How do we Set Stops for Range Trading Strategies?

This installment of our Money Management series looks to the benchmark Relative Strength Index (RSI) strategy to determine proper trading techniques for range trading strategies. In our last article we used algorithmic trading software to find the optimal risk/reward profile for a trend-following strategy. It should come of little suprise that range trading systems are substantially different, and we hope to gain a better understanding money management for such different trading techniques.

What is good money management in forex trading? Learning with our RSI Trading Strategy

Possibly everyone that has ever written about money management has said the same thing: let your profits run and cut your losses short. Of course, all too few give proper examples of what this actually means, and our goal is to gain a better understanding of specific examples using the RSI strategy. We will use this as a general guideline as to the trading characteristics of other similar range trading strategies.

For the purposes of this article, we will revisit one of the basic strategies discussed in our earlier introduction: the RSI Range Trading Strategy on a 60min USDCHF chart. Using FXCM’s Strategy Trader software, we will load a standard RSI strategy available here on our FX Programmers Wiki page.

In order to ensure we have several years of backtesting data available, view a video on importing additional data into the Strategy Trader platform: how to import historical data into Strategy Trader.

Our theoretical results for the RSI Trading Strategy on the USDCHF show that the system performed relatively well in recent years. Extended periods of outperformance dominate as our theoretical equity curve shows long runs of steady gains. Yet much of those gains would have disappeared through times of significant market turmoil, and we see years such as the infamous 2008 produce noteworthy pullbacks in our theoretical equity curve. Such sharp declines suggest that this strategy could improve with money management techniques.

Before we explore specific adjustments, however, it is useful to think about the general concepts behind our RSI trading strategy. Namely, we will buy the currency pair when it bounces from oversold territory and sell it when it drops below overbought territory. In a sense we’re attempting to pick tops and bottoms based on previously advances and declines—looking for a retracement move every time.

Conceptually this makes sense: buy a currency when it has run out of its bearish steam and vice versa. In practice, however, we can see that the strategy will most often lose big if price stays in overbought or oversold territory for extended periods of time. In thinking about the general concepts behind our strategy, we can already identify one potential flaw: the strategy will suffer especially large losses during extended overbought or oversold periods.

How do we protect against this?

Given that we know the strategy will have particularly large losses, we can set protective stop-loss orders to preserve capital. But where do we place them? Our next task is to keep a very good track record of our trades and adjust them accordingly. Our RSI strategy is simple enough such that we can easily automate it using different types of software and test accordingly. Using FXCM’s Strategy Trader software, we will load a standard RSI strategy available here on our FX Programmers Wiki page.

View a video guide on strategy backtesting and optimization in Strategy Trader here:

Basic Backtesting Optimization

Setting Stops for our RSI Forex Trading Strategy

The single most important factor in determining where to set our stops is how far adrift a trade usually goes before becoming profitable. Clearly we want to set our protective stop loss at a level such that it will protect us but not interfere with successful trades. As such, we’ll look for the “Maximum Adverse Excursion” of profitable trades and set stops accordingly. The chart below shows exactly how much in losses we incur and whether the trade is, in the end, profitable.

Any trade that has drawn down more than $300 has never turned a profit.

Our chart is revealing, as it shows that trades with sizeable drawdowns very seldom result in winning positions. In fact, the maximum drawdown suffered by any single winning trade was approximately $300, or 300 pips. We immediately see that our stop loss should be, at maximum, 300 pips away—having zero effect on our percentage-profitable rate and saving us from substantial losses. More importantly, however, we see that the vast majority of profitable RSI trades have small drawdowns—arguing for similarly tight money management.

The next step would be to identify which stop loss level is optimal for our particular trading strategy and trade accordingly. Using the strategy optimization tools available in the Strategy Trader software, we examine which stop-loss would give us the greatest theoretical “Return on Account”.

“Return on Account” in Strategy Trader gives us the percentage by which net-profit exceeds maximum drawdown. Thus we can get a sense for the best risk-adjusted returns of our strategy by stop loss using the software’s optimization techniques.

According to our theoretical strategy optimization results, this strategy begins to do best when one uses a hard stop of approximately 250 pips. This level theoretically allows trades sufficient room to run astray before reaching their objective.

Now that we know which stop level should theoretically give us the best results in trading the RSI Strategy on the USDCHF, we will now look to take-profit levels.

The chart above tells us that our strategy theoretically performs best with a take-profit level of approximately 220 pips—roughly equal with our optimal stop-loss level of 250 pips. In other words, a risk-to-reward ratio of approximately 1:1 has done reasonably well for the RSI strategy on the US Dollar/Swiss Franc pair.

Such a risk profile stands in stark contrast to the Moving Average Crossover Strategy we discussed in our last article, and it underlines key differences in two very different trading styles. Whereas the Moving Average system depended on low-probability but high-profitability trades to perform well, our simple oscillator RSI depends on frequent and smaller gains to succeed.

Though it is critical to note that what worked in the past is no guarantee of what may work in the future, recognizing the different characteristics of these two trading styles can be quite useful in one’s own trading.

What’s the Moral of the story?

With our money management analysis techniques in hand, we can apply this to almost any strategy. Obviously it is a good deal more work to perform this analysis on anything that is not easily automated, but it is all the same important to keep close tabs on your particular trading style. If you trade ranges, do your trades follow a similar profile? If you think there is an appropriate protective stop loss level for your strategy, it is relatively easy to monitor your charts or demo trade your idea to confirm that it will work. Paying much closer attention to your trading system will teach you everything there is to know about your strategy—highlighting strengths and, perhaps more importantly, weaknesses.

View previous articles in this series:

How do we use Money Management for Moving Average Forex Strategies?

Written by David Rodriguez, Quantitative Strategist for DailyFX.com

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