Projects

A collection of quantitative trading strategies and financial models. Each project includes comprehensive backtesting, risk metrics, and methodology documentation.

Signal SystemRandom ForestGaussian Copula

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)
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Quantitative TradingMachine LearningPython

Proprietary Custom Models

Quantitative research library: factor models, mean reversion systems, VaR/CVaR risk analytics, and portfolio construction. LoRA-fine-tuned LLMs for calibrated probability estimates; VL-JEPA for temporal pattern recognition. Multi-asset regime detection, 95% confidence intervals, audit trails—built for deployment where explainability and compliance matter.

Type
Research Library
Focus Areas
Trading, Risk, Optimization
Asset Classes
Equities, Futures, Crypto, ETFs
ML Techniques
Ensemble, Neural Networks, Statistical
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