This is the second part of the automated trading course, which will deal with how to develop a profitable strategy. No further programming knowledge is required when you did the first part of this course. It's here: http://www.forexfactory.com/showthread.php?t=388887
This second part will cover writing basic trading strategies, optimizing, walk forward analysis, portfolio strategies, and money management. It uses some new trading algorithms such as frequency filters. To avoid misunderstandings: It's not a course about technical analysis. I won't explain here moving averages or the like. It's just about how to develop and backtest a strategy based on a trading idea that you already have.
The goal is developing a robust portfolio strategy with a stable return. You can see the out-of-sample equity curve of such a portfolio system here, although it is not the same strategy as developed in the course:
http://zorro-trader.com/manual/images/z2perf2.png
For the course you'll need a free program for running the script examples and testing the strategies. It's called "Zorro" and you can download it from zorro-trader.com. Please also keep two things in mind:
► All strategies presented in this thread are meant for educational purposes. They are all profitable, but designed for simplicity, not for maximum profit or robustness. For really trading such a strategy, you would normally add entry filter rules for filtering out unprofitable trades. How to find and generate such rules with machine learning algorithms, such as Zorro's perceptron or decision tree, might be covered in a future third part of the course. For really trading a strategy you normally also use a more sophisticated exit algorithm, realized with a trade management function. But that's also stuff for a future part and we'll keep it simple in this part of the course.
► I will post some backtest results here, but they can be slightly different to the results you'll get when testing the scripts yourself. That's because the simulated spread, commission, and rollover parameters can be different and the backtest periods are also different. You could prevent this by setting Spread and other broker dependent parameters to a fixed value in the script, and use fixed periods for simulation and test, but keeping them up to date with the market gives a more realistic result.
This second part will cover writing basic trading strategies, optimizing, walk forward analysis, portfolio strategies, and money management. It uses some new trading algorithms such as frequency filters. To avoid misunderstandings: It's not a course about technical analysis. I won't explain here moving averages or the like. It's just about how to develop and backtest a strategy based on a trading idea that you already have.
The goal is developing a robust portfolio strategy with a stable return. You can see the out-of-sample equity curve of such a portfolio system here, although it is not the same strategy as developed in the course:
http://zorro-trader.com/manual/images/z2perf2.png
For the course you'll need a free program for running the script examples and testing the strategies. It's called "Zorro" and you can download it from zorro-trader.com. Please also keep two things in mind:
► All strategies presented in this thread are meant for educational purposes. They are all profitable, but designed for simplicity, not for maximum profit or robustness. For really trading such a strategy, you would normally add entry filter rules for filtering out unprofitable trades. How to find and generate such rules with machine learning algorithms, such as Zorro's perceptron or decision tree, might be covered in a future third part of the course. For really trading a strategy you normally also use a more sophisticated exit algorithm, realized with a trade management function. But that's also stuff for a future part and we'll keep it simple in this part of the course.
► I will post some backtest results here, but they can be slightly different to the results you'll get when testing the scripts yourself. That's because the simulated spread, commission, and rollover parameters can be different and the backtest periods are also different. You could prevent this by setting Spread and other broker dependent parameters to a fixed value in the script, and use fixed periods for simulation and test, but keeping them up to date with the market gives a more realistic result.