2) In the table, you will see the indicators of all trading advisors who have worked for several months or years. This will help you to understand which of the robots is the safest or which program you need to connect for aggressive trading and getting quick results. For the convenience of search, you can use a filter that will sort the algorithms according to the following criteria: drawdown, initial deposit, number of days worked and total profit. The better the ratio of these indicators, the greater the assessment assigned to the robot in the overall rating. For clarity, you will see a graph giving a visual assessment of the performance of each robot.
If traders are positive on the prospects for the Yen, they would expect the number on the right to go down – i.e. the Yen would be getting stronger against the Dollar. Traders would be buying less Yen with a Dollar as the Yen got stronger. Similarly, if the Yen was expected to weaken, forex traders would expect the Yen number to go up, reflecting the fact that the dollar could buy more yen.
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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.