Using Statistical Analysis to Develop Intelligent Exits


When most traders develop mechanical trading systems, they spend 90 percent of their time developing the entry signals. The exit signals are usually less complex and are tested only in combination with the entries. Unfortunately, this process does not develop optimal exits for a given system and market. This chapter discusses how to develop properly designed exit signals, using various statistical methods.


The underlying logic between developing entry and exit signals is different. When developing entry signals, we are trying to find a set of conditions that statistically produces a good risk–reward ratio when taking a position in a given direction. To judge how predictive an entry rule is, I use the set of primitive exits shown in Table 9.1.

Test your entry rules using different values of N for each of the primitive exits defined above. This will allow you to evaluate how well a given entry rule works in predicting future market direction. It is easy to understand the logic needed to develop and test entry rules. The problem with developing exit rules is that the logic is not as easy to define because there are many reasons to exit a trade. The exit development process requires mixing money management and technical information about a system for a given market. For example, ...

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