Different Optimisation Profile Results in Crosschecks vs WF Matrix for the same strategy

This is probably a question rather than a bug, but I am not sure.



What is the difference between the Optimisation Profile Results in the Cross Check and the WF Matrix?


I am not talking about the WF Results Profile, which I get but the Optimisation profile tab in the WF Matrix results.


In the example attached both were run at 20,000 optimizations.


I get the feeling I am missing something obvious?

Attachments
Opt Profile WF Matrix.jpg
(180.47 KiB)
Opt Profile Cross Check.jpg
(197.38 KiB)
  • Votes 0
  • Project StrategyQuant X
  • Type Bug
  • Status Refused
  • Priority Normal

History

N
#1

nathan

22.03.2019 14:05

Task created

MF
#2

Mark Fric

25.03.2019 13:48

Status changed from New to Waiting for information

Optimization profile is the same, but from the look of both results it seems there is much smaller variety of parameters usd in WF Matrix optimization.


I tried it myself, but I'm getting very similar results in both cases. Could you attach both these results for investigation.

N
#3

nathan

25.03.2019 19:48

Attachment Strategy 41331.sqx added

Attachment WF Matrix - Strategy 41331.sqx added

No problem, attached below
MF
#4

Mark Fric

26.03.2019 10:39

Status changed from Waiting for information to Refused

Attachment wf_param_settings.jpg added

ok, the difference is visible, I didn't notice it before.


Optimization profile in WF result was created from 2304 optimizations, in simple result from 13000 optimizations. 

So there was much bigger variety of parameters in simple result.


I don't know what exactly were your settings for WF Matrix, but I assume the parameters settings was such that number of possible combinations was smaller.


Check your Parameters settings.

When running optimization in cross checks, the settings are Up and Down is 30%, and Max steps = 10, this is not configurable in Cross checks.


If you run WF Matrix in Optimizer, you probably used the default values like in screenshot. They result in 2304 combinations.

So you can improve the number of steps and range % to get more optimizations.


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