In the last post , we tested a momentum strategy using the Rate of Change indicator. Using ROC (12month), gave us pretty good results when testing it on the SPX index. Based on these results, I wondered if this strategy would work on a basket of securities.
To test this , I quickly coded this strategy in Quantopian. Quantopian is a platform that allows users to code their trading strategy in python, and run it in real time with your broker.For this test, we'll use 10 sectors ETFs ( XLF','XLK','XLI','XLY','XLV','XLB', 'IDU','XLE','XLP','IYZ'). The backtest will take place from 12/01/2002 to 12/31/2015 , representing more than 10 years of data. We'll compare the results to the SPY ETF, that tracks the S&P 500 index.
Total Return : 157.7 %
Annual Return : 8 %
Sharpe : .68
Max DD : 18.5 %
Not bad ! The strategy worked pretty well using these ETF. The cumulative return of the strategy is superior to the SPY as it avoided the 2008 financial crisis .
A Max DD of 18.5 % seems a bit high for the average investors. This could be fix by choosing asset will relatively low volatility , or changing the allocation of our basket.
At the end of the day, this simple momentum strategy is pretty good in my opinion. One can use this as the foundation to build a more complex momentum strategy. The trades used in my Journal are based on momentum. I encourage anyone to make some research on this topic. You can expect more post on momentum in the near future.