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Factor based allocation has become increasingly popular in recent years. But how to implement it in practice still remains a puzzle for many newcomers. Possible underperformance relative to a reference index is often seen as a major issue.
Academic research and many years of experience have shown that factor based solutions can help to significantly improve the profile of a portfolio, for example by reducing downside risk or enhancing long term returns.
However, it is also important to acknowledge that allocating to factors can lead to significant tracking errors and that periods of relative underperformance compared to the broader market are inevitable. These can continue uninterrupted for several years, testing the patience of many investors.
Moreover, as mentioned in a previous article of this series explaining the major challenges investors face in factor investing, numerous academic papers suggest it is impossible to successfully time factors and to predict which are going to do well or lag in the near future.
This explains why allocating to factors requires a long term investment horizon. In their famous 2009 research paper(1) analyzing the performance of the Norwegian government pension fund during the global financial crisis, Andrew Ang, William Goetzmann, and Stephen Schaefer explicitly acknowledged this “since the factors earn risk premiums over the long run”.
This also explains why many investors, who tend to choose asset managers according to their performance over the past three to five years relative to a benchmark, often see factor investing as a source of additional risk, at least in the short run. An FTSE Russell survey carried out in 2016 actually suggested that underperforming the benchmark ranked fifth among investor concerns with respect to factor oriented allocation.
Empirical research shows that in order to reap the full benefit of factor investing, clients need to consciously focus on a strategic asset allocation, as opposed to short term returns relative to a certain reference index. Therefore, the relevance of factor investing strategies should be evaluated in the same way as traditional asset classes. After all, investors don’t stop investing in equities after a few years of underperformance compared to bonds, nor should they lose sight of the long term business case when factor based strategies have had a couple of bad years.
Still, for investors reluctant to accept possible underperformance in the short term, in order to reap long term benefits, enhanced indexing provides a solution. Efficient enhanced indexing strategies are designed to systematically capture the market return and, in addition, benefit from well-rewarded factor premiums.
They take the capitalization-weighted index as a starting point. Then they give slightly more weight to stocks with favorable factor characteristics and slightly less to stocks with unfavorable factor characteristics, using proprietary investment models. This ensures the investment is relatively cost effective, while preventing overcrowding and arbitrage.
‘Enhanced indexing portfolios typically deliver moderate outperformance’
Enhanced indexing portfolios typically deliver moderate outperformance, or at least market-like returns after costs, depending on how much portfolios are allowed to deviate from their benchmark. The key performance indicator for this kind of product is the information ratio, which measures the excess returns of a portfolio relative to its benchmark.
Portfolios with greater tracking error flexibility are a better choice for investors who aim to consistently capture more of the factor premium. Our research shows that the looser the tracking error criteria, the higher the expected returns tend to be, in absolute terms.
Enhanced indexing also enables comprehensive ESG integration. For example, ranking methodologies based on sustainability scores can be introduced into the portfolio construction process. Meanwhile, passive investors either completely ignore ESG considerations or limit their efforts to rigid exclusion lists.
All these elements make enhanced indexing an attractive alternative to classic passive strategies. Decades of underwhelming active manager performance and increasing cost awareness have pushed large numbers of investors into passive strategies, often through the use of ETFs. But going passive also leads to chronic modest underperformance, once management costs are taken into account.
Furthermore, in a 2015 white paper(2), David Blitz, Head of Quantitative Equities research at Robeco, argued that enhanced indexing can also be more cost effective than alternative investments for boosting the return of a simple passive equity/bond portfolio. This is because in order to compensate for the ─ comparatively much higher ─ fees involved in alternative investment strategies, these need to achieve unreasonably high returns after costs.
Robeco’s Core Quant equity strategies follow this enhanced indexing approach. They exploit proven factor premiums such as value, quality and momentum, combined within a transparent portfolio algorithm and a unique set of risk controls, designed to consistently outperform the market after costs.
The aim of the stock selection model is to create a portfolio with holdings that, taken collectively, have the ultimate stock profile: attractive valuation, high quality, higher than average analyst revisions and positive share price momentum.
In addition, our proprietary portfolio construction algorithm features a flexible set-up, so we can easily adapt mandates to a variety of individual requirements concerning, for example, the investable universe, the risk-return profile and the integration of stricter sustainability criteria(3).