Last year was challenging for quantitative equity strategies with a large proportion of them underperforming their benchmark on a rolling one-year basis. There has, therefore, been a great deal of interest in understanding the shortcomings of quantitative portfolios over the same calendar year.

  • In 2019 investors displayed a clear preference for the largest cap assets 
  • Long-only quant equity strategies as they tend to be underweight the largest names

Edward Rackham

The struggles faced by quants in 2019 were related not just to the efficacy of quantitative signals but the ability of systematic strategies to access these signals over that period – an issue exacerbated by the outperformance of large-cap stocks over smaller names. 

To further understand the difficulties faced by quants in 2019 it is informative to consider recent returns to common quantitative strategies. The compounded active performance of five simulated portfolios from the end of 2003 to the end of 2019 is given in the figure.  

What is immediately clear from the figure is that a quantitative manager implementing one or multiple of these factor portfolios would have added value over the past 15 years. What is also clear, however, is that 2019 saw a downturn in all but one of five of the common quant strategies. Such consistent underperformance across almost all strategies is unusual. Moreover, at first glance, the results are unintuitive. Certainly there were many high -quality companies with durable cash flows that performed well in 2019. Residual reversal and earnings revisions factors have proven powerful signals in different market environments and many of the ‘winners’ in 2019 continued to win throughout the year, suggesting that momentum-based strategies should also have fared well. Indeed, only the value portfolio’s underperformance in 2019 is in line with expectation as it continues the trend of negative returns that have been observed over the past five years for such strategies.

To further understand the challenges faced by quants and to rationalise investment intuition with the figure, it is helpful to consider the performance of the largest names versus the smallest names within the developed-world opportunity set over 2019. 

Overall, the compounded payoff to the size factor – the return associated with characteristic of being large capitalisation – is negative over the past 15 years, consistent with the idea that there is a premium to holding small-cap names. Performance from the end of 2017 to the end of 2019, however, has been reversed with the largest names outperforming their smaller-cap counterparts. 

Interestingly, the preference for large-cap names over mid or small-cap names was even more pronounced in 2019 conditional on those stocks also being, for example, of high momentum or high quality.  That is, high-quality stocks did well in 2019 if they were also mega caps; high-momentum stocks added value if those stocks were also amongst the index’s largest names. Indeed, this was the case for almost all of the factors in the figure last year.

Compounded active performance v2

The observation that signal efficacy is concentrated in the largest names for most of the systematic investment signals is relevant to the question of quant performance. 

Being overweight the largest names within the global benchmark requires managers to build portfolios with concentrated positions in a handful of large caps. Many quantitative investment processes tend to result in long-only diversified portfolios that hold large numbers of names so as to exploit breadth. Quant portfolios are, as a result, frequently underweight the largest names in the index irrespective of investment style.

Given that quant portfolios tend to access the smaller end of the capitalisation spectrum, the performance of the investable quant portfolios of  the figure can now be understood. The underperformance of investment strategies constructed around these signals was as much related to the portfolio’s ability to access the mega caps within the opportunity set as it was to the performance of the signals. That is, for a given quantitative investment signal in 2019, it was necessary to buy exposure to these factors amongst the largest names in the opportunity set while simultaneously avoiding the smaller end of the cap spectrum – an allocation that simply does not come naturally to most quantitative portfolios. 

Given the market environment of 2019, and the consistent performance of the largest names, it is tempting to conclude that quant managers should adjust their investment processes to account for continued mega-cap performance. While lessons must be learned from the events of 2019, there is also risk in assuming that market environments and factor behaviour will continue indefinitely. Investor preferences for factors and assets tends to be cyclical and while large-cap growth assets may continue to perform well, a change in economic fortunes could result in a different outlook. 

In the short term, however, challenges to performance may continue to plague quant investment processes if factor efficacy remains focused within the largest end of the market. Nevertheless, such an environment does not, on an ongoing basis, preclude the existence of alternative investment ideas within the broad opportunity set that are unrelated to size. Systematic managers who can find such ideas and, importantly, express those ideas efficiently within an investment portfolio may still be able to overcome the headwinds of mega-cap outperformance.

Edward Rackham is co-director of research at Los Angeles Capital

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