6-Model Consensus

const consensus: BotDef = aiBot<DirReq, ConsRes>(
  {
    id: "ai-consensus",
    name: "6-Model Consensus",
    category: "ai",
    glyph: "⌬",
    tagline: "All AI quants vote. Tier emerges from agreement, not opinion.",
    formula: "binary + magnitude + +macro + sequence + transformer + quantile",
    endpoint: "/api/consensus",
    module: "ai quants/models/best_consensus/build.py",
    params: [],
  },
  {
    request: dirRequest,
    build: (data) => {
      const c = data.consensus;
      return {
        signals: [],
        metrics: [
          { key: "dir", label: "Consensus direction", value: c.direction.toUpperCase(), tone: c.direction === "up" ? "bull" : c.direction === "down" ? "bear" : "neutral" },
          { key: "agree", label: "Agree", value: `${c.agree_count} / ${c.n_models}`, tone: c.agree_count >= c.n_models - 1 ? "bull" : "neutral" },
          { key: "tier", label: "Tier", value: c.tier.toUpperCase(), tone: c.tier === "ultra" ? "bull" : c.tier === "high" ? "info" : "neutral" },
          { key: "acc", label: "Expected acc band", value: c.expected_accuracy_band, tone: "info" },
          { key: "mag", label: "Avg magnitude", value: `${(c.avg_magnitude * 100).toFixed(2)}%`, tone: "info" },
        ],
        summary: `Real-model consensus on ${data.ticker}: ${c.agree_count}/${c.n_models} agree → ${c.direction.toUpperCase()} (${c.tier} tier). Accuracy band: ${c.expected_accuracy_band}.`,
        beginner:
          "Six different AI models look at the same stock and vote. When 5 or 6 agree, the trade is much higher quality. When they're split, the market is genuinely confused.",
        verdict: {
          side: c.direction === "up" ? "buy" : c.direction === "down" ? "sell" : "hold",
          text: c.direction === "split"
            ? `Models split — no edge.`
            : `${c.tier.toUpperCase()} consensus — ${c.agree_count}/${c.n_models} say ${c.direction.toUpperCase()}.`,
          confidence: c.tier === "ultra" ? 0.95 : c.tier === "high" ? 0.78 : c.tier === "medium" ? 0.55 : 0.3,
        },
      };
    },
    mock: (ctx) => {
      const px = closes(ctx.candles);
      const trend = trendStrength(px);
      const rv = realisedVol(px);
      const seed = hashStr(ctx.symbol + "consensus");
      const rand = seedRand(seed);
      const models = [
        { name: "binary GBM", p: 0.5 + trend * 1.4 + (rand() - 0.5) * 0.15 },
        { name: "magnitude", p: 0.5 + trend * 1.1 + (rand() - 0.5) * 0.18 },
        { name: "+macro", p: 0.5 + trend * 1.0 - (rv - 0.25) * 0.6 + (rand() - 0.5) * 0.14 },
        { name: "sequence CNN", p: 0.5 + trend * 0.9 + (rand() - 0.5) * 0.20 },
        { name: "transformer", p: 0.5 + trend * 1.2 - (rv - 0.25) * 0.4 + (rand() - 0.5) * 0.14 },
        { name: "quantile", p: 0.5 + trend * 0.8 + (rand() - 0.5) * 0.16 },
      ].map((m) => ({ ...m, p: Math.min(0.97, Math.max(0.03, m.p)), vote: (m.p > 0.5 ? 1 : -1) as 1 | -1 }));
      const upVotes = models.filter((m) => m.vote === 1).length;
      const downVotes = 6 - upVotes;
      const dir = upVotes >= 5 ? "up" : downVotes >= 5 ? "down" : "split";
      const agree = Math.max(upVotes, downVotes);
      const avgMag = Math.abs(trend) * 0.6;
      const tier = agree === 6 && avgMag > 0.04 ? "ultra" : agree >= 5 ? "high" : agree >= 4 ? "medium" : "low";
      const accBand = tier === "ultra" ? "65–77%" : tier === "high" ? "60–66%" : tier === "medium" ? "55–60%" : "≤55%";
      const signals: Signal[] = [];
      return {
        signals,
        metrics: [
          { key: "dir", label: "Consensus direction", value: dir.toUpperCase(), tone: dir === "up" ? "bull" : dir === "down" ? "bear" : "neutral" },
          { key: "agree", label: "Agree", value: `${agree} / 6`, tone: agree >= 5 ? "bull" : "neutral" },
          { key: "tier", label: "Tier", value: tier.toUpperCase(), tone: tier === "ultra" ? "bull" : tier === "high" ? "info" : "neutral" },
          { key: "acc", label: "Expected acc band", value: accBand, tone: "info" },
        ],
        pane: {
          kind: "histogram",
          series: [{
            values: models.map((m) => m.p - 0.5),
            color: "var(--bear)",
            label: "P(up) − 0.5 per model",
          }],
          refLines: [{ value: 0, color: "var(--fg-faint)" }],
          height: 100,
        },
        summary:
          `Models voting UP: ${upVotes}/6 — ${tier.toUpperCase()} consensus. ` +
          models.map((m) => `${m.name} ${(m.p * 100).toFixed(0)}%${m.vote === 1 ? "↑" : "↓"}`).join(" · "),
        beginner: "Six models vote on direction. 5–6 agreeing = high quality. Split = sit out.",
        verdict: {
          side: dir === "up" ? "buy" : dir === "down" ? "sell" : "hold",
          text: dir === "split"
            ? `Models split ${upVotes}↑ / ${downVotes}↓ — no edge.`
            : `${tier.toUpperCase()} consensus — ${agree}/6 say ${dir.toUpperCase()}. Historical acc band: ${accBand}.`,
          confidence: tier === "ultra" ? 0.95 : tier === "high" ? 0.78 : tier === "medium" ? 0.55 : 0.3,
        },
      };
    },
  },
);