Co-founder and CIO2020 - PRESENTPrincipia Invest
Technologies: Python, Bloomberg API, Scikit-learn, AWS S3, DigitalOcean
- Managed a team of two researchers and a financial analyst who have researched and implemented multi-factor long-only US equities algorithms with an unsupervised learning portfolio optimization component. (CAGR 19% since 2008, Sharpe 1.1).
- Delivered a real-time implementation of a portfolio algorithm using Bloomberg API and Python on DigitalOcean hosted server and S3 data lake.
- Initiated a real-time database update on 1,500+ liquid US stocks including market, fundamental, and sentiment data.
Co-founder and Head of Consulting2018 - PRESENTHudson & Thames
Technologies: Python, MlFinLab
- Developed MlFinLab - a Python package for financial machine learning research. Managed at least six open-source Python developers.
- Participated in the development of ArbitrageLab - a Python package used to conduct a research in pairs trading, mean-reversion, and statistical arbitrage. Managed the cointegration approach and Kalman filter implementations.
- Assisted in the development of PortfolioLab - a Python package which contains various algorithms used in portfolio optimization,.
Senior Quantitative Researcher2018 - 2020Modex
Technologies: Python, Pandas, Apache Arrow, SQL, NumPy, Scikit-learn
- Researched and implemented a VIX futures trading strategy with an intraday hedging component (1-Minute Bars) (40% ROC since January 2019 and Sharpe ratio 2.2 in the 2012-2019 backtest period).
- Managed a back-end engineer and quantitative developer who designed and implemented a high-performance proprietary backtesting platform (Apache Arrow, Parquet, Hadoop stack) with a team of software developers.
- Improved the existing FX strategy (increased Sharpe ratio from 0.7 to 1.2 in the 2010- 2019 backtested period with 12% ROC since August 2018 in real-time trading).
Quantitative Researcher2016 - 2018Integral Capital Management Sarl
Technologies: Python, SQL, Scikit-learn
- Implemented an index option trading strategy (13% ROC for six months of trading, backtested performance: 30% CAGR with 23% volatility for the 2010-2017 backtest period).
- Participated in creating a proprietary API for multithreading financial data preprocessing and feature generation in Python.
- Implemented a quantitative market ETF management strategy with monthly rebalance (CAGR 11%, Sharpe 1.0 in the 2008-2017 period).