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Game Theory Panel

Adverse selection · depth · regime · overhang · crowding demo data

Game Theory Score

What is driving it

VPIN toxicity
Kyle λ · depth
Regime
Crowding

Cost basis & overhang

Grinblatt & Han (2005). The reference price is where the average share actually changed hands, not a moving average. Because holders sitting on gains supply into strength, price underreacts first and drifts after — which is where momentum comes from.

Microstructure detail

Kyle (1985) / Glosten-Milgrom (1985). λ is the slope of the market maker's pricing rule and 1/λ is depth. VPIN is how one-sided flow is — the adverse selection he is pricing. High readings mean trade smaller, not backwards.

Execution planner

Almgren et al. (2005) square-root law; Almgren-Chriss (2001). Your own order is order flow, and the market prices it exactly as it would price an insider's. impact ≈ σ·√(Q/ADV). Spreading over D days cuts total cost by √D.
Embedding this in liquidityllama.com
// The engine is a standalone global — no build step, no dependencies.
const snap = LLGameTheory.snapshot(closes, volumes, {
  intraday: false,          // true for crypto/futures intraday bars
  sharesOutstanding: null   // pass it for equities to get a real turnover rate
});

snap.gts        // -100..+100 conviction dial
snap.stance     // 'long' | 'short' | 'flat'
snap.regime     // 'trend' | 'revert' | 'random_walk'
snap.crowding   // { score, crowdedSide, payoffInversion }

// Full series for charting:
const full = LLGameTheory.gameTheoryScore(closes, volumes);
full.gts                        // Float64Array
full.diagnostics.referencePrice // Grinblatt-Han cost basis line

// Screener use: rank a watchlist by conviction with clean liquidity.
rows.sort((a,b) => b.gts - a.gts)
    .filter(r => r.microstructure.vpinPercentile < 80 && !r.crowding.payoffInversion);

Every number here is derived from published models, each cited on the panel it appears in. These are descriptions of market state, not predictions, and none of this is investment advice. Percentile readings need a long history to mean anything — treat anything computed on fewer than ~250 bars as indicative only.

Coming soon · invite-only

Run this on your own charts

The same logic as this page, as TradingView scripts: LL Game Theory Score plots order-flow toxicity, Kyle's lambda, crowding and disposition overhang.

Invite-only. Published as a protected script — access is granted per TradingView username, so the source stays closed. Link goes live once it’s uploaded.