How and when should you exit a trade? Most articles about trading center around when to buy (or sell short) or how to deal with the psychological aspects. Hardly anything can be found about exits, even though when to exit a trade is probably just as important as the entry. How and when should you exit a trade? What method should you use to exit a trade? What is the best time to close a trade? When to exit a trade? How long should you wait until you exit? This article looks at 5 trading exit strategies.
This article summarizes the 5 exit strategies in trading. 5 main methods of how to exit or close your trading strategies, and we provide multiple examples of how and when to exit a trading strategy. At the end of the article, we do a test by entering randomly but adjusting the exit variable.
How important is it to know when to exit a trade?
Let’s illustrate the importance of exits with some anecdotal evidence from the training course of the proprietary trading firm Bright Trading.
When we started full-time trading 20 years ago, something we covered in our 26 trading lessons, Bright Trading taught its traders how to make money by being on the same side as the specialist. Bright’s course taught the traders how to send opening-only (OPG) orders in a basket of NYSE stocks before the opening each day. This could be done by sending a limit order above and below the estimated opening price in the expectation that you would get a price improvement when the (or if) the specialist opened the stock high or low.
For example, if you sent a short order at 50.13 USD you might get filled at 50.25 instead. If the stock opened lower, the order would automatically cancel and you’d get no shares. Without going into details, this simple strategy worked very well until the financial crisis in 2008/09. We traded this strategy well for many years, while others failed.
The interesting thing is that all traders in Bright’s course had the exact same entry, yet some traders were unsuccessful while others made huge amounts of money. The difference is due to money management, position-sizing, and when and how you exit a trade. The latter is probably the most important. This shows how it can be worthwhile to spend some time on the exits and not only on the entry.
What is the best exit strategy in trading?
We emphasize that there is no best exit strategy in trading except one rule: keep it as simple as possible. The more variables you include in an exit strategy, the more likely you are to curve fit your backtests.
Moreover, the exit depends on the strategy. If you have a short-term mean reversion strategy, it makes sense to sell on strength. Opposite, in a longer trend-following strategy it might make sense to exit on weakness, ie. when the trend is changing.
Hence, we can safely conclude there is no best exit strategy in trading.
Different trading exit strategies
There are, of course, almost unlimited ways to exit a position in trading. Below is a description of the most common techniques of how to exit a trade:
Trading exit strategy 1: An exit based on parameters/variables
When you backtest a trading idea, you use some strictly defined variables about how and when to enter a trade. This could for example be to buy at the close when the two-day RSI is below 10.
When simulating this trading strategy you can employ the “opposite” sell signal: sell when the two-day RSI is above 90. If you backtest this on the S&P 500 since 1993 on the oldest ETF around (SPY) you get this equity curve if you invested 100 000 and compounded/reinvested until September 2021:
The number of trades is 226, the average gain is 1.05% per trade, the max drawdown is 37%, and the profit factor is 2.1. The exposure time, the time spent in the market, is quite high at 38%, and the reason for that is the relatively high threshold of when to exit. A two-day RSI is of 90 is high and “forces” you to stay in a trade for a reasonably long time.
Let’s change the exit threshold and test any level when the two-day RSI is higher than 50 with intervals at 5 (while keeping the entry variable the same):
The total return is lower, but the losses and suffering along the way are reduced: the max drawdown is 24%. You get slightly more trades (303), but the time spent in the market is reduced a lot (14%).
By playing around you can see how the different exit criteria changes as the exit variable is changed.
Trading exit strategy 2: Time-based exit
This is one of the simplest possible exits there is. You simply exit after a certain period of time, be it minutes, days, months, or n bars. A time-based exit might be simple, but it’s still one of the most efficient exits you can use. We regard a time exit as a very underrated exit parameter.
One other advantage with a time-based exit is reduced drawdowns. Such an exit makes sure you spend just a small amount of time in the market, and you additionally get out early if it’s just a beginning of a bear market.
Yet another advantage with a time-based exit is the lack of curve fitting. There might be better ways to spend your time than to optimize the exit, and time-based exits are simple but very efficient. We emphasize again the importance of simplicity in trading: the simpler you make it, the more robust it is.
Let’s continue with the trading strategy above: we enter if the two-day RSI crosses below 10, but we sell after x days.
The equity curve with a time-based exit of five days looks like this:
Of the three different exits we have thus far covered in this article, a time-based exit of five days has returned the most, although the log scaled chart shows diminishing returns over the last decade.
Read more about drawdowns in these two articles:
Trading exit strategy 3: Stop-loss exit
Endless books and articles have covered the importance of stop losses. Despite all this, we rarely see a strategy that improves with a stop-loss. Of course, one of the aims of a stop-loss is to avoid the risk of ruin, but this problem you can address by using other techniques.
We have covered stop-loss at length in another article which sums up our take on the issue:
Let’s test our original strategy again (entry <10 and exit >90) but implement a stop-loss.
The table below shows the result for all stop-loss levels (column 2):
We tested stop-loss levels from 1 to 10 percent with 0.5% intervals. The only stop-loss level that improved the original trading strategy is 8.5%. This is a very wide stop-loss and we can argue it’s not a stop at all. As you can see, all the other stop-loss thresholds made the strategy perform worse.
A stop-loss can also be a certain amount of money, for example, 1 000 USD.
One of the aims of stop-loss is to reduce the total drawdown of a strategy. Does the above stop-losses reduce drawdown? No, only if you use a very tight stop-loss of 2% or lower. Unfortunately, you then cut winners short and end up making less money, illustrating the trade-offs in trading. There is no free lunch!
Trading exit strategy 4: Trailing stop exit
A stop-loss can be both static and dynamic. If it’s dynamic we can call it a trailing stop.
A trailing stop starts with a fixed level below your entry price, but the trailing stop moves up if the price goes in your desired direction. However, if the price falls, you don’t lower the price, but you exit at the trailing stop if your stop is hit.
Depending on the price movement, a trailing stop starts as a stop-loss but could end up as a “profit stop”.
Our research indicates, again, that the benefits of a trailing stop are negligible or close to non-existent.
Let’s return to our original strategy and implement trailing stops at certain levels:
Not shown in the table is max drawdown. By using a tight trailing stop at 6% or lower, the max drawdown is reduced to 20% or lower, but at the expense of much less total profits.
Trading exit strategy 5: Target exit
The last exit method we’ll show today is a profit target.
Again, we run our original strategy of buying if the two-day RSI is below 10 and selling when the two-day RSI ends above 90:
The second column shows the different levels of profit target: from 1 to 10% with 0.5% intervals. There are no other stops. Yet again the total profits don’t manage to beat the original strategy for any of the target levels. Max drawdown was for all levels between 30 to 40%, more or less in line with the original strategy.
If you want to read more about profit targets, please read our full article about profit targets:
Combining many trading exit strategies
You might argue you can combine a normal exit with both stop-loss and a profit target, for example. Our experience indicates that this is not a good idea.
First, you risk curve-fitting your strategy because of the increased number of variables. Second, you are likely to cut your winner shorts.
However, one option instead of a stop-loss is to use a time stop together with a “normal” exit:
Combining a variable exit and a time-based exit
The last twist we’ll use in this article is a combination of using both a regular exit and a time-based exit. If the exit variable is not triggered within x number of days, then we exit by the defined time-based exit.
The rules are like this: we enter when the two-day RSI is below 10, and exit when the RSI is above 90. We set a time-based exit of x days:
Column two shows the different exits in bars after entry. The table shows that the strategy improves by using a time-based exit between 8 and 10 days. Not only is the profits bigger, but the max drawdowns are reduced significantly.
Is this curve fitting? No, we don’t think so. You are buying on short-term weakness and you want to see the trade go your way quickly or get out. You want to give the strategy x days to work out, but if it doesn’t work out within n days you exit. The idea is simple but reasonably efficient.
One of our subscription services, the monthly Trading Edges, uses this combination occasionally.
A random entry but variable exit strategy
Let’s end the article by removing the entry variable to a random one. By using the random function in Amibroker we can simulate a strategy many times. However, we keep the exit criterium: that the two-day RSI must be higher than 90.
When we use a random entry, we get a different sequence every time – like a Monto Carlo simulation. One of the simulations gave this equity curve:
The CAGR is 7% with 47% of the time spent in the market. We simulated many times, and we can conclude a random entry doesn’t generate the same good result as our non-random entry. However, it shows that the exit is an important variable to create good trading strategies.
Amibroker code and course
Amibroker is a very powerful tool despite its cheap price. It works both for backtesting and live trading, especially with Interactive Brokers. How you can learn to code, do backtests, and live trading is described in our Amibroker course.
Conclusions: How and when should you exit a trade?
As with most things in trading, there are no rules that work well all the time and no hard rules for when to exit a trade. Most traders spend less time on exits than on entries, but the exit is just as important and should be considered just as rigorously as the entry.
Our simple tests in this article show that simplicity gets you a long way. Adding stops rarely add value to a strategy, except for time-based stops. Time stops work well with “normal” exit variables.
What are the challenges associated with exit strategies in trading?
Exit strategies in trading pose challenges, as evidenced by the anecdotal evidence from Bright Trading. Traders with the same entry point experienced varying levels of success due to differences in money management, position sizing, and the timing and method of exiting a trade.
Is there a one-size-fits-all exit strategy in trading?
No, there is no universal exit strategy in trading. The most important rule is to keep exit strategies as simple as possible. The effectiveness of an exit strategy depends on the specific trading strategy employed, whether it’s short-term mean reversion or a longer trend-following approach.
What are the common methods for exiting a trade based on parameters/variables?
One common method is to exit based on predefined parameters or variables established during backtesting. For example, selling when the two-day RSI is above a certain level. The article provides insights into how adjusting these exit variables can impact the strategy’s performance.