Probabilistic Momentum

Just a quick attempt to a more statistical approach wrt the rotation strategy (Antonacci's Dual Momentum and similar).

Most of the times, with these kind of strategies, the best asset (according to some momentum/trend indicator) is selected on a periodic basis (usally monthly - indipendently from the strenght of the indicator) in order to avoid market whipsaw patterns (noise) and/or excessive trading. 

A better (and simple way) is to observe the indicator each day, but then decide whether to trade or not based on its statistical significance - e.g. using the t-stat for the difference between the mean of two assets (using past average returns as indicators).

The attempt works well for two uncorrelated assets like MDY and EDV (and self.pr_lvl=0.6), even better than Antonacci's algo (higher returns and fewer trades) - but it fails for more assets: just naively increasing the prob level (self.pr_lvl) does not seem to work it. 

Need some extra working before junking it (adaptive vol control, different indicators, ...). Suggestions very welcomed.

Update Backtest

Cannot change post above, so I'll correct that here:

Main source of the algo above is the following great post:

Thanks for linking source article, I will add it to my reading list. :-)


You're welcome!


Update Backtest


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