AmiBroker Adaptive Trading Strategies Course

Adaptive Trading Strategies are systems with rules that change depending on the market regime. This course will focus on developing adaptive trading strategies using AmiBroker, leveraging the Custom Backtest (CBT) interface introduced in the CBT Intensive Course. At the completion of this course, you can:

• ​Define your own Market Regimes
• Consider how trade setup, entry, and exit are assigned to a regime
• Summarize metrics by regime
• Select the best parameters for each regime
• Modify your AFL to use adaptive (regime-specific) parameters
• Compare the adaptive strategy performance to a baselin

Included in The Course 

• ​4 hours of downloadable pre-recorded video classes 
• AmiBroker files from classes 
• Code templates that allow you to get coding quickly 
• One hour of one-on-one access (over email or Skype) to Matt to ask any questions you may have 

I took Matt’s beginning and advanced Amibroker (AB) courses a few years ago. After that, I was able to code three swing-trading strategies. I also took Matt’s CBT and Adaptive Trading Course in AB in 2018. I then worked with Matt to significantly upgrade one of my 3 strategies and started trading it in Jan. 2019. Not only have my trading results more than paid for the course fees, but they have paid for several family vacations! I highly recommend Matt’s courses if you want to create trading strategies you can have confidence in.

Kirk D

Prerequisites 

• ​AmiBroker version 6.0 or later installed. Version 6.2 or later is preferred.
• A data source configured to work with AmiBroker
• Basic familiarity with AFL, including the ability to create and execute back tests and optimizations with AmiBroker’s standard back test engine
• Working knowledge of the CBT, AmiBroker object model, custom metrics
  

Summary of course 

Video 1 

Our end goal is to create an adaptive strategy which performs optimally under different market regimes. The first step toward that goal is to summarize salient metrics by regime, which will then allow us to evaluate which strategy parameter values perform best in each regime. The first session will focus on providing those regime-specific metrics.

Video 2 

With our favorite metrics summarized by regime for each variation of an optimization, we can now identify the “best” variation for each market regime during our in-sample test period. This is an exercise best accomplished with some help from Excel. We’ll then plug the adaptive parameters into our AFL without breaking the static (non-adaptive) functionality.

Video 3 

In our final session, we’ll see whether our adaptive strategy outperformed the static version. The most apples-to-apples comparison would be between the Adaptive OOS test and a Static OOS test using the best parameters from the IS optimization. Of course, we’ll also want to see how our Adaptive version measured up against the full range of possible Static OOS outcomes, i.e. the optimization report.

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If you have questions about the course that you want to ask, ​Contact Me.