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Highlights of 2020 Developed forecasting system for hotel room supply and demand for COVID workstream in my previous day job. That’s meaningful! Quit my data scientist job in middle of 2020 to try and pursue a quantitative finance, systematic trading path. Spent the next half of year exploring and building up infrastructure for fully automated algorithmic trading and portfolio management. Deployed 3 trading strategies with 1 currency hedging feature.

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Medium links to write-up on fully automated algorithmic trading and portfolio management infrastructure Algorithmic trading infrastructure for non options and options strategies Designing, Building and Deploying a Fully Automated Algorithmic Trading System: link How to place option spread (e.g. straddle) through Interactive Brokers API, a 101 tutorial: link Performance monitoring features in fully automated algorithmic trading and portfolio management infrastructure Developing a performance monitoring component in my fully automated algorithmic trading system (part 1): link

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Testing github gist

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Trend following strategy in futures using non binary forecasts Project motivation As David Ricardo, a British economist in the 19th century once said, ‘cut short your losses and let your profits trend’ allude to the point that trend following as a profitable strategy could exist even back then. Having read AQR’s papers on the Time Series Momentum (TSMOM, I am keen to explore this topic in the futures space (Moskowitz, T.

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Developing a performance monitoring system for my algorithmic trading system It’s one thing to backtest your signals and forecasts on historical data but it’s a completely different animal in terms of execution. I have written about this here. Another important component of setting up an algorithmic trading system is performance monitoring. Some important questions I had in mind while developing this component, How do I measure my slippage? Commissions paid?

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