Statistical significance check

The idea is to add some kind of "statistical significance" check.

The "statistical significance" (the higher the better) is proportional with the number of trades (the higher the better) divided by the number of optimized parameters (the lower the better). There should be some validation parameter which takes into account the number of optimized parameters in a given strategy and the number of resulting trades in IS/OOS period. This check could prevent from curve fitting / over optimization of the resulting strategies which are based on too many input parameters (= too many degrees-of-freedom). So taking into account the number of degrees-of-freedom used for the strategy generation, this mechanism could give users a warning that the number of trades is probably too low to be considered statistically significant.


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  • Votes +8
  • Project StrategyQuant X
  • Type Feature
  • Status Archived
  • Priority Normal
  • Assignee None
  • Milestone Archived (To be done later)

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Kc
#1

coensio

28.01.2019 13:55

Task created

N
#2

nathan

28.01.2019 14:04
Voted for this task.
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#3

tnickel

28.01.2019 23:48
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IH
#4

clonex / Ivan Hudec

29.01.2019 12:54
Voted for this task.
IH
#5

clonex / Ivan Hudec

29.01.2019 12:55

Information Criterion

Information criterion are a rigorous statistical way to test if the amount of complexity in your model is worth the extra predictive power. The test favors simpler models and will tell you if you are introducing a large amount of complexity without much return. One of the most common methods isĀ Akaike Information Criterion.

Rr
#6

Partizanas

29.01.2019 17:02
Voted for this task.
m
#7

mabi

30.01.2019 08:58
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#8

ludvick

09.10.2019 10:58
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MF
#9

Mark Fric

16.02.2020 13:52

Status changed from New to Archived

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#10

bentra

08.05.2020 19:31
Voted for this task.

Votes: +8

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