Trend-following and improving portfolio construction - Know your correlation matrix

 

Trend-following is more than just finding trends. Portfolio construction matters. Research has shown that positioning based on volatility will help with portfolio construction (see "Trend-following with and without volatility scaling - Two different worlds"); however, accounting for correlation will provide even more value especially if markets move to correlation extremes like what we have seen in the last decade. Accounting for correlation adapts allocations processes to incorporate the marginal contribution to risk and allows for full implementation of risk parity principles. 

Many investors discuss risk parity without understanding the dynamics or benefits when these techniques are used. I am not stating that all risk should be equalized nor am I saying that investors should not include their trend views. Using all of the information in the covariance matrix will allow investors to incorporate changes in volatility but also the changes in the relationship across markets.  In a good paper, "Trend-following. risk parity, and the influence of correlations", Nick Baltas  explains the nuances of risk parity when applied with trend-following futures markets and shows how correlation extremes harmed those who just focused solely on volatility positioning. 

The paper focuses on seemingly minor but critical change in portfolio structuring and position sizing. A normal approach to position sizing is to use volatility parity which positions solely on relative risk. Positions can be set to equal risk through using an inverse to market volatility; however, this improvement does not account for correlation between markets. Volatility parity is suboptimal especially as markets become more correlated. Including correlation centers the problem on the contribution to risk. This slicing of contributions to total risk is the essence of risk parity and will more efficiently allocate exposures through using covariance terms. 

We will dispense with the difficulties with measuring correlation which is a much more complex topic. Baltas looks at the impact of employing volatility parity, naive risk parity, versus full risk parity which is equal risk contribution. This research finds that the difference between volatility and risk parity seems small when correlations between markets are low and do not move to extremes as seen in a crisis or if there is a single market driver, but there is a world of difference in the post-GFC period when correlations have increased and moved to higher levels. 

In the post-GFC period there is a significant difference between the choice of position sizing. Notice the significant differences in Sharpe ratio between correlation regimes. The Sharpe ratio can increase by a factor of 3 when in an extreme correlation environment. Not accounting for correlation will place a drag on performance and change the Sharpe ratio even if the same signals are employed. By this time, most firms have tried to account for risk contributions; however, it is important for investors to appreciate the value of these portfolio construction improvements.

Working on better signal extraction is always critical but improvement in portfolio craftsmanship is almost as important. A good set of signals can be masked when there is poor portfolio construction. A good model can be turned into a better model through accounting for the correlation and cross-market linkages. 

Hat tip to Darren @reformedtTrader for noting this paper.