QUANTITATIVE PRICE ANALYSIS
Probabilistic price projections, stochastic volatility cones, LPPL bubble detection, tail risk, regime classification, direction forecasts with accuracy tracking, model comparison, signal correlation, and cross-asset contagion mapping — computed on-demand for any stock, crypto, or futures contract.
WHAT YOU GET
WHAT'S INSIDE
Enter a dollar move, get probabilistic time estimates at 50/68/90/95% confidence. Uses the reflection principle for barrier-hitting at any point.
Close-to-Close, EWMA, Parkinson, Garman-Klass, Yang-Zhang. Applied universally. Regime detection with percentile ranking.
Three stochastic models producing probability cones. GARCH for vol clustering, Heston for stochastic vol, Merton for jump diffusion.
Log-Periodic Power Law from Sornette's critical crash theory. Multi-timeframe fitting with 4 JLS quality gates.
Generalized Pareto Distribution fitted to tail losses. VaR and Expected Shortfall at 95/99/99.5% confidence.
Hurst exponent, multiscale entropy, HHMM regime detection, wavelet decomposition. Reveals hidden structure in price action.
Ensemble of online-learning predictors across multiple timeframes. Tracked accuracy with 7d/30d/90d rolling windows and leaderboard rankings.
Public rankings of assets by forecast accuracy. Per-asset drill-down with prediction history, confidence calibration, and rolling accuracy trends.
Side-by-side accuracy across all model components. Cone calibration, composite sub-method scores, and model agreement analysis.
Pairwise agreement heatmap across 6 composite sub-methods. Signal independence analysis, top combinations, and fire rate timelines.
Pearson correlation of bubble signals between assets. Contagion clusters, lead-lag detection, and concurrent bubble timeline.
Granger causality for lead-lag relationships. Copula tail dependence for joint crash/rally probabilities across asset pairs.
UNDER THE HOOD
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