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Mechanical trading systems - Weissman R.L.

Weissman R.L. Mechanical trading systems - Wiley publishing , 2005 . - 240 p.
ISBN 0-471-65435-3
Download (direct link): mechanicaltradingsystems2005.pdf
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Nondirectionally Biased Mean Reversion Day Trading
Typical duration of trade: minutes to hours
Example: RSI crossover
• Can capitalize on virtually any trading environment—trending, choppy, or mean reverting.
• No overnight margins and ability to “clear one’s head” at close of each trading day.
• More trading opportunities.
• With proper money management, each trade should risk small percentage of working capital.
• More decisions mean more stress.
• Smaller per-trade profits mean few vehicles are volatile and liquid enough to be profitable.
• Must fight tendency to overtrade or risk losing discipline and/or consistency.
• Off-floor disadvantage: loss of the bid/ask spread and/or higher commissions. Because such costs are fixed, as time frames are shortened, the viability of these strategies becomes marginalized.
System Development and Analysis
Benefits and Pitfalls
All truths are easy to understand once they are discovered; the point is to discover them.

Mechanical trading systems offer traders a multitude of benefits, including quantification of risk, reward, and assessment of percentage of winning trades prior to entry, along with a host of others. However, for every benefit, there are pitfalls to be avoided and/or (in some instances) accepted as the price paid for enjoyment of such benefits.
The first and most obvious problem in the system development process is that all decisions made regarding trading systems are based on historical data. Future market behavior will never look exactly like the past, and because all models are based on extrapolations from historical data, the best we can hope for is a strong positive correlation between past and future market behavior.
Because decisions regarding indicators and parameter sets for our trading systems are determined through our study of historical data, the methods used to ensure the robustness of our systems must address this limitation in the system development process. Although this statement seems so obvious that it is almost not worth mentioning, the ramifications of this simple truth are far-reaching and underestimation of this flaw leads to a significant number of the errors commonly committed in the system development process.

This section acts both as a comprehensive review of those benefits enjoyed by those employing mechanical trading systems and as an opportunity to examine other benefits not previously addressed.
The greatest benefit of mechanical trading systems is their ability to reprogram traders away from destructive types of behavior in favor of successful trading habits. Although this reprogramming process is typically a long and painstaking one, for those who have a single-minded desire to succeed (see Chapter 11), it is a powerful tool in tempering emotionalism as well as fostering discipline, patience, and adherence to principles of sound price risk management.
Another benefit enjoyed by those employing mechanical trading systems is quantification of risk and reward in general, along with the ability to quantify the risk/reward for an entire portfolio of assets. Without the quantification of risk and reward, performance forecasting is problematic. Moreover, although prudent price risk management is not dependent on utilization of a mechanical trading system per se, the ability to quickly compare historical results of a system to current performance and to determine whether these deviations are within normal tolerances or suggestive of a paradigm shift in market dynamics is invaluable to both traders and risk managers.
As stated earlier, because the mechanical trading systems showcased throughout this book are based on mathematical technical indicators, they require system developers to have significantly less specialized knowledge than other market participants regarding the underlying fundamentals affecting a particular market. Absence of this prerequisite expertise allows traders to apply their system or systems to trade various assets with negative and/or low correlations.
In addition, traders also can execute various transactions simultaneously in multiple systems exhibiting negative and/or low correlations, such as trend-following and intermediate-term mean reverting systems. Finally, because many mechanical system traders base entry and exit decisions on mathematical technical indicators, their performance typically will display a negative and/or low correlation to those of fundamental and/or discretionary technical traders.

Data Integrity Issues Revisited
To understand the performance tables presented throughout Chapter 3, I discussed two specific data integrity issues: methods of accurately back-
System Development and Analysis
testing futures contracts (which accounted for contract expiration issues) and point value versus percentage changes in the data history. Here I merely reiterate their importance in maintenance of data integrity. If either of these issues is germane to readers’ data history, please review that chapter.
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