Projects

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.

17.
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
18.
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
19.
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
20.
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
21.
Statistical Analysis of Trading Strategies (2026)
Research guide to rigorous backtesting, overfitting detection, and data-snooping correction — White's RC, Hansen SPA, PBO, CPCV, DSR, and Monte Carlo validation.
Research, statistical validation, backtesting methodology
22.
Risk Reports & Stop / Take-Profit Analysis (2026)
Interactive risk–return maps for 71 equity index strategies and 54 options ETF backtests, plus a stop-loss / take-profit sensitivity lab on ^GSPC.
Recharts, backtest aggregation, SL/TP experiment
23.
Hierarchical PCA and Modeling Asset Correlations (2026)
Dynamic clustering with Hierarchical PCA for sector-based equity portfolio management: statistical sign-pattern clusters and K-means on PCA loadings, following Avellaneda and Serur (2020).
HPCA · statistical clustering · K-means · Avellaneda & Serur (2020)
24.
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

Showing 17–24 of 28 projects

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