Statistical significance of a new rule
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- Roundtable Knight
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Statistical significance of a new rule
Say I add a new rule to a system that seems to improve results. How many instances should said rule come in to effect for it to be statistically significant? Obviously more is better, but is there any sort of rough guide?
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- Roundtable Knight
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"... that seems to improve results"
Depends how you quantify this. I'd look at how the trade frequency changes when you apply the new rule, and also the average size of winners to losers. Also, I'd be suspicious if a new rule happened to significantly improve the win% since this may be eliminating losing trades by pure coincidence/curve fitting/date anomaly.
It also make a difference whether it's an entry rule, position sizing rule, or exit rule - they each should affect different aspects of your trading program in different ways (see attached model).
Hope this helps
Depends how you quantify this. I'd look at how the trade frequency changes when you apply the new rule, and also the average size of winners to losers. Also, I'd be suspicious if a new rule happened to significantly improve the win% since this may be eliminating losing trades by pure coincidence/curve fitting/date anomaly.
It also make a difference whether it's an entry rule, position sizing rule, or exit rule - they each should affect different aspects of your trading program in different ways (see attached model).
Hope this helps
- Attachments
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- TradingSystemComponentModel.pdf
- Objectives, traits, and components of a trading program
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- Roundtable Knight
- Posts: 207
- Joined: Mon Feb 23, 2004 9:13 am
- Location: Vermont, USA
- Contact:
How many trades are there when this rule is not implemented at all?
Just looking at the chart it appears to be a "robust" parameter with respect to R3 since it has a nice "bell curve" shape with the "sweet spot" lookback around 9 days, but only filtering out 100 trades.
If I was analyzing this I'd calculate System Value for each instance and see which one is the highest.
System Value = (Average R/STDEV(losing R) ) * number of trades per year (or day, week, month, depending on average trade duration).
Assuming you're still left with at least 100 trades in your sample after filtering i'd say the results were statistically significant, but it would be better to see a complete TBB report with the lookback stepped from 1 to 17.
Just looking at the chart it appears to be a "robust" parameter with respect to R3 since it has a nice "bell curve" shape with the "sweet spot" lookback around 9 days, but only filtering out 100 trades.
If I was analyzing this I'd calculate System Value for each instance and see which one is the highest.
System Value = (Average R/STDEV(losing R) ) * number of trades per year (or day, week, month, depending on average trade duration).
Assuming you're still left with at least 100 trades in your sample after filtering i'd say the results were statistically significant, but it would be better to see a complete TBB report with the lookback stepped from 1 to 17.