192: “Predicting profitability using machine learning” – Ernie Chan
Better System Trader
English - June 15, 2021 16:01 - 54 minutes - 74.4 MB - ★★★★★ - 256 ratingsInvesting Business Education mechanical stockmarket forex futures investing markets profit stocks success swanscott Homepage Download Apple Podcasts Google Podcasts Overcast Castro Pocket Casts RSS feed
Previous Episode: 191: Combining Algos using State-Based Market Design – Richard Metzger
Quant trader Ernie Chan from PredictNow.ai joins us to discuss how to predict the profitability of trades using machine learning, including:
Unconditional probability and the problem with win% in backtest reports, Why “conditional probability” is much more useful for a trader and how to apply conditional probabilities to capital allocation, Why you should use Machine Learning for risk management and capital allocation only (and not for building trading strategies), Why feature selection and feature importance ranking are so valuable, Plus, the best ML techniques for prediction, how simple should trading strategies be, insights from cluster-based feature selection, do these techniques really work, ML as a crystal ball and much more!
Disclaimer:
Trading in the financial markets involves a substantial risk of loss and is not suitable for everyone. All content produced by Better System Trader is for informational or educational purposes only and does not constitute trading or investment advice. Past performance is not necessarily indicative of future results.