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You are here: Home / Connors Research / How to Select an Exit Method

How to Select an Exit Method

March 21, 2013 by Matt Radtke

You don’t make (or lose) money until you exit a trade, so having a precise, quantified exit method is crucial to generating predictable returns. Unfortunately, many published strategies either gloss over the exit rules completely, or they rely on vague directives such as “exit when you reach your profit target”. Since they don’t specify how to calculate a reasonable profit target, this is basically equivalent to saying “exit when you feel like you’ve made enough money”, which is not very helpful at all.

Both entry and exit rules can be thought of in terms of how strict they are, i.e. how easy or difficult they are to achieve. You might also say that strictness is a measure of how frequently or infrequently the rule conditions occur. For oscillators such as ConnorsRSI, values that are closer to the extremes (0 and 100) are more strict (less likely to occur) than values that are in the middle of the range. For moving averages, it is easier to cross a short-duration MA than a longer-duration MA.

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Stricter entry rules will be satisfied less frequently than more lenient entry rules, and thus a strategy that relies on the stricter rules will generate fewer trades than a strategy whose entry rules are more easily satisfied. With a robust strategy, the reward for fewer trades is generally a higher gain per trade, on average. For example, if you’re using a mean-reversion strategy that enters on a price drop, there will typically be a bigger bounce from a large pullback (stricter entry rule) than from a smaller pullback.

The strictness of exit rules has little effect on the number of trades generated by the strategy. However, just like the entry rules, stricter exit rules typically result in higher average profits. Why? Because stricter exit rules tend to keep you in your trades for a longer time, giving the strategy more time to work. Thus, for entries the tradeoff is between more trades and higher gains per trade, while for exits the tradeoff is between shorter trade durations and higher gains per trade.

For example, below is a subset of results from a strategy that we tested this week. Because this is a short strategy, we entered the trade after an increase in price, and tested exiting when the price fell below the 3, 5, or 10-day moving average. The entry rules for all three strategy variations shown here are identical; the only difference between them is the exit method.

The number of trades for all three variations is very similar. However, as we progress from the most lenient MA(3) exit to the strictest MA(10) exit, the average gain per trade increases by over 50% from 9.79% to 14.84%, while the trade duration nearly doubles from 2.20 to 4.25 days. The percentage of profitable trades also increases moderately, from 78% to 82%.

We observe this pattern over and over again in our testing. It applies to both mean reversion and trend following systems, whether those systems were developed for stocks, options or ETFs. Consider how it might affect your own quantified trading strategies.

Filed Under: Connors Research, Education Tagged With: Trading Lessons

About Matt Radtke

Matt Radtke is Senior Researcher for Connors Research. Mr. Radtke graduated magna cum laude from Michigan State University with a degree in computer science. He has 25 years of software development experience in companies large and small, including Hewlett-Packard and Bell Northern Research. Mr. Radtke has been actively trading stocks, ETFs, and options since 2008. Over the past several years he has become increasingly involved with the Connors Group family of companies, first as a student, then as a member of Chairman’s Club, and finally as a consultant, researcher, and author.
Matt has co-authored several quantified strategy guidebooks including ETF Trading with Bollinger Bands, Options Trading with ConnorsRSI, Trading Leveraged ETFs with ConnorsRSI, and ETF Scale-In Trading.

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