The key figures of a successful CFD Trading Strategy

On social trading portals hundreds of different trading strategies compete for followers. The number of circulating scripts for large trading platforms like MetaTrader4 is even greater. But how can a promising strategy be recognized? Objective performance indicators must be decisive.

There is little point in evaluating trading strategies solely on the basis of the performance achieved so far. Firstly, this does not say anything about the period of time the strategy has been used and under which market conditions the rules and regulations have proven themselves. Secondly, the performance does not say anything about the risk assumed.

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1. Risk-adjusted performance

The evaluation of trading strategies therefore focuses on risk-adjusted performance indicators. These figures adjust the return achieved for the risk assumed. Finally, the law of market efficiency must also apply to trading strategies: Investing in one strategy may not make sense if there is a second strategy that could achieve a higher return with the same risk or a lower risk with the same return.

2. Sharpe ratio

One of the most important risk-adjusted performance indicators is the Sharpe Ratio (SR), named after its developer William Sharpe. SR is calculated by subtracting the volatility observed over the same period from the return achieved by a strategy. The difference is put in relation to the so-called risk-free interest rate. This is generally understood to be the interest rate on very safe government bonds such as those of the Federal Republic of Germany.

A case study: An investment strategy has achieved a return of 8% in the period under review (one year). The volatility was 4 % and the risk-free interest rate was 2 %. To calculate the SR, the return of 8% is reduced by the volatility, resulting in a value of four. This is divided by the risk-free interest rate. The SR thus assumes a value of 2. The higher the value of the SR, the better the risk assumed was remunerated during the period under review.

3. Sortino ratio

The Sortino Ratio is a modified variation of the Sharpe Ratio. This ratio also focuses on the excess return achieved by a strategy compared to the risk-free interest rate. The difference lies in the calculation of the volatility taken into account. Only downward fluctuations are taken into account.

4. MAR

To determine the MAR ratio, the annual return is divided by the highest loss suffered by a strategy during the period under review. For example: The annual return is 10%, the highest loss suffered so far is 20%. The MAR ratio then assumes a value of 0.5. This would be an insufficient value. Only from a value of 1.0 does the ratio signal that the risk assumed has been adequately remunerated by a correspondingly high return.

5. Payoff ratio

The payoff ratio is determined by comparing the profits made during the period under consideration with the losses incurred. If the payoff ratio is above 1.0, the average profit was higher than the average loss. The average loss is the only feature of a trading strategy that can be determined almost exactly by taking appropriate measures to limit losses.

6. trade ratio

The trade ratio indicates the ratio of profitable to loss-making positions during the period under consideration. A value above 1 indicates that the majority of trades were concluded with a profit. This is by no means a necessary condition for a successful trading system. Some strategies usually go through long series of losses and then overcompensate these with a few but very large profits. Such strategies are only suitable for beginners to a very limited extent. For the beginning, strategies with a high hit rate are better.

7. Max. Drawdown

The max. drawdown indicates the largest loss suffered during the period under consideration in relation to the entire trading account (!). The lower this value, the better the strategy is in principle. Especially in combination with attractive returns, a manageable maximum drawdown is a very important quality criterion for strategies.

8. Volatility

Just as historical volatility can be measured for general market development as a measure of the intensity of fluctuation, the same is possible for the capital curve of a trading account. Since volatility is a measure of the risk assumed, low volatility is generally preferable to high volatility. However, most trading approaches with high returns also require the acceptance of higher volatility.

9. Further characteristics for validity

Key figures are not an end in themselves, but the result of a statistical evaluation of the results of a trading strategy for a defined period under consideration. A fundamentally sound data basis is a necessary condition for performance figures to be sufficiently meaningful.

One way of checking validity is to eliminate the two most successful transactions of the observation period from the statistics and then to look at the key figures again. If there are conspicuously large differences compared to the previous period, it cannot be ruled out that the original key figures were largely based on random events.

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