Permutation And Randomization Tests For Trading System Development
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Permutation and Randomization Tests for Trading System Development
This book provides the trading system developer with a powerful set of statistical tools for measuring vital aspects of performance that are ignored by most developers. All algorithms include intuitive justification, basic theory, all relevant equations, and highly commented C++ code for complete programs that run in a Windows Command Console. Reprogramming them in other languages should be easy, given the detailed explanations of each algorithm. The following topics are covered: Testing for overfitting at the earliest possible stage Evaluating the luckiness-versus-skill of a fully developed system before deploying it Testing the effectiveness and reliability of a trading system factory Removing selection bias when screening a large number of indicators Probability bounds for future mean returns Bounding typical and catastrophic future drawdowns Is the best indicator or model in a competition truly the best, or just the luckiest? Which markets provide truly superior profits for your trading system? What holding time for your system provides the best risk/return performance?
Statistically Sound Machine Learning for Algorithmic Trading of Financial Instruments
Author: David Aronson
language: en
Publisher: Createspace Independent Publishing Platform
Release Date: 2013
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: Estimate future performance with rigorous algorithms Evaluate the influence of good luck in backtests Detect overfitting before deploying your system Estimate performance bias due to model fitting and selection of seemingly superior systems Use state-of-the-art ensembles of models to form consensus trade decisions Build optimal portfolios of trading systems and rigorously test their expected performance Search thousands of markets to find subsets that are especially predictable 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 dot com.
Testing and Tuning Market Trading Systems
Build, test, and tune financial, insurance or other market trading systems using C++ algorithms and statistics. You’ve had an idea and have done some preliminary experiments, and it looks promising. Where do you go from here? Well, this book discusses and dissects this case study approach. Seemingly good backtest performance isn't enough to justify trading real money. You need to perform rigorous statistical tests of the system's validity. Then, if basic tests confirm the quality of your idea, you need to tune your system, not just for best performance, but also for robust behavior in the face of inevitable market changes. Next, you need to quantify its expected future behavior, assessing how bad its real-life performance might actually be, and whether you can live with that. Finally, you need to find its theoretical performance limits so you know if its actual trades conform to this theoretical expectation, enabling you to dump the system if it does not liveup to expectations. This book does not contain any sure-fire, guaranteed-riches trading systems. Those are a dime a dozen... But if you have a trading system, this book will provide you with a set of tools that will help you evaluate the potential value of your system, tweak it to improve its profitability, and monitor its on-going performance to detect deterioration before it fails catastrophically. Any serious market trader would do well to employ the methods described in this book. What You Will Learn See how the 'spaghetti-on-the-wall' approach to trading system development can be done legitimately Detect overfitting early in development Estimate the probability that your system's backtest results could have been due to just good luck Regularize a predictive model so it automatically selects an optimal subset of indicator candidates Rapidly find the global optimum for any type of parameterized trading system Assess the ruggedness of your trading system against market changes Enhance the stationarity and information content of your proprietary indicators Nest one layer of walkforward analysis inside another layer to account for selection bias in complex trading systems Compute a lower bound on your system's mean future performance Bound expected periodic returns to detect on-going system deterioration before it becomes severe Estimate the probability of catastrophic drawdown Who This Book Is For Experienced C++ programmers, developers, and software engineers. Prior experience with rigorous statistical procedures to evaluate and maximize the quality of systems is recommended as well.