New Strategy Performance Summary

Last week I said I would change the design of my strategy performance summaries to help compare better around the blogosphere, so here is the first example with it.

This strategy is also to show that sometimes we are so focused on the US securities market that we miss some attractive investment opportunity. As a matter of fact, I am particularly guilty on this one. I usually study the S&P 500 and its futures in my research. However for this one, I turn home to look at an ETF for Canadian Government Bonds (Yahoo ticker: XGB.TO) introduced to me in one of my classes. I tested a simple DV2 strategies using entry/exit at .5 and traded the strategy long and short. The results are below.

The results were impressive for such a simple strategies, the risk vs. return profile is also very good, I usually wouldn’t share a strategies with such good results but since it is so simple I figured why not. However, be careful with this, transaction costs would definitely impact performance. As a closing thought, I encourage you to look for trading ideas in places where you normally wouldn’t as you might be surprised by the results.

Lastly, in the post where I discuss the new strategy report, Freeman commented and made a valid point:

QF-For the Sortino Ratio why not set the MAR equal to the benchmark’s historical returns for the period under consideration? It appears unrealistic to set an acceptable %-return at 0 given the opportunity costs associated with trading any strategy. The above suggestion is just one way (albeit a simple one) to consider given the hypothetical alternatives one could have had at the time a strategy was executed.

So basically, here is the trade off, we either base the Sortino ratio on the excess return, or simply take the unprocessed return over the downside deviation. Both have their advantages, if we use the excess return, we take into account the opportunity cost of trading the strategy vs. buy and hold the benchmark. If we decide to compute the ratio using the normal return series, we gain the opportunity to put it in perspective with the Sharpe ratio as currently computed (Rf = 0%). We would basically get the Sharpe ratio computed only with the downside deviation (ie. no penalty for upside volatility). Alternatively, I could compute both measures with the excess return series. I would like reader feedback on this, so if you would just let me know in the comment section what you would prefer for the ratios and also what you think of the new performance summary as a whole, it would help me make it better for you!


13 thoughts on “New Strategy Performance Summary”

  1. The new performance summary looks great. If we got rid of the Rf=0 ratios in the new reports it’d be difficult to compare the performance of previous strategies posted as measured by those ratios… how about just keep both the unprocessed and excess return versions of the Sortino and Sharpe, e.g. have Sharpe, Sortino, SharpeER, and SortinoER (ER for excess returns)?

  2. Keep the version where MAR is set at 0% for the comparability reasons Troy mentioned. One possibility for the relative version is to use the maximum of the benchmark return and a money market fund or short-term treasuries. This way you can also account for the opportunity cost of NOT being in cash! Plus it raises the bar, since I’m assuming outperforming the S&P by 10% when it returns negative 20 might be great if you run a mutual fund but for us little guys who don’t receive asset management fees, its little consolation.

      1. QF-I agree with the statements made. I especially like the idea presented by Joshua. Good work.


  3. I’ve only been using R for a few months, and find it extremely flexible and impressive. I am curious about your statistical summary above which include “best year’ , ‘worst year’, etc. Is this home brew, of is there are package that produces this. I like the CalendarReturns, RollingPerformance, QuantMod, and a few others , but the summary statistics that I’ve used thusfar contain things I do like, but others I don’t.

    BTW – Great site !

    1. Hey Dennis,

      It is basically a group of function I put together in a meta function. Most of it comes from the PerformanceAnalytics package however. It is worth checking out, there is a whole lot of useful functions in it.



  4. Hi Qf,
    Really interesting post – thanks for sharing. I just tried re-creating your results using R, and I can’t get to them. Similar, but not as good. Are you trading a fixed size, or it is scaled in some way? Happy to send my R code through to you, if you want to compare…?

    1. tFB,

      Thank you for the comment, I used compounded results were I fully reinvested the profits back in the strategy. I can look at your R code if you want me to.



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