This interview podcast features Aaron Fifield interviewing Dr. Ernest Chan, a quantitative trader with 15+ years of experience in finance. The conversation begins with Dr. Chan's unconventional path to trading, starting with AI research at IBM, and then delves into his trading strategies, which involve running multiple (7-8) diversified models across various markets (Forex, futures, stocks, options) to mitigate risk. Dr. Chan emphasizes the importance of diversification, the challenges of backtesting (data snooping bias), and the need to adapt strategies based on market conditions, rather than trying to predict regime shifts. He advises aspiring quantitative traders to start with simple strategies and gradually increase complexity, using tools like Excel spreadsheets before moving to programming languages like Python or R. Listeners gain insights into practical quantitative trading approaches and the importance of continuous adaptation and modification of trading strategies.
