Money management focuses on the potential effects on the trading account from the execution of every single trade. In the optimistic scenario, each position will be profitable. But in the realistic one, stops will be hit, thereby realizing losses.

Losing positions are an inevitable part of foreign exchange trading. The real goal for traders is to keep the number of losing positions and the amount of the corresponding losses within the limits of what is permissible for their strategy. For this purpose, money management applies a set of rules and limits.  

Let’s consider an example: the trader John opens a total of 100 positions. John places a take-profit (TP) order of 100 pips and a stop-loss (SL) order of 100 pips for each. Thus, the potential profit and loss are identical for all positions (we ignore trading costs). If in half the cases the stop is hit and in the other half the price target is reached, the final result will be zero (50 gains of 100 pips and 50 losses of 100 pips). However, if John can maintain this efficiency of 50% winning and 50% losing positions, but increase the price target to 200 pips, for example, the profit realized will be significant (50 gains x 200 pips and 50 losses of 100 pips).

Reward to Risk Ratio

One of the most popular rules in forex trading – the reward to risk ratio (RRR) – is based on this elementary arithmetic. Let’s look at several scenarios in the table below, each of which will result in zero profit (breakeven). The total number of trades remains 100.

RR Ratio. Chart:

Table 1: Reward to Risk Ratio. Source:

We have already seen that 50 gains of 100 pips offset 50 losses of 100 pips. In the second scenario with an RRR of 2:1, it would take 33.33 winning positions of 200 pips to offset 66.67 losses of 100 pips. Thus, one out of three winning positions will offset the losses. With an RRR of 3:1, one out of four positions will be enough to preserve the balance in the account. In this scenario, however, the profits should carry 300 pips. In the latter, even more extreme case, 10 winning positions of 900 pips each would be needed to offset losses on the remaining 90 positions of 100 pips each.

It is obvious that the more we increase the RRR, the fewer positions will need to reach their price target to achieve a zero result. In itself, such a rule does not mean much. Because it is simple arithmetic in which we pick the numbers. If we make 300 pips with one successful trade, and then lose four times 100 pips, we will gradually lose everything.

However, RRR demonstrates a very important idea – you do not have to be consistently successful to achieve positive results. RRR builds the discipline to make risk-adjusted trading decisions. Position management criteria are clearly defined, resulting in consistent trading strategy execution.

Each trader will attempt to apply the RRR framework to his or her market approach. Let’s consider an RRR of 3:1 in the context of a buy trading strategy in an ascending price channel. A long position is opened when the support line is reached, and profit is taken when the resistance line is reached. The chart illustrates the idea.

Chart 1: Risk-Adjusted Trend Strategy. Chart: MetaTrader4

Chart 1: Price Channel Strategy, Reward to Ris Ratio 3:1. Chart: MetaTrader4

Once the price channel has been formed and confirmed by a series of lows and highs, a buying opportunity can be discovered. Such an opportunity appears at price of 1.3635 when the support line is reached again. It makes sense to place the stop order at 1.3550 – below the previous low and below the trend line. These are key supports. Their possible break would compromise the upward trend. The potential loss is equal to 85 pips (1.3635-1.3550). At RRR 3:1, the price target should be located at 1.3890. It is important that the target is realistic from a technical point of view and not simply defined as the stop-loss distance multiplied by three. In this case, it is located on the upper trend line of the corridor, making it just that.

In this particular example, the price target has been reached. Of course, even in this fairly clear concept there are subjective factors such as the construction of the price channel, the right price to open a position, etc. In this case, the trading plan is based on very basic technical analysis – price channel supports and resistances. Each trader builds their own unique approach to the market and tests their strategy in a demo environment. When they find the right RRR settings for their strategy, they can move to real account testing.

Position Size

Another important aspect of successful money management has to do with the size of open positions. In the forex space, the opinion that the risk on a given position should not exceed 2% of the balance is quite popular. Thus, even 5 or 10 consecutive losing positions will not be fatal. In fact, this 2% poses a huge risk, especially for novice traders. It is much more reasonable to keep potential losses below 1%.

Let’s consider two scenarios – a series of 10 consecutive losses, each of which amounts to either 5% or 1% of the original balance. In the first case, the result is a loss of 50% (10 losing trades of 5% each). If the original account balance was USD 10,000, its final value would be USD 5,000.

The worst thing is not that this is a huge loss in absolute value. The problem is that its recovery is becoming an almost impossible challenge. Getting back to the starting position means a 100% increase in the current value of the account (a USD 5,000 profit). That is, a 50% loss must be offset by a 100% profit.

But in real trading, the new situation should also be reflected in traded volumes. If 5% of 10,000 was equal to USD 500 in the beginning, then this USD 500 is now equal to 10% of the current balance. The size of the new positions should therefore fall by half. Potential profits would also fall by half. This makes reaching the initial account value of USD 10,000 quite a challenging task.

In the second scenario, the total loss would be 10% of the original capital – 10 losing positions of 1% each. Obviously, the damage suffered will be significantly smaller and their recovery more likely. A more conservative approach would reduce the risk of excessive losses.

This example is just a visual illustration of the enormous damage that overly aggressive strategies can lead to. Effective money management protects the trading account during negative periods in order to preserve the capital when positive periods occur. Various limits are used for this purpose in practice.

Trading Limits

Such is the example already mentioned with a maximum allowable loss on each trade of 1%. If this rule is combined with another one – that the maximum number of losing trades per day should not exceed two, then these two limits in aggregate ensure that the daily loss will not be more than 2%.

At a 3% weekly loss, trading can be suspended. At a 5% monthly loss, trading can be suspended until the new month starts.

These limits may seem a bit superficial. Lack of trading also means missed opportunities. But setting limits is one of the most effective methods of controlling losses. Similar logic, albeit a bit more complicated, is used by asset management companies, banks, etc. They automatically take certain actions when a limit is reached.

But let us go back to our example. Even with the worst-case scenario (but with limits in place) and monthly losses of 5% of the opening balance, the annual decline would be 60% (12 months at 5%). While this is a huge loss, there will still be some cash in the account at the end of the year. The need for a comprehensive reassessment of the trading strategy will be evident but losses will still be limited. At the same time, many other traders who uncontrollably open new positions will have lost everything without even giving themselves a chance to analyze the reasons for their failures.

In conclusion: money management assesses the potential effects of individual trades on the trading account and controls the maximum allowable losses through a series of rules and limits. This approach to risk management is fundamental for forex markets. It controls the exposure to market risk, filters trades by “reward to risk ratio” and helps to achieve trading consistency.

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