AmiBroker testing and Excel

Many system testers focus on optimising variables like moving averages. But it is also possible to get a better understanding of position size, risk and other trade parameters.

The following charts were generated from Amibroker optimise runs. I optimised a number of criteria, %Risk, minimum position size $, capital and maximum number of trades held - all at the same time. What results is a lot of data that I then transfered to Excel. Using Autofilters and pivot tables in Excel I can fix some parameters, as well as exclude others, and create 3D charts as shown below.


I had some fun with colours - the default ones set on my version of Excel didn't really work for me.


So in the one spreadsheet I have, amongst other things, a large number of 3D combinations to consider. I lose the ability to rotate the charts but I did customise the colours to my liking. It's a little time consuming generating pivot tables and determining what values to include / exclude, what parameters to fix and what value to fix them at but I feel I am only scratching the surface with Excel.

regards
stevo

3D rotating charts video

Rotating the charts in Amibroker makes it a lot easier to work out what is going on.
stevo - unfortunately the video didn't post.

Optimising & % trades not taken

I did an 2 parameter optimise on a weekly system I am working on. The axis marked "Monte Carlo" is a dummy variable - the variable is not used anywhere in the system. The axis marked "trades not taken %" is where a % of buy signals were ignored at random.



With this long term weekly system the more buy signals ignored the lower the CAR (Compound annual return %). I could ignore 10% to 30% of the trades without a huge dropoff in performance.

The "Monte Carlo" axis shows the variation of CAR at different levels of trades not taken. If a big trade is always taken because no trades are ignored then this one trade could give a false impression of the system. By testing with a random buy variable it is possible to approach Monte Carlo simulations using a different randomising approach.

Also I randomised the buy and sell price over the week the signal was given (it's a weekly system) so, even at 100% of signals not ignored there was slight variation in the results.

Hope that all makes sense!

stevo