In particular I would like to make the system a lot faster, since it will allow parameter searches to be carried out in a reasonable time. While Python is a great tool, it's one drawback is that it is relatively slow when compared to C/C++. Hence I will be carrying out a lot of profiling to try and improve the execution speed of both the backtest and the performance calculations.
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To date, we've been experimenting with the OANDA Rest API in order to see how it compared to the API provided by Interactive Brokers. We've also seen how to add in a basic portfolio replication element as the first step towards a proper event-driven backtesting system. I've also had some helpful comments on both previous articles (#1 and #2), which suggests that many of you are keen on changing and extending the code yourselves.
Trading on margin is extremely popular among retail Forex traders. It allows you to open a much larger position than your initial trading account would otherwise allow, by allocating only a small portion of your trading account as the margin, or collateral for the trade. Trading on margin also carries certain risks, as both your profits and losses are magnified.
Slippage Handling - The system is currently generating a lot of slippage due to the high-frequency nature of the tick data provided from OANDA. This means that the portfolio balance calculated locally is not reflecting the balance calculated by OANDA. Until correct event-handling and slippage adjustment is carried out, this will mean that a backtest will not correctly reflect reality.
Local Portfolio Handling - In my opinion carrying out a backtest that inflates strategy performance due to unrealistic assumptions is annoying at best and extremely unprofitable at worst! Introducing a local portfolio object that replicates the OANDA calculations means that we can check our internal calculations while carrying out practice trading, which gives us greater confidence when we later use this same portfolio object for backtesting on historical data.
Trading on margin refers to trading on money borrowed from your broker in order to substantially increase your market exposure. When opening a margin trade, your broker lends you a certain sum of money depending on the leverage ratio used, and allocates a small portion of your trading account as the collateral, or margin for that trade. The remaining funds in your trading account will act as your free margin, which can be used to withstand negative price fluctuations from your existing leveraged positions, or to open new leveraged trades. The relation between your free margin and other important elements of your trading account, such as your balance and equity, will be explained later. For now, it’s important to understand the meaning of margin in Forex.