This book serves two purposes. First, it teaches the importance of using sophisticated yet accessible statistical methods to evaluate a trading system before it is put to real-world use. In order to accommodate readers having limited mathematical background, these techniques are illustrated with step-by-step examples using actual market data, and all examples are explained in plain language. Second, this book shows how the free program TSSB (Trading System Synthesis & Boosting) can be used to develop and test trading systems. The machine learning and statistical algorithms available in TSSB go far beyond those available in other off-the-shelf development software. Intelligent use of these state-of-the-art techniques greatly improves the likelihood of obtaining a trading system whose impressive backtest results continue when the system is put to use in a trading account. Among other things, this book will teach the reader how to:
โข Estimate future performance with rigorous algorithms
โข Evaluate the influence of good luck in backtests
โข Detect overfitting before deploying your system
โข Estimate performance bias due to model fitting and selection of seemingly superior systems
โข Use state-of-the-art ensembles of models to form consensus trade decisions
โข Build optimal portfolios of trading systems and rigorously test their expected performance
โข Search thousands of markets to find subsets that are especially predictable
โข Create trading systems that specialize in specific market regimes such as trending/flat or high/low volatility
More information on the TSSB program can be found at TSSBsoftware.com.