The recent influx of new speculators in the Forex trading market has been met with a similarly pronounced outflow of existing traders. Extremely volatile market conditions have clearly been detrimental to many participants, and much of this effect relates to popular trading strategies in the market today. In Part 1 of this article series, we discussed one of the major reasons for losses in the average Forex trading strategies: Poor money management. It is subsequently helpful to examine popular trading strategies and identify exactly where many traders go wrong — fixing mistakes in our own trading.

What Is Good Money Management in Forex Trading? Learning with Our RSI Trading Strategy

Good money management comes down to one all-too-popular trading aphorism: Let your profits run and cut your losses short. Almost every popular trading guide says this, but all too few give the reader good examples of what constitutes proper money management. Of course, part of the difficulty comes from the fact that there is no definite answer or definitive guide on what to do. Our job is to establish analysis techniques that allow us to determine what to do in specific situations.

For the purposes of this article, we will revisit one of the basic strategies discussed in our earlier introduction: the RSI Range Trading Strategy.

Our theoretical results for the RSI trading strategy show that it has lost money trading the EUR / USD throughout the past several years. Yet, it is likewise interesting to note that it lost the majority of its money in the latter half of 2008 to late 2009. In other words, our historical back test suggests that there have been periods of time in which the strategy has been profitable, and the trading ideas perhaps hold some merit. Our goal is to formulate a strategy such that our money management will protect us from substantial losses.

Before we do that, 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 previous 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. 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 big 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. The tests in our example are run using eSignal's EFS programming language and eSignal software.

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 shown below points out exactly how much in losses we incur and whether the trade is, in the end, profitable.

Our chart is revealing because it shows that trades with sizeable draw-downs very seldom result in winning positions. In fact, the maximum draw-down 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 especially small draw-downs — 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. For the purposes of our back-tested results on the Euro / US Dollar currency pair for our strategy, this level turns out to be a meager 35 pips. Such a number tells us that, as far as the RSI trading strategy is concerned, cutting your losses extremely short may make sense.

Unfortunately, our new protective stop-loss level was not enough to make our strategy profitable, but we do see notable improvement in the trading system's performance. In fact, the hypothetical equity curve shows that the strategy would have made respectable profits until late 2008 market volatility made for extremely challenging RSI range trading strategy conditions.

More importantly, we have learned something significant about the RSI range trading strategy — it lends itself well to short protective stop-loss levels. In fact, we will find that this is true of many range trading-style strategies. If we run similar analysis on other popular systems, we will find that they likewise benefit from small protective losses.

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.

*Reprinted (and modified) with permission from FXCM