Hello.
One of my strategies has an APR > 30% by disabled NSF-Positions. In case of enabled NSF-Positions there is just 15% APR (Nasdaq 100). What does it mean and what consequences does that mean (in general an for live trading)?
Thanks a lot.
Marko
One of my strategies has an APR > 30% by disabled NSF-Positions. In case of enabled NSF-Positions there is just 15% APR (Nasdaq 100). What does it mean and what consequences does that mean (in general an for live trading)?
Thanks a lot.
Marko
Rename
NSF positions is a situation when your backtest generates more candidates than available equity. Unless you specify a Transaction.Weight, WL7 makes a random choice of hich position to trade. As said in the FAQ you can get rid of NSFs by reducing your position size and/or increasing margin factor.
Check out this video -- "What are NSF Positions?"
https://www.youtube.com/watch?v=HXA-AetQ3Jk
Check out this video -- "What are NSF Positions?"
https://www.youtube.com/watch?v=HXA-AetQ3Jk
I run into issues with NSF too. You really want to keep your NSF positions to a minimum to get consistent results in your back testing. In Build 44 they added NSF metrics to the Metrics Report. This video by Glitch may help: https://www.youtube.com/watch?v=vaH6XBwo1gQ&t=51s
Another trading angle is to weight the PlaceTrade Buy transaction by a "DataSet" merit metric. Any DataSet merit metric must to computed in PreExecute{} because this requires comparing all metrics for all stocks in the DataSet together against a composite merit metric (and possibility sorting against that composite metric). I would check some examples of using PreExecute{} for doing this if you're interested.
You should appreciate the original intent of the transaction weight was to simulate the worst case scenario--not the best case scenario. So you need to tread cautiously (and conservatively) when computing the composite DataSet merit metric that contrasts all stocks in the DataSet. But this can be done *if* you know the salient metrics to build that composite in PreExecute. This is definitely very advanced design, and it can be dangerous if your composite is poorly formulated. Happy computing.
You should appreciate the original intent of the transaction weight was to simulate the worst case scenario--not the best case scenario. So you need to tread cautiously (and conservatively) when computing the composite DataSet merit metric that contrasts all stocks in the DataSet. But this can be done *if* you know the salient metrics to build that composite in PreExecute. This is definitely very advanced design, and it can be dangerous if your composite is poorly formulated. Happy computing.
Thank you very much!
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