Today, I'll just throw out some more results from the multi-algorithmic testing I've been doing with SignalSolver. This time for Facebook (symbol FB). This is a stock which moved a lot in the time-frames used in the study. Could SignalSolver correctly predict and capitalize on these price movements? Let's see...
Optimizations for June 2015 through June 2016
As described in the methodology and the AMZN results, two optimizations were run on the June 2015 through June 2016 stock price data, one which rewarded raw returns using the Percentage Band, the other which rewarded more consistent returns and using the EMA band. First, lets look at Buy-hold performance for the subsequent periods:
Now lets see if the algorithms were able to exploit these price movements.
Results of the Return Optimization:
Now, the results for the Figure of Merit optimizations:
and the multi-algorithm averages:
One difference to note is that the return optimized algorithms were started out in a long state (because the End State vote indicated Long 7 to 1), whereas the FOM optimized algorithms were started out of the market because there was no good consensus. Accordingly, these returns would have been realized with lower capital.
Jan 2015 to Jan 2016 FOM Results
Here's the buy-hold results:
A pretty dramatic rise at the end of Jan 16. Luckily, all the algorithms were started long, so we got a piece of the action:
Averaging more algorithms simultaneously gave better results, for the most part. In fact for the 25 and 50 day we actually beat Buy-hold for the higher averages.