Agentic coding skills for backtesting trading strategies using VectorBT. Supports Indian, US, and Crypto markets with realistic transaction cost modeling, TA-Lib indicators, QuantStats tearsheets, and 12 ready-made strategy templates.
An implementation of Giuseppe Paleologo's Rademacher Antiserum, designed to assess strategy performance consistency through Rademacher complexity and RAS-adjusted Sharpe Ratios. This code evaluates strategy robustness by applying Rademacher random vectors for anti-overfitting analysis.
Helix Treasury System
scikit-learn-compatible time-series cross-validation: purging, embargo, combinatorial purged CV, and deflated Sharpe ratios
Crypto-currencies (Bitcoin) trading & Transfer Learning applications
面向 A 股因子的可复现研究框架:信号 → IC / 分层回测 / walk-forward → Tear Sheet 报告
Systematic intraday opening-range breakout strategy on US equities — 10-year validated backtest with walk-forward optimization, statistical robustness suite, and live paper-trading on Alpaca.
一个面向 AI Agent / 量化实习的多智能体量化研究平台 / A resume-ready multi-agent quantitative research platform for AI Agent & Quant internships
Adversarial co-evolution orchestrator: an executor LLM improves an artifact, a deterministic scorer judges it (keep-if-better via git), a validator LLM advises — until quality peaks. Off-the-shelf agent CLIs, walk-forward scoring, live web dashboard. General-purpose, not just trading.
End-to-end quantitative trading system for Taiwan stocks — DoubleEnsemble model, 300+ factors, Walk-Forward backtesting, React dashboard
Portfolio backtest engine with montecarlo simulation, walk-forward, efficient frontier, FIRE, charts, performance optimization, max drowdown with Ai suggest!
Prove a trading edge survives real costs out-of-sample, or kill it. An honest edge-validation harness for CME micro futures & prop challenges.
Quantitative forex strategy research engine — 10 strategies, Optuna optimization, walk-forward + Monte-Carlo validation, honest overfit/ruin analysis. Pure Python.
Personal local quant trading + research platform — PIT factor composite (momentum / quality / value / PEAD) on the S&P 500, daily pipeline, paper execution, FastAPI + Next.js dashboard.
Quant research: early-breakout momentum on SP500 — 9.4% CAGR vs SPY's 7.9% on 26-year survivorship-bias-free backtest (1,081 historical constituents). Automated Alpaca paper trading. 305 tests. Not financial advice.
A股量化Alpha研究: 多因子选股 + LightGBM非线性因子挖掘, Walk-forward验证, 自动交叉验证检查
Utilized time series, statistic, ML and NLP models to practice. Topics include stock forecasting (algorithm trading), US 2024 presidential election and customer sentimental review.
Method to use rolling optimization with 3D LSTM arrays. Explores integrating multi-asset portfolio with embedding layer.
NFL forecasting engine — spread/ML/total/Wong-teasers with two-stage LightGBM + Monte Carlo, isotonic calibration, walk-forward backtest, and a native macOS desktop app.
SiraEdge Portfolio Optimization Module - Complete implementation with 7 optimization models, ML integration, and comprehensive documentation
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