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Signal SystemRandom ForestGaussian CopulaMHCICTAlpha GenerationMulti-AssetPythonQuantitative FinancePortfolio Optimization
Financial Forecasting Signal System
Alpha signal system combining Random Forests and Gaussian Copulas across 31 assets (equities, crypto, forex). Delivers 62% 1-month hit rate with tail-aware dependency modeling via 10K Monte Carlo simulations. Institutional Trading Concepts (ICT) integration for precise entry/exit levels—risk-reward 1:1.3 to 1:2.5. Manifold-constrained clustering for sector coherence. Generates signals for systematic execution.
Type
Signal
Statistical Models
Gaussian Copula
Style
Mixture of Experts
Assets
31 (Equities, Crypto, Forex)
# Methodology
• Random Forest Model: Implements 100-tree ensemble learning with 15 engineered features including moving averages, RSI, MACD, Bollinger Bands, ATR, and volume indicators. The model achieves 62% 1-month hit rate with risk-adjusted alpha generation across 31 assets.
• Gaussian Copula: Models asset dependencies and correlations using 10,000 Monte Carlo simulations. Captures non-linear relationships and tail dependencies between assets, providing robust portfolio optimization and risk management insights.
• Manifold Constrained Hierarchical Clustering: Uses Isomap embedding to preserve geodesic distances in 3-5 dimensional manifold space. Applies sector coherence constraints and momentum persistence analysis for improved clustering stability.
• ICT Integration: Incorporates Institutional Trading Concepts including liquidity zones, order flow analysis, order blocks, and kill zones. Provides precise entry/exit levels with risk-reward ratios of 1:1.3 to 1:2.5.
• Gaussian Copula: Models asset dependencies and correlations using 10,000 Monte Carlo simulations. Captures non-linear relationships and tail dependencies between assets, providing robust portfolio optimization and risk management insights.
• Manifold Constrained Hierarchical Clustering: Uses Isomap embedding to preserve geodesic distances in 3-5 dimensional manifold space. Applies sector coherence constraints and momentum persistence analysis for improved clustering stability.
• ICT Integration: Incorporates Institutional Trading Concepts including liquidity zones, order flow analysis, order blocks, and kill zones. Provides precise entry/exit levels with risk-reward ratios of 1:1.3 to 1:2.5.
Core Model
Random Forest + Gaussian Copula + MHC + ICT
# Data Source
Yahoo Finance, Alpha Vantage, Real-time Market Data