Ernest P. Chan
Quantitative trader and author of chan-algorithmic-trading (2013) and its predecessor Quantitative Trading, which he describes as the beginner’s book — how to find strategy ideas, backtest them, automate execution, and size positions with the Kelly formula — where the 2013 book is “all about strategies.”
Between the two he ran a fund, and the preface reports what that changed: never manually override the model, prefer underleverage to overleverage “especially when managing other people’s money,” strategy performance itself mean-reverts, and “overconfidence in a strategy is the greatest danger to us all.” He says he came through the 2010 flash crash, the 2011 US debt downgrade and the 2011–12 European debt crisis “more confident than before” that the approach is sound.
His audience is the serious retail trader. He states it directly: fund management did not change that focus, and every strategy in the book is meant to be implementable by an independent trader without a seven-figure brokerage account. That places him against most of this spoke — trademaster is a university lab’s platform, banbot and tensortrade are frameworks for building systems, and quant-bible-mit-sloan is written to get people hired at firms. Chan is writing for someone trading their own money and telling them to keep the model simple.
Method. MATLAB, statistics over machine learning, and an explicit preference for “simple mathematical models” over data mining. His position on complexity is the corpus’s clearest counterweight to its ML-heavy centre of gravity (synthesis).
Connections
- author of chan-algorithmic-trading, published by john-wiley-and-sons
Related
chan-algorithmic-trading · mean-reversion · backtesting · erik-smolinski · synthesis