feat: add autonomous paper-trading and calibration pipeline

workers/signalWorker.js

@@ -1,10 +1,14 @@
 const https = require("https");
 const http = require("http");
 
+const { getPriceContext, formatPriceContext } = require("./priceContext");
+
 const CONCURRENCY = 4;
+const PREDICTION_WINDOW_DAYS = 21;
 
 
 async function runSignalWorker(archiveDb, intelligenceDb, config) {
+  const loopDelay = config.workers?.signalLoopDelayMs ?? 1000;
   const llmConfig = config.openRouter || {};
 
   // add as_of column if it doesnt exist yet
@@ -28,15 +32,28 @@ async function runSignalWorker(archiveDb, intelligenceDb, config) {
     LIMIT 1
   `);
 
+  // decay window — only feed recent predictions into the signal prompt.
+  // backtest showed signal degrades sharply after ~10 days, so use 21d as a soft window
   const getPredictions = intelligenceDb.prepare(`
-    SELECT type, direction, magnitude, timeframe, rationale, event_date, id
+    SELECT type, direction, magnitude, timeframe, rationale, probability, event_date, id
     FROM event_predictions
     WHERE company_id = ?
       AND substr(event_date, 1, 10) <= ?
+      AND date(substr(event_date, 1, 10)) >= date(?, '-${PREDICTION_WINDOW_DAYS} days')
+      AND timeframe != 'short'
+      AND direction IN ('positive', 'negative')
     ORDER BY event_date DESC
     LIMIT 50
   `);
 
+  const getCompanyAccuracy = intelligenceDb.prepare(`
+    SELECT
+      COUNT(*) as total,
+      SUM(correct_10d) as correct
+    FROM prediction_outcomes
+    WHERE company_id = ? AND correct_10d IS NOT NULL
+  `);
+
   const getFacts = intelligenceDb.prepare(`
     SELECT claim, type, confidence, confirmation_count
     FROM company_facts
@@ -118,11 +135,31 @@ async function runSignalWorker(archiveDb, intelligenceDb, config) {
           continue;
         }
 
-        const predictions = getPredictions.all(company_id, checkpoint_date);
+        const predictions = getPredictions.all(company_id, checkpoint_date, checkpoint_date);
         const facts = getFacts.all(company_id, checkpoint_date);
         const relationships = getRelationships.all(company_id, checkpoint_date);
 
-        const prompt = buildPrompt(company.name, facts, relationships, predictions, checkpoint_date);
+        // skip if the decay window left us with nothing useful
+        if (predictions.length === 0) {
+          inFlight.delete(key);
+          continue;
+        }
+
+        // pull market context + historical accuracy for this company
+        let priceBlock = null;
+        if (company.ticker) {
+          try {
+            const snapshot = await getPriceContext(intelligenceDb, company.ticker, checkpoint_date);
+            priceBlock = formatPriceContext(snapshot, company.ticker);
+          } catch (_) {}
+        }
+
+        const acc = getCompanyAccuracy.get(company_id);
+        const accuracyBlock = (acc && acc.total >= 5)
+          ? `Past prediction accuracy for ${company.name}: ${(acc.correct / acc.total * 100).toFixed(0)}% over ${acc.total} evaluated calls.`
+          : null;
+
+        const prompt = buildPrompt(company.name, facts, relationships, predictions, checkpoint_date, priceBlock, accuracyBlock);
 
         let result;
         try {
@@ -165,6 +202,10 @@ async function runSignalWorker(archiveDb, intelligenceDb, config) {
 
       } catch (err) {
         console.error(`[signal:${id}] cycle error:`, err.message);
+      } finally {
+        // Successful and early-exit paths must yield too; otherwise an invalid
+        // checkpoint can turn this into a tight synchronous SQLite loop.
+        await sleep(loopDelay);
       }
     }
   }
@@ -179,7 +220,7 @@ async function runSignalWorker(archiveDb, intelligenceDb, config) {
 }
 
 
-function buildPrompt(companyName, facts, relationships, predictions, asOf) {
+function buildPrompt(companyName, facts, relationships, predictions, asOf, priceBlock, accuracyBlock) {
   const factsBlock = facts.length > 0
     ? facts.map(f => `- ${f.claim} (confirmed ${f.confirmation_count}x)`).join("\n")
     : "No known facts yet.";
@@ -188,9 +229,30 @@ function buildPrompt(companyName, facts, relationships, predictions, asOf) {
     ? relationships.map(r => `- ${r.relationship_type}: ${r.to_entity} (${r.confidence})`).join("\n")
     : "No known relationships.";
 
-  const predBlock = predictions.map((p, i) =>
-    `${i + 1}. [${p.type}] ${p.direction} / ${p.magnitude} / ${p.timeframe} — ${p.rationale || "no rationale"}`
-  ).join("\n");
+
+  // recency-weighted prediction block — newer predictions get a [RECENT] tag,
+  // and high-magnitude + long-timeframe gets [HIGH CONFIDENCE].
+  // probability is surfaced when present so the LLM can weight by it.
+  const asOfMs = new Date(asOf + "T00:00:00Z").getTime();
+
+  const predBlock = predictions.map((p, i) => {
+    const tags = [];
+    if (p.magnitude === "high" && p.timeframe === "long") tags.push("HIGH CONFIDENCE");
+
+    if (p.event_date) {
+      const ageDays = Math.round((asOfMs - new Date(p.event_date.slice(0, 10) + "T00:00:00Z").getTime()) / 86_400_000);
+      if (ageDays <= 7) tags.push(`RECENT ${ageDays}d`);
+      else tags.push(`${ageDays}d old`);
+    }
+
+    const probStr = (typeof p.probability === "number") ? ` p=${p.probability.toFixed(2)}` : "";
+    const tagStr = tags.length ? ` [${tags.join(", ")}]` : "";
+
+    return `${i + 1}. [${p.type}]${tagStr}${probStr} ${p.direction} / ${p.magnitude} / ${p.timeframe} — ${p.rationale || "no rationale"}`;
+  }).join("\n");
+
+  const pricePart = priceBlock ? `\nMarket context for ${companyName}:\n${priceBlock}\n` : "";
+  const accPart = accuracyBlock ? `\n${accuracyBlock}\n` : "";
 
   return `You are a financial intelligence analyst generating a trade signal for ${companyName} as of ${asOf}.
 
@@ -199,10 +261,12 @@ ${factsBlock}
 
 Known relationships:
 ${relBlock}
-
-Event predictions up to ${asOf}:
+${pricePart}${accPart}
+Recent event predictions (last 21 days):
 ${predBlock}
 
+Weight RECENT and HIGH CONFIDENCE predictions more heavily. Discount older predictions and any that lack a probability score. Predictions that disagree with the recent price trajectory are weaker — be sceptical of bullish predictions on a name that has already rallied 20% in 30 days, and vice versa.
+
 Generate a trade signal as JSON with this exact shape:
 {
   "signal": "BUY | HOLD | SELL",
@@ -214,11 +278,14 @@ Generate a trade signal as JSON with this exact shape:
   "summary": "2-3 sentence plain English summary"
 }
 
+Default to HOLD when the predictions are mixed, stale, or low-probability. Reserve BUY/SELL for cases where the weight of high-confidence recent evidence is unambiguous.
+
 Risk factors should be derived from:
 - Supply chain concentration (heavy dependence on single suppliers)
 - Geopolitical exposure (relationships with entities in sensitive regions)
 - Competitive threats (strong competitors gaining ground)
 - Regulatory exposure (themes mentioning regulation or export controls)
+- Stretched valuation given recent price moves
 - Negative prediction patterns in recent events
 
 Only output valid JSON. Always respond in English.`;