Reward and risk. Destroying stereotypes

Reward and risk. Destroying stereotypes

We welcome all readers of our blog! In our today’s article we will try to destroy the well-established stereotypes in the interpretation of such an indicator of the trading system efficiency as the risk-reward ratio.

In this article:

  • False stereotypes in understanding reward and risk.
  • Trading efficiency depends on a complex of indicators.
  • Example of calculation of expectancy in trading.
  • Conclusions.

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False stereotypes in understanding reward and risk

Any false statement in the end is accepted by the majority of people as a generally accepted truth if it constantly does the rounds by well-known and respected people.

The trader environment is not an exception. Let’s list some well-established statements, relating to the risk management, which bore to death and are a pain in the neck:

“Reward-to-risk ratio should be higher than 1”.

“Open trades with the reward-to-risk ratio being not less than 2 to 1”.

“High reward-to-risk ratio guarantees your success in the market”.

Quite often we listen to gurus of trading absolutely without thinking that they place emphasis incorrectly. Such statements confuse beginner traders. It goes without saying that the high reward-to-risk (R:R) ratio helps many traders to make money in the market even in the event of a low percentage of profitable trades. Nevertheless, there is a big number of successful traders who always take a higher risk in a trade than the expected profit. Their success is explained by a high win rate (if you want to better understand such concepts as the risk-reward ratio and win rate, we recommend you to read the Risk-reward ratio. How to use these indicators correctly article).

Trading efficiency depends on a complex of indicators

Good R:R ratio may increase the average size of a profit and decrease the average size of a loss, but, in fact, everything depends on the considered trading system. Trading profitability is shaped not by ONE but by several statistical indicators.

Here are the most important of them:

Percentage of profitable trades — W%.

Percentage of loss-making trades — L%.

Average gain from a profitable trade – avg. W.

Average loss from a loss-making trade – avg. L.

Only on the basis of a sufficient number of statistical indicators we can make conclusions about the trading strategy profitability. Now let’s calculate EXPECTANCY of the trading system:

In order to obtain a more or less adequate statistics, you need to execute not less than 100 trades. The more trades you execute, the more reliable data you obtain.

EXPECTANCY = (W% х avg. W) — (L% х avg. L)

EXPECTANCY shows what pofit, most probably, a trader would receive after a long series of trades. In order to obtain all necessary data for determining the profitability of your trading strategy, conduct the forward test of the system on the demo account with the help of the ATAS platform.

Example of calculation of expectancy in trading

Let’s assume that John the trader has developed his own trading system and decided to test it on the demo account. Having traded for six months and executed more than 900 trades, he obtains the following statistics:

W% — 70%;

L% — 30%;

Avg. W — USD 200;

Avg. L — USD 420.

John calculates expectancy with the help of simple arithmetic using our formula: (0.7 х 200) — (0.3 х 420) = USD 140 — USD 126 = USD 14. John can make a conclusion on the basis of the obtained statistics that if he executes 100 trades using his system, the average profitable trade would constitute USD 200, while average loss-making one — USD 420. So, after a series of 100 trades, with the R:R ratio less than 1, our imaginary trader will make the profit: (70 х USD 200) — (30 х USD 420) = USD 14,000 — USD 12,600 = USD 1,400.

It doesn’t mean that John would definitely make these USD 1,400. He EXPECTS to receive this profit. It’s a clear thing that real results of John could be a bit better or a bit worse, but they would PROBABLY be very close to USD 1,400. And do not forget that we deal with probabilities.

CONCLUSIONS

Traders who place hopes in a high win rate often forget about the size of the average loss, which may result in sad consequences. This is the problem, which scalpers often face. The majority of them will simply lose money without a high win rate. A scalper, by default, tries to make a ‘fast’ profit at rather ‘wide’ stops and they badly need a good win rate. Such an approach may result in big losses if the percentage of profitable trades starts to fall. Some scalpers manage to avoid this problem. They leave certain positions open for working out more long-term goals (of course, if there is a basis for it). This allows them to significantly increase the average profitable trade and, doing so, increase stability of the obtained results.

Traders who are obsessed with a high average size of the reward, could also find themselves in the wrong boat if their win rate goes down below the acceptable value. Do not become ‘slaves’ of a high R:R ratio. Common sense should be present in everything. Take profits should be reasonable and they should be placed at those price levels, which the market, most probably, would reach. Identify your goals only after a thorough market analysis and identification of a sufficient ‘cruising range’.

There are a lot of indicators of the trading system profitability and the R:R ratio is only ONE OF them and in no way the major one. That is why if you have an efficient, from your point of view, trading system in sight, conduct its analysis on a virtual account and calculate expectancy. You can find out that a trading system with a low R:R may bring a good and stable profit.

Dear friends, share your thoughts in the comments. Your opinions are of high value for us!

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