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Testing and Tuning Market Trading Systems: Algorithms in
C++
BOOK DETAIL
Paperback: 332 pages Publisher: Apress; 1st ed. edition (October 27, 2018) Language: English ISBN-10:
148424172X ISBN-13: 978-1484241721 Product Dimensions: 7 x 0.8 x 10 inches Shipping Weight: 1.3
pounds (View shipping rates and policies) Customer Reviews:
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Book Description
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 live up 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 legitimatelyDetect overfitting early in developmentEstimate the
probability that your system's backtest results could have been due to just good luckRegularize a
predictive model so it automatically selects an optimal subset of indicator candidatesRapidly find
the global optimum for any type of parameterized trading systemAssess the ruggedness of your
trading system against market changesEnhance the stationarity and information content of your
proprietary indicatorsNest one layer of walkforward analysis inside another layer to account for
selection bias in complex trading systemsCompute a lower bound on your system's mean future
performanceBound expected periodic returns to detect on-going system deterioration before it
becomes severeEstimate 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.

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