Facebook (FB) Signals – Daily

From 09-Aug-16 to 12-Sep-18, these trading signals for Facebook (FB) used as directed would have performed around 10.6 times better than buy-hold.

Facebook (FB) Signals-Daily

These trading signals for FB were selected from over a million backtest results for their reward/risk and parameter sensitivity characteristics. While backtests don't always provide reliable signals which can be counted on moving forward, many traders find value in knowing what buy and sell signals would have worked well in the past.

For the 528 day (2.1 year) period from Aug 9 2016 to Sep 12 2018, these signals for Facebook, Inc. (FB) traded both long and short would have yielded $30,973 in profits from a $10,000 initial investment, an annualized return of 96.3%. Traded long only (no short selling) the signals would have returned $13,330, an annualized return of 49.9%. 83.5% of time was spent holding stock long. If you had bought and held the stock for the same period the profit would have been $2,925 (an annualized return of 13.1%).

For this type of strategy, not every signal is acted upon and signals are often reinforced. If you are long in the security, buy signals can be ignored, for example. Similarly if you are short you can ignore sell signals. For this particular FB strategy there were 79 buy signals and 16 sell signals.These led to 16 round trip long trades of which 13 were profitable, and 15 short trades of which 14 were profitable. This is a daily strategy; daily OHLC data is used to derive all signals and there is at most one buy and sell signal and one trade per day.

Drawdown (the worst case loss for an single entry and exit into the strategy) was 14% for long-short and 14% for long only, compared to 26% for buy-hold. Using drawdown plus 5% as our risk metric, and annualized return as the reward metric, the reward/risk for the trading long and short was 5.00 vs. 0.43 for buy-hold, an improvement factor of around 11.8. If traded long only, the reward/risk was 2.59.

The backtests assume a commission per trade of $7.

Multi-algorithm analysis for FB (Facebook)

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.




FB Sept 2014 to Sept 2105 FOM Optimizations


Another impressive set of returns (if you had guessed long). How did the algorithms do?

Good 10 and 25 day results, but hanging on for 50 trading days would have knocked a big hole in your profits. But,  had you held on for 99 days you would have beaten buy-hold very nicely.