System Architecture

// 1. Ingest price tick
engine.feedTick({ timestamp: Date.now(), price: 64232.02 })
  → volatility.update(price, timestamp)  // EWMA σ²
  → momentum.addTick({ timestamp, price }) // ROC buffer

// 2. Generate prediction
const result = engine.predict({
  currentPrice: 64232.02,
  strikePrice: 64355.45,
  timeRemainingSeconds: 176
})
// → baseProb = N(d₂)  [Black-Scholes]
// → momentumFactor = 0.5×ROC₁₀ + 0.3×ROC₃₀ + 0.2×ROC₆₀
// → reversionFactor = -deviation (if |dev| > 0.3%)
// → finalProb = sigmoid(logit(baseProb) + 150×momentum + 80×reversion)

// 3. Check abstention conditions
if (abstained) return { reason: 'dead_zone', ... }

// 4. Compare to market
const ev = calculateEV(p=0.85, q=0.10)
// → evYes = p/q - 1 = 0.85/0.10 - 1 = +7.50 (750% EV!)
// → evNo = (1-p)/(1-q) - 1 = -0.83 (-83% EV)
// → bestSide = 'YES', bestEV = 7.50

// 5. Size position
const bet = positionSizer.calculateBet({
  p: 0.85, q: 0.10,
  bankroll: 100,
  brierScore: 0.19,
  predictionCount: 150
})
// → alpha = 0.25 (tier 3: Brier < 0.22)
// → fullKelly = (0.85-0.10)/(1-0.10) = 0.833
// → fractionalKelly = 0.25 × 0.833 = 0.208
// → bet = 0.208 × $100 = $20.80 → capped to $5.00 (5% max)

{
  "engine": {
    "ewma": { "lambda": 0.94 },
    "momentum": { "bufferSize": 300 },
    "abstention": {
      "minTicks": 50,
      "deadZone": 0.10,
      "sigmaMultiplier": 2.0,
      "minAccuracy": 0.40,
      "minAccuracyWindow": 20,
      "minEV": 0.05,
      "minMargin": 0.15
    },
    "prediction": {
      "logitMomentumWeight": 150,
      "logitReversionWeight": 80,
      "nearExpiryGuardSec": 5
    }
  },
  "risk": {
    "bankroll": 100,
    "maxBetPct": 0.05,
    "kellyFraction": 0.25,
    "brierTiers": [
      { "maxBrier": 1.0, "minPredictions": 100, "alpha": 0.10 },
      { "maxBrier": 0.26, "minPredictions": 100, "alpha": 0.20 },
      { "maxBrier": 0.22, "minPredictions": 100, "alpha": 0.25 },
      { "maxBrier": 0.18, "minPredictions": 100, "alpha": 0.40 }
    ]
  }
}