2013’s over… Time for some reflection.
Last year, I started producing the Wisdom State of Trend Following report. The concept is very similar to the State of Trend Following report, which I’ve been running on this blog for a few years: take a diversified portfolio of futures markets, and run it through a mix of classic trend following systems over different timeframes to obtain a trend following composite index.
I worked with Shane at Wisdom Trading to make sure that the new index was closer to “real trading” than the index on this blog. In effect, we added trade friction parameters (slippage and commissions) and made sure that all products could be traded by US citizens/entities (Wisdom cover a very good range of markets but CFTC regulations prevent trading of markets such as Turkish Lira or OMX Helsinki 25).
In terms of sector balancing, my initial pick for the State of TF report was more “random”, so I made sure to have a more even split in the list of around 40 markets selected (details of individual markets and sectors can be found on Wisdom State of TF report posts, like the latest one from December and on the State of TF reports like this one for the AuTraSy version).
The end result was an index that reflected historical trend following performance fairly well in comparison to well-known benchmark indexes, but also to the actual real-life trading performance of trend following systems traded/executed by Wisdom Trading for their clients over the last one or two decades.
The Wisdom report was launched in August, but one thing puzzled me (along with some readers): despite applying very similar concepts, the YTD performance for both “State of TF” indexes showed a substantial difference. That difference lasted until the end of the year, as shown by these two charts:
The AuTraSy report ended 2013 in the black, while the Wisdom one ended fairly down. AuTraSy: +3.07% and Wisdom: -13.63%.
Why such a Difference: Trade Friction or Portfolio?
The actual code to run both reports is slightly different, so to make things easier to investigate I decided to run the same suite of systems and code for this whole comparison post. This left both report versions with two main differences: different portfolios and trade friction – included in the Wisdom one but not the AuTraSy one. Here’s a chart showing the impact of the two sources of difference:
This test gives slightly different results (Wisdom stays unchanged while AuTraSy finishes at +4.5% – the difference is due to the change of code and weights between systems in the suite). However we can see that on the whole, this AuTraSy version tracks our standard report very well (this is a good proxy and will be referred to as simply “AuTraSy” below).
A couple of figures to complement the graph:
- AuTraSy: +4.5%
- AuTraSy with friction: -3.7%
- Wisdom: -13.7%
- Wisdom/AuTraSy with friction Correlation: 0.83
So, trade friction played a large part in explaining the difference, but not the biggest part. And despite the remaining difference being around 10 percentage points, both indexes are actually quite “similar”, as shown by the correlation number. The remaining difference is only due to portfolio composition so lets’s take a closer look at this.
Study on Portfolio Differences
Narrowing down on the big winning trades, a fair number (expectedly) came from markets that were in the AuTraSy portfolio but not in the Wisdom one. Namely: Gold, Azuki Beans, Swiss MidCap Index or Japanese Yen for the largest winners.
I ran a new index version: Wisdom with additions (initial portfolio + the four products above) to see how much of the performance difference could be affected by adding these extra four markets:
Adding only four products to a portfolio of 40+ markets (less than 10% population variation) had a big impact: it made up all of the difference between the two indexes. A good illustration of how in trend following it is important not to miss any trades: any one has the potential to turn into a big winner and positively affect the whole system/portfolio performance.
We (unfortunately) never have this “hindsight” possibility of adding the best instruments after the fact. But we can trade as many markets as possible. The theory is that it will increase the probability of catching large trending moves, which should more than offset the extra losing trades from “less cooperating markets”. That’s what I wanted to check by running a test on a combined “Wisdom + AuTraSy” portfolio (overlapping products being included only once). Here’s the result (after adjusting leverage to obtain similar levels of heat/volatility):
Of course, adding many markets introduces the winning ones, but also some markets that lose money overall. However, it is interesting to note that this approach (of trading a lot more markets) gives as good a performance increase as the “hindsight” portfolio changes. A good illustration of the benefits of diversification — a recurring theme on this blog.
We’ve previous looked at how choices of portfolio composition can introduce elements of randomness in performance – something shown in the chart below (from the good, bad and ugly portfolios post, which tests 5,000 permutations of portfolio compositions and shows a large variance in the potential performance results).
We’ve also seen that adding more markets to a portfolio tends to generally increase performance and reduce the variance of results, as shown in the chart below (from the diversification – free lunch post). The clouds gradually move left and up (better risk-adjusted performance) and with less dispersion, as more products are added
In the case of “Wisdom with additions” vs “Full combination” portfolios, we can consider the former a lucky pick (albeit with hindsight bias): a dot on the top-left side of the scatter plot cloud, whereas the latter is a true random result. Adding either a lucky bias or diversification with extra markets are two ways to improve a portfolio’s performance. Only one solution does not require a crystal ball though. But it does usually require more capital. This might make it hard to implement for smaller traders.
Some ideas to work around limited capital yet still be able to benefit some of the diversification advantages have been discussed in “How to trade futures with a small account”.