Featured projects in quantitative finance, portfolio construction, and systematic investing.
Each project applies quantitative methods to a specific problem in finance — from clustering-based portfolio construction and market regime detection to adaptive portfolio strategies and RRG-based rotation analysis.
Projects include interactive visualizations, source code links, and methodology explanations. Data is updated periodically via automated pipelines.
| 1. | Diversified Stock Portfolio Using Clustering Analysis (2024) S&P 500 portfolio construction using K-means clustering on risk/return features (correlation, beta, returns, volatility, Sharpe ratio). Backtested vs index. Python, K-means, backtesting | Active |
| 2. | Relative Rotation Graph (RRG) — US Equity (2025) Dynamic RRG for US stocks vs S&P 500. JdK RS-Ratio and RS-Momentum with animation. Python, yfinance, Recharts | Active |
| 3. | Adaptive Portfolio Strategies: Sequential Allocation Methods (2025) Comprehensive analysis of 14 sequential portfolio allocation strategies on diversified ETF portfolio. Includes momentum-based, reversion-based, and pattern-learning approaches with transaction cost analysis. Python, sequential optimization, backtesting | Active |
| 4. | Optimal Execution with RL Agent (DQN) (2026) Deep Q-Learning execution agent for slicing large orders under microstructure-style market impact. Compared against TWAP, passive, aggressive, and random baselines. Python, Gymnasium, Stable-Baselines3, execution simulation | Active |
| 5. | Fundamental Stock Analysis (2026) US large-cap fundamental analytics dashboard with deep cross-sectional ranking, distribution diagnostics, sector structure, risk/return mapping, and multi-factor composite interpretation. Python, fundamental screening, interactive charts | Active |
| 6. | Market Regime Detection Using Gaussian Models (2025) Comprehensive market regime identification across 21 global indices using Gaussian Mixture Models (GMM) and Greedy Gaussian Segmentation (GSS). Detects bull, bear, and transition regimes for adaptive portfolio management. Python, GMM, GSS, regime detection | Active |
| 7. | Stock Sentiment Tracker (2025) US equity sentiment tracker using VADER lexical analysis on financial news headlines. Tracks prices, sentiment scores, and correlations for S&P 500 stocks. Updated daily. Python, VADER, NLP, financial news APIs | Active |
| 8. | Yield Curve Intelligence (2026) Yield-curve research project built from yfinance market data: Nelson-Siegel fitting, slope/inversion diagnostics, and regime-aware risk context. Python, yfinance, Nelson-Siegel, macro risk signals | Active |
| 9. | Fama–French Factor Lab (2026) Unified factor dashboard: US FF5 and Carhart momentum, multi-asset ETF panel, international sleeve comparison, volatility regimes, risk budgeting, sleeve attribution, SPY research grid, and q-factor extension notes. Refreshed from Ken French + yfinance. Python, pandas, linear factor models, Ken French data, yfinance | Active |
| 10. | Smart Beta: Factor-Tilted Portfolio Construction (2026) One-year rolling study on a sector-balanced U.S. equity panel: equal weight, min variance, value tilt, and value–momentum blend with full risk and factor analytics. Factor models, portfolio construction, risk analytics | Active |
| 11. | Cross-section shrinkage lab (ETF panel) (2026) Yahoo Finance ETF panel: PCA spectrum, cross-sectional R² vs K, pseudo-OOS folds, ridge diagnostics. JSON from npm run data:shrinking-cross-section. Python, Recharts, PCA, shrinkage, cross-sectional R² | Active |
