# Why the Risk-to-Reward Ratio is Overrated

Sometimes axioms are repeated over and over, and that is enough for many to accept them as fact. “No pain, no gain” – really? Would every doctor agree with that? “If it sounds too good to be true, then it probably is” – well, truthfully there are homes selling for \$1 now, so maybe that isn’t true either.

In trading, one of my favorites is “you must aim to get more profit than you risk on each trade.” Sometimes this is stated in other ways, such as:

“Always keep your reward to risk ratio greater than 1”

“Only take trades with a minimum of a 2:1 reward to risk ratio”

“If you aim for more than you risk, then you will make money.”

“A good reward to risk ratio ensures you to be profitable, winning more than you lose.”

Another way of stating this is that your reward to risk ratio must be greater than 1, or 2, or any other number that your favorite trading guru comes up with. Many traders have heard that it is desirable to have a high reward to risk ratio, and it certainly makes it easier for a trader to make money even if the trader has a low win percentage. However, there are many profitable traders who always risk more than they aim to secure in profits. The key to profitability for these traders is that they keep a high win rate.

An example may best illustrate how the reward to risk ratio is calculated:

Amber puts her stop loss at 1.3050, so her stop is 50 pips away from her entry.

Amber decides to enter a profit target of 1.3200, 100 pips away from her entry.

Thus, Amber is risking 50 pips to make 100 pips.

If we divide the possible gain by the possible loss, we get the reward to risk ratio.

100 pips profit / 50 pips risked = 2:1 reward to risk ratio

In other words, Amber has decided to keep her profit target further from her entry price than her stop loss. This certainly is understandable, but there are many other ways to make money trading. Keeping a good reward to risk ratio may increase your average win size and decrease your average loss size, but there are other statistics that determine your overall profitability, as a trader.

The most important statistics are as follows:

• Percentage of winning trades – W%.
• Percentage of losing trades – L%.
• Average gain on a winning trade – Ave W.
• Average loss of a losing trade – Ave L.
• Here’s why these statistics are important – with just these four statistics you can find out how good your trading system is, and thus decide if it is worth it to trade the system with real money. With these four statistics you can calculate expectancy of your trading system.

The formula is as follows:

Expectancy = (W% x Ave W) – (L% x Ave L)

The expectancy number tells you how much money you would expect to win over many trades. The best way to get these statistics is to backtest your trading strategy, or employ your trading strategy with a demo account. Do this for many, many trades (at least 50), and then plug in the numbers.

Let’s look at a trader, Jeff, as an example:

Let’s say that trader Jeff has a trading system that he backtests manually in a demo account for six months, with over 900 trades, and he gets the following statistics.

W% – 70%

L% – 30%

Ave W – \$200

Ave L – \$420

Calculating expectancy, Jeff sees that (0.7 x 200) – (0.3 x 420) = \$140 – \$126 = \$14. So, armed with this information, trader Jeff knows that if he takes 100 trades with his system, and the average winning trade is \$200, and the average losing trade is \$420, with a 70% win rate he is likely to have 70 winning trades, 30 losing trades and he will probably make \$1400. How does Jeff know this? He knows this because he knows that (70 x \$200) – (30 x \$420) = \$14,000 – \$12,600 = \$1,400.

This doesn’t mean trader Jeff will make \$1,400. This only means that we would expect him to make \$1,400 over 100 trades. Of course Jeff’s real results could be a little better or a little worse, but they are probably going to be very near \$1,400 after 100 trades.

Many traders, including myself, have gotten into trouble by simply focusing on one part of the equation.

• Traders who focus on win rate and forget about average loss size can get into trouble if their average loss gets too big.
• This is the sort of problem that many scalpers run into. Scalpers count on a high win rate. Without a high win rate most scalpers will lose money. This is because nearly every scalper, by definition, will look to take quick profits from the markets, however the scalper will often have a stop loss that is placed further away than the profit target, and this can spell trouble if the win percentage starts to slip. Some scalpers avoid this problem by letting some positions run for a while if they are exceptionally well-timed entries. This will dramatically increase the scalper’s average win and can really improve the odds of the scalper’s long term survival.

• Traders who focus on average win size can get into trouble if they let their win rate get too low.
• This problem is common with those traders who are focused on the reward to risk ratio. Sometimes traders become “slave to the reward to risk ratio.” Profit targets should be placed where the market is likely to go. Traders who focus too much on the reward to risk ratio can avoid this problem by defining profit targets using sound market analysis, and THEN calculating the reward to risk ratio.

There are many things to think about when backtesting your trading system – the reward to risk ratio will tell only part of the story. If you have a trading system that you think may work, backtest the strategy, and then calculate the expectancy. You may find that that the strategy makes money, even if the reward to risk ratio is not ideal.

Walter Peters, PhD is a professional forex trader and money manager for a private forex fund. In addition, Walter is the co-founder of Fxjake.com, a resource for forex traders. Walter loves to hear from other traders, he can be reached by email at walter@fxjake.com.

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