Can We Improve Sector Rotation?

Can We Improve Sector Rotation?




Can We Improve Sector Rotation?

by Corey Hoffstein, Newfound Research

  • Momentum-based sector rotation is a popular investment strategy.
  • Recent academic studies have shown that alternative implementations of standard momentum – including risk-adjusted momentum, residual momentum, and “frog-in-the-pan” momentum – can significantly improve the risk-adjusted and total return potential of stock-based momentum systems.
  • We explore whether these approaches create value for sector rotation systems.

Momentum is a system of investing that buys and sells securities based upon recent returns.  Momentum investors buy outperforming securities and avoid – or sell short – underperforming ones.

In the traditional academic implementation of momentum, hundreds of individual securities must be bought and sold.  One popular – albeit simplified – implementation of this approach is sector rotation, where investors implement a momentum strategy through industry groups or sectors.

In a past commentary[1], we demonstrated that sector rotation was entirely subsumed by the momentum factor (i.e. does not represent its own unique risk factor) and dampens total return potential.  We also found, however, that as the number of sectors utilized decreased, so did the risk of momentum crashes.  Risk-averse investors, therefore, still may find traditional sector rotation a valuable approach.

Since the momentum factor was identified and published by Jegadeesh and Titman in 1993, several other approaches have been explored and documented.  Most prominently have been risk-adjusted momentum, idiosyncratic momentum, and frog-in-the-pan momentum.

In this study, we explore whether these approaches are value-add in a traditional sector rotation approach.

Risk-Adjusted Momentum

Whereas traditional momentum looks at trading 12-1 month returns, risk-adjusted momentum scales this return figure by trailing realized volatility.

One argument for this approach is that it is secretly a multi-factor approach.  Here, we can think of 12-1 returns as our “momentum score” and inverse realized volatility as our “low volatility score.”  By multiplying them together to create a risk-adjusted momentum score, we are invoking a multi-factor scoring process somewhat similar to the “tilt-tilt” process advocated for by FTSE Russell.

Another potential argument for this approach is that by scaling by volatility, we overweight those sectors whose return has been more continuous in nature and less discrete (e.g. the return is driven by a large jump).  The rational inattention theory posits that since time is a scarce resource, investors may selectively ignore information or only obtain news on a limited frequency or with limited accuracy.  Chen and Yu (2014) found that portfolios constructed for stocks “more likely to grab attention” based on visual patterns induces investor overreaction.[2]  Indeed, momentum continuation could be induced by visually-based psychological biases.

Several studies have demonstrated the benefits of risk-adjusted momentum, including Shaik (2011) [3] and Soe (2016)[4], who find that risk-adjusted momentum creates excess risk-adjusted and total returns in large-cap U.S. equities, small-cap U.S. equities, and global equities.

Similarly, Ahti (2012)[5] finds that beta-adjusted momentum (where the anti-beta and low-volatility anomalies are close cousins) enhances global equity momentum by increasing total return and lowering volatility.

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