An important feature of the trading algorithm Sakura EA is its informativeness and focus on traders of any level of skill and experience. Expert Advisor actively addresses the trader by means of information messages in the experts tab of MT4 terminal. And also, messages on the price chart at the moment of its work.
An equally important component of the trading advisor interface is Sakura EA is an information panel, which, as on the dashboard of the aircraft, displays all relevant information about the trading algorithm at a given time.
When choosing a broker, we recommend to use only those types of accounts, where the ECN system is used, as only on such accounts liquidity providers provide minimum spreads and the most favorable conditions for trading intraday systems with small trading purposes. It is also worth checking that the broker’s commission is adequate. Spread, commission and slippage are the most important for this trading advisor, which can directly affect its profitability. You can find the list of our recommended brokers at the end of the page.
Analysis of backtesting results
ТNow let’s move on to the analysis of the testing results of this trading algorithm. We would like to remind you that all our developments pass a full cycle of optimization and testing in conditions as close as possible to the real market. For this purpose, we use all the functionality of Tick Data Suite software packages for modeling trades at high quality quotes with the possibility of simulating slippage, as well as Quant Analyzer for detailed evaluation of large arrays of statistical data obtained as a result of the trading robot optimization stage.
Initially, let’s deal with the matrix of the forthcoming statistical analysis of the testing results of this trading system. We will evaluate the results of test runs in Tick Data Suite on real Dukascopy quotes, where the real dynamic spread is already integrated.
Let’s set the spread multiplier to 1.10 and set the minimum spread at 10 points, thus maximally tightening the conditions of the test modeling of trades and as a result bring them closer to the conditions of real trading.
As mentioned earlier, trading takes place during the night hours, just in the median time between active trading sessions, passing through rollover. As you know, at this time, liquidity in the market drops strongly and spread increases many times. And as a consequence of all the above, the execution of orders is worsening. For maximum approximation in the TDS settings, we will set the delay in order execution, slightly higher than it happens in practice, based on experience.
Everything, conditions for crash-test of our algorithm are created, we launch the model into the bouncer and check how the preventive systems of trading security developed by us will work.
Testing will be carried out with a fixed lot, only in this way without the activated money management function it is possible to adequately evaluate the results of test runs.
As can be seen from the results of the test run on the example of EURAUD pair, the trading algorithm allows you to generate profits with a high profit factor of 2.33. In this case, the recaverie factor, the most significant indicator of evaluation of the test results is 24, which shows how much profit exceeds the maximum drawdown, thus showing the potential of the system to recover.
Based on the results of the obtained chart of equity changes, let’s draw a trend line, as can be seen, the line of deposit changes exactly rounds the trend line, while over the last years there have been practically no periods of stagnation in the trading model work, which is embedded in the algorithm. This suggests, first of all, high predictive properties of this advisor.
Let’s run our mandatory method of checking the ready results of the trading algorithm settings, the Monte Carlo method, simulating many trading conditions, thus allowing to exclude the so-called fit for a particular market. As you know, the accuracy of this mathematical method is directly proportional to the number of iterations of calculations under changing conditions. For this purpose, let us set the number of simulations in Quant Analyzer to 400.
The received result, first of all, speaks about high stability of the received settings of trading algorithm and allows to expect profitable trading on real trading accounts with high probability.
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