry : null;
outcomes.push({ marketId: market.id, question: market.question, category: market.category,
outcomes.push({ marketId: market.id, eventKey: market.eventKey, question: market.question, category: market.category,
type: signal.type, side: signal.side, band: priceBand(entry), entry, exit, horizonHours,
grossReturn, netReturn, fadeNetReturn, hourMove: signal.hourMove, dayMove: signal.dayMove, weekMove: signal.weekMove,
observedAt: current.t, evaluatedAt: future.t });
@@ -135,17 +135,18 @@ function median(values) {
}
function summarize(rows, field = "netReturn") {
if (!rows.length) return { count: 0, markets: 0, mean: 0, median: 0, winRate: 0, worst: 0, best: 0, marketMean: 0, lower90: 0, upper90: 0 };
if (!rows.length) return { count: 0, markets: 0, events: 0, mean: 0, median: 0, winRate: 0, worst: 0, best: 0, marketMean: 0, lower90: 0, upper90: 0 };
const returns = rows.map((row) => row[field]).filter(Number.isFinite);
if (!returns.length) return { count: 0, markets: 0, mean: 0, median: 0, winRate: 0, worst: 0, best: 0, marketMean: 0, lower90: 0, upper90: 0 };
const marketBuckets = new Map();
if (!returns.length) return { count: 0, markets: 0, events: 0, mean: 0, median: 0, winRate: 0, worst: 0, best: 0, marketMean: 0, lower90: 0, upper90: 0 };
const eventBuckets = new Map();
rows.forEach((row) => {
const value = row[field];
if (!Number.isFinite(value)) return;
const bucket = marketBuckets.get(row.marketId) || [];
bucket.push(value); marketBuckets.set(row.marketId, bucket);
const key = row.eventKey || row.marketId;
const bucket = eventBuckets.get(key) || [];
bucket.push(value); eventBuckets.set(key, bucket);
});
const marketReturns = [...marketBuckets.values()].map((values) => values.reduce((sum, value) => sum + value, 0) / values.length);
const marketReturns = [...eventBuckets.values()].map((values) => values.reduce((sum, value) => sum + value, 0) / values.length);
const marketMean = marketReturns.reduce((sum, value) => sum + value, 0) / Math.max(1, marketReturns.length);
const variance = marketReturns.length > 1
? marketReturns.reduce((sum, value) => sum + (value - marketMean) ** 2, 0) / (marketReturns.length - 1) : 0;
@@ -153,7 +154,7 @@ function summarize(rows, field = "netReturn") {
return { count: returns.length,
mean: returns.reduce((sum, value) => sum + value, 0) / returns.length,
median: median(returns), winRate: returns.filter((value) => value > 0).length / returns.length,
worst: Math.min(...returns), best: Math.max(...returns), markets: marketReturns.length,
worst: Math.min(...returns), best: Math.max(...returns), markets: new Set(rows.map((row) => row.marketId)).size, events: marketReturns.length,
marketMean, lower90: marketMean - margin90, upper90: marketMean + margin90 };
}
@@ -191,6 +192,36 @@ const RULES = [
})),
];
const COMBINATION_CATEGORIES = ["Politics", "Sports", "Crypto", "Economy", "Pop Culture", "Other"];
const COMBINATION_BANDS = ["longshot", "mid", "favorite", "heavy-favorite"];
for (const category of COMBINATION_CATEGORIES) {
const slug = category.toLowerCase().replace(/\s+/g, "_");
for (const side of ["YES", "NO"]) {
RULES.push({ name: `follow_trend_${slug}_${side.toLowerCase()}`, field: "netReturn",
test: (row) => row.type === "trend" && row.category === category && row.side === side });
RULES.push({ name: `follow_reversal_${slug}_${side.toLowerCase()}`, field: "netReturn",
test: (row) => row.type === "reversal" && row.category === category && row.side === side });
for (const band of COMBINATION_BANDS) {
RULES.push({ name: `follow_trend_${slug}_${side.toLowerCase()}_${band.replace("-", "_")}`, field: "netReturn",
test: (row) => row.type === "trend" && row.category === category && row.side === side && row.band === band });
}
}
}
for (const side of ["YES", "NO"]) {
for (const band of COMBINATION_BANDS) {
RULES.push({ name: `follow_trend_${side.toLowerCase()}_${band.replace("-", "_")}`, field: "netReturn",
test: (row) => row.type === "trend" && row.side === side && row.band === band });
RULES.push({ name: `follow_reversal_${side.toLowerCase()}_${band.replace("-", "_")}`, field: "netReturn",
test: (row) => row.type === "reversal" && row.side === side && row.band === band });
}
}
RULES.push(
{ name: "follow_strong_trend_yes", field: "netReturn", test: (row) => row.type === "trend" && row.side === "YES" && Math.abs(row.dayMove) >= 0.015 && Math.abs(row.weekMove) >= 0.03 },
{ name: "follow_strong_trend_no", field: "netReturn", test: (row) => row.type === "trend" && row.side === "NO" && Math.abs(row.dayMove) >= 0.015 && Math.abs(row.weekMove) >= 0.03 },
{ name: "follow_hour_confirmed_trend_yes", field: "netReturn", test: (row) => row.type === "trend" && row.side === "YES" && Math.sign(row.hourMove) === Math.sign(row.dayMove) },
{ name: "follow_hour_confirmed_trend_no", field: "netReturn", test: (row) => row.type === "trend" && row.side === "NO" && Math.sign(row.hourMove) === Math.sign(row.dayMove) },
);
function evaluateRules(rows) {
return Object.fromEntries(RULES.map((rule) => [rule.name, summarize(rows.filter(rule.test), rule.field)]));
}
@@ -209,7 +240,7 @@ function chronologicalEvaluation(rows) {
const robustRules = Object.fromEntries(RULES.map((rule) => {
const segments = thirdRules.map((result) => result[rule.name]);
const trainStats = trainRules[rule.name], testStats = testRules[rule.name], pooledStats = pooled[rule.name];
const enoughData = segments.every((segment) => segment.count >= 20 && segment.markets >= 5);
const enoughData = segments.every((segment) => segment.count >= 20 && segment.events >= 5);
const trainTestPositive = trainStats.count >= 40 && testStats.count >= 20
&& trainStats.mean > 0 && trainStats.marketMean > 0 && testStats.mean > 0 && testStats.marketMean > 0;
const trainTestNegative = trainStats.count >= 40 && testStats.count >= 20
@@ -246,6 +277,7 @@ async function fetchActiveMarkets(limit) {
const rawMarkets = await fetchActiveMarkets(MARKET_LIMIT);
const markets = rawMarkets.map((raw) => ({ id: String(raw.id), question: raw.question || "", category: categoryOf(raw),
eventKey: String(raw.events?.[0]?.id || raw.events?.[0]?.slug || raw.eventId || raw.id),
tokenId: String(parseJson(raw.clobTokenIds)[0] || "") })).filter((market) => market.id && market.tokenId);
const histories = await mapLimit(markets, CONCURRENCY, async (market) => {
const data = await fetchJson(`${CLOB}/prices-history?market=${encodeURIComponent(market.tokenId)}&interval=1m&fidelity=60`);
@@ -260,8 +292,8 @@ const primaryOutcomes = outcomes.filter((row) => row.horizonHours === primaryHor
const report = {
generatedAt: new Date().toISOString(), marketLimit: MARKET_LIMIT, marketsWithHistory: successful.length,
methodology: { horizonHours: HORIZONS, primaryHorizon, observationBucketHours: 6, historyInterval: "1m", fidelityMinutes: 60,
estimatedRoundTripCostCents: COST_CENTS, clusterUnit: "market",
note: "Current active-market selection and current category tags are a survivorship-biased proxy; signal inputs and future marks are time-ordered without lookahead. Confidence intervals use per-market means to reduce repeated-observation distortion." },
estimatedRoundTripCostCents: COST_CENTS, clusterUnit: "event",
note: "Current active-market selection and current category tags are a survivorship-biased proxy; signal inputs and future marks are time-ordered without lookahead. Confidence intervals cluster correlated markets by Polymarket event." },
overall: summarize(primaryOutcomes), byType: grouped(primaryOutcomes, "type"), byCategory: grouped(primaryOutcomes, "category"),
byBand: grouped(primaryOutcomes, "band"), bySide: grouped(primaryOutcomes, "side"),
chronologicalSplit: chronologicalEvaluation(primaryOutcomes),
@@ -272,7 +304,7 @@ const report = {
failures: histories.filter((result) => result?.error).length,
};
const compact = process.env.EVAL_SUMMARY === "1";
const compactStats = (stats = {}) => ({ count: stats.count || 0, markets: stats.markets || 0,
const compactStats = (stats = {}) => ({ count: stats.count || 0, markets: stats.markets || 0, events: stats.events || 0,
mean: stats.mean || 0, marketMean: stats.marketMean || 0, lower90: stats.lower90 || 0, upper90: stats.upper90 || 0,
winRate: stats.winRate || 0 });
const compactRules = (rules = {}) => Object.fromEntries(Object.entries(rules)