Two months back, I paired up with my friend, an advanced coder and doesn't know a lot about forex strategies; together with my scalping strategy and coding skills, we programmed an EA. Over the course, we kept optimizing it to the tiniest details and tried our best to replicate my trading strategies Yesterday he claimed that we had reached the final build and couldn't optimize it anymore for now. I went through the code one last time, and it kinda made sense to me since I could figure out 'some' stuff out of the code.
Now when I backtested it, I had very mixed feelings. It performed very well. Too well. I was equally stunned and expected something that after the efforts we both had put into it. I don't know a lot about EAs or coding, but I know that the stock MT4 backtests are often not reliable and are misleading, so I went ahead and bought a set of tick data from a paid service- Tick Data Suite 2.
Broker MetaTrader Terminal There are notable differences between the MetaTrader terminal provided by MetaQuotes from their website, and the counterpart delivered by your specific broker. For example, the symbol properties, i. These predefinitions are likely to be different from that which is directly relevant to your broker. It is possible to match the properties manually, such that the environment downloaded from MetaQuotes matches your individual broker, but the easiest and most reliable methodology would follow from a direct download from your broker.
Testing on Demo Accounts It is common practice to test a strategy on a demo account prior to release on a real account. Whilst this is a respectable precaution, there should be an additional testing phase on the real trading account. This is primarily due to the different order book structure LOB of the real and demo environments.
There will be slight variations in price and volume, which may alter the outcome of your strategy. For this reason, it is recommended to trial a strategy on a real account before increasing the capital. This is especially relevant within EAs utilising deep neural nets, for which the training set can provide an unrealistic view of projected performance.
One way of reducing the risk of overfitting is to split to testing period into a back-testing period and a forward-testing period walk forward test. This will allow for a strategy to optimise itself over the given back-testing period, and treat the walk forward test as new information. Following the back-test and walk-forward, it would be good practice to favour results with consistency as opposed to excessive returns in either period. Similarly, the maximum drawdown should be consistent between both results.
Sample size For any given test, it is crucial to apply a weight to the number of trades within the test. For example, for any two results, with different number of trades, but all other conditions remain constant, it would be sensible to favour the result with a greater number of trades.
Calmar Ratio There are a variety of useful statistical measures for portfolio analysis. Beyond the return and drawdown, it is sensible to consider the alpha, beta, Sharpe ratio and various other metrics. A measure we like to assess is the Calmar ratio, calculated as below.
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