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the other related kinds of information useful in assessing a trading system on a whole portfolio of commodities or stocks at once is made evident. The process of conducting portfolio-wide walk-forward and other forms of testing and optimization is also described. For example, instruction is provided on how to search for a set of parameters that, when plugged into a system used to trade each of a set of commodities, yields the best total net profit with the lowest drawdown (or perhaps the best Sharpe Ratio, or any other measure of portfolio performance desired) for that entire set of commodities. Small institutional traders (CTAs) wishing to run a system on multiple tradables, as a means of diversification, risk reduction, and liquidity enhancement, should find this discussion especially useful. Finally, to keep all aspects of the systems and components being tested objective and completely mechanical, we have drawn upon our academic and scientific research backgrounds to apply the scientific method to the study of entry and exit techniques. In addition, when appropriate, statistics are used to assess the significance of the results of the investigations. This approach should provide the most rigorous information possible about what constitutes a valid and useful component in a successful trading strategy. So that everyone will benefit from the investigations, the exact logic behind every entry or exit strategy is discussed in detail. For those wishing to replicate and expand the studies contained herein, extensive source code is also provided in the text, as well as on a CD-ROM (see offer at back of book). Since a basic trading system is always composed of two components, this book naturally includes the following two parts: The Study of Entries and The Study of Exits. Discussions of particular technologies that may be used in generating entries or exits, e.g., neural networks, are handled within the context of developing particular entry or exit strategies. The Introduction contains lessons on the fundamental issues surrounding the implementation of the scientific approach to trading system development. The first part of this book, Tools of the Trade, contains basic information, necessary for all system traders. The Conclusion provides a summary of the research findings, with suggestions on how to best apply the knowledge and for future research. The Appendix contains references and suggested reading. Finally, we would like to point out that this book is a continuation and elaboration of a series of articles we published as Contributing Writers to Technical Analysis of Stocks and Commodities from 1996, onward.
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Jeffrey Owen Katz, Ph.D., and Donna L. McCormick
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There is one thing that most traders have in common: They have taken on the challenge of forecasting and trading the financial markets, of searching for those small islands of lucrative inefficiency in a vast sea of efficient market behavior. For one of the authors, Jeffrey Katz, this challenge was initially a means to indulge an obsession with mathematics. Over a decade ago, he developed a model that provided entry signals for the Standard & Poor s 500 (S&P 500) and OEX. While these signals were, at that time, about 80% accurate, Katz found himself secondguessing them. Moreover, he had to rely on his own subjective determinations of such critical factors as what kind of order to use for entry, when to exit, and where to place stops. These determinations, the essence of discretionary trading, were often driven more by the emotions of fear and avarice than by reason and knowledge. As a result, he churned and vacillated, made bad decisions, and lost more often than won. For Katz, like for most traders, discretionary trading did not work. If discretionary trading did not work, then what did Perhaps system trading was the answer. Katz decided to develop a completely automated trading system in the form of a computer program that could generate buy, sell, stop, and other necessary orders without human judgment or intervention. A good mechanical system, logic suggested, would avoid the problems associated with discretionary trading, if the discipline to follow it could be mustered. Such a system would provide explicit and well-defined entries, normal or profitable exits, and abnormal or money management exits designed to control losses on bad trades, A fully automated system would also make it possible to conduct historical tests, unbiased by hindsight, and to do such tests on large quantities of data. Thorough testing was the only way to determine whether a system really worked and would be profitable to trade, Katz reasoned. Due to familiarity with the data series, valid tests could not be performed by eye. If Katz looked at a chart and believed a given formation signaled a good place to enter the market, he could not trust that belief because he had already seen what happened after the formation occurred. Moreover, if charts of previous years were examined to find other examples of the formation, attempts to identify the pattern by eyeballing would be biased. On the other hand, if the pattern to be tested could be formally defined and explicitly coded, the computer could then objectively do all the work: It would run the code on many years of historical data, look for the specified formation, and evaluate (without hindsight) the behavior of the market after each instance. In this way, the computer could indicate whether he was indeed correct in his hypothesis that a given formation was a profitable one. Exit rules could also be evaluated objectively. Finally, a well-defined mechanical trading system would allow such things as commissions, slippage, impossible tills, and markets that moved before he
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xvi could to be factored in. This would help avoid unpleasant shocks when moving from computer simulations to real-world trading. One of the problems Katz had in his earlier trading attempt was failing to consider the high transaction costs involved in trading OEX options. Through complete mechanization, he could ensure that the system tests would include all such factors. In this way, potential surprises could be eliminated, and a very realistic assessment could be obtained of how any system or system element would perform. System trading might, he thought, be the key to greater success in the markets.
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