How to find good value when using WF optimization?

• 04/12/2020 at 9:29 AM #125757
  Moda

  @nonetheless

  Thanks you for your work. I have a beginner question, i’m trying to figure out what is the good way for optimization with WF.

  My question is can i ask you what is your workflow in order to find good value when using WF optimization?

  Example are you putting let’s say for a variable, a range of value and optimize it (WF) with single iteration or 7 iteration and jump to second variable….

  or working by block of variables optimization…are you using only WF optimization or old optimization too?

  Sorry for the noise and out of topic question but i really would like to find out the good way to do it, for now i’m struggling finding decent variable value after optimizing (WFE %>50).

  I searched on the forum but didn’t find a precise answer…

  

  Moda

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  04/12/2020 at 2:55 PM #125801
  GraHal

  @Moda  it would be good to have a new Topic on WF as we haven’t had a discussion on it for a while?

  Also a new Topic means that more folk would probably contribute, also more folk would benefit by being able to find the Topic on WF in the future.

  Moda … if you agree to below then a Moderator would raise a new Topic for you.

  Mods

  Please place the above question on WF in a new Topic

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  nonetheless, Moda

  

  GraHal

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  04/12/2020 at 3:37 PM #125808
  Moda

  @GraHal sure sounds great … not the place here

  Thanks

  

  Moda

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  04/12/2020 at 6:12 PM #125819
  Vonasi

  Topic split from ‘Mother of Dragons’ topic as requested.

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  Moda, GraHal

  

  Vonasi

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  04/12/2020 at 7:23 PM #125824
  Moda

  Thanks @Vonasi

  

  Moda

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  04/12/2020 at 10:34 PM #125849
  nonetheless

  Hi Moda, this is how I do optimizations:

  First I optimize over the maximum data, ie the full 200k to get a picture of how viable an idea is. If the number of variables is low, then i’ll run a 7x WF with max variance. If the result is good then I’ll look at the values for the most recent 1 or 2 sectors and use those in another back test over the full 200k. This gives OOS performance for the recent months, plus the data from before the IS period.

  If the algo has a lot of variables then I skip the 7x WF and just do one 70-30 WF over 25% of the data (50k), then back test @200k. If it still looks good, I run it through the Robustness Tester which you can read about here:

  https://www.prorealcode.com/topic/day-month-year-strategy-robustness-tester/

  If there are various sets of values that do well OOS then I pick the one that does best in the Robustness tester.

  I would be v curious to know what method other people use to arrive at a final set of values.

   

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  Moda

  

  nonetheless

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  04/12/2020 at 10:45 PM #125850
  Vonasi

  nonetheless wrote:

  If there are various sets of values that do well OOS then I pick the one that does best in the Robustness tester.

  So you run the robustness tester several times with various fixed variable settings and then go with the most robust? If my understanding of what you wrote is correct then that is a very solid way of comparing different sets of values. It gives you a fighting chance that you have the most robust even if they are not the most profitable.

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  nonetheless

  

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  04/12/2020 at 10:47 PM #125851
  Moda

  @nonetheless many thanks this is much more clear to me now

  

  Moda

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  04/12/2020 at 11:09 PM #125853
  nonetheless

  Vonasi wrote:

  So you run the robustness tester several times with various fixed variable settings and then go with the most robust?

  Yes, correct. Bloody time-consuming but seems to get results.

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  GraHal

  

  nonetheless

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  04/13/2020 at 12:45 PM #125919
  Moda

  Thanks for pointing me the direction again…here some work

  Need to work this a bit more!!

  

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  04/25/2020 at 5:44 PM #128045
  Moda

  i’m curious how robust this will be…

  

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  04/25/2020 at 8:18 PM #128070
  nonetheless

  There’s no fixed way to interpret these scores but to me that looks reasonably good. It’s always harder to get a good score for the average gain – rarely above 50 in my experience – and you’ve got a good number for the %win, so I’d say that’s a decent result.

  

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  04/25/2020 at 8:21 PM #128071
  Francesco

  Moda wrote:

  i’m curious how robust this will be…

  You should better check the robustness test that you did… usually this is not an usual distribution of values

  

  Francesco

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  04/25/2020 at 9:27 PM #128086
  nonetheless

  Francesco wrote:

  not an usual distribution of values

  if it’s 43.8 for average gain, 91.5 for %win and 67.6 average of the two? that looks quite normal to me.

  

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  04/25/2020 at 9:34 PM #128089
  nonetheless

  which part do you find unusual?

  

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