The market in US large-cap equities is the most liquid and competitive one among equity markets in developed countries. I often meet investors who believe that it is arbitraged to such an extent that active management is bound to fail and they therefore opt for an investment approach based on market-cap indices such as the widely followed S&P 500 index. However, greater liquidity does not mean that there are no structural biases in this market: psychologists have repeatedly shown that here too, group thinking persistently leads to sub-optimal solutions. We believe factor investing can be a simple way to profit from such biases. Here are the results.
US large caps constitute more than half the market capitalisation of developed equity markets and one third of all equities, including small caps and emerging market equities. Thus, it is hard to not talk about outperforming US large caps in any discussion about global asset allocation. Asset managers have noted that there are actually three times more funds than underlying stocks! Morningstar has registered more than 1 500 funds investing in this specific stock universe.
The value of active investment management in a crowded market
Yet, there is no market for which the debate between active and passive investing is more relevant. Despite the numerous actively managed funds available, some ETFs passively replicating the S&P 500 market-cap index have reached incredible sizes. In Europe, in particular, I meet many investors who are reticent about active investment management of US large caps since they assume that the opportunities are limited in this stock universe where abundant liquidity is reckoned to allow for rapid arbitrage of any good investment idea.
Yet, psychological studies of the way groups take decisions tell us that ‘group think’ is often inefficient. Most often, groups actually make worse decisions than the average of their individual members. Social interactions, trends, endowment effect or availability biases, among other things, trick groups into exaggerated decisions around the position of opinion leaders. The notable exception is when the decision being taken is “eureka-like”, i.e. when there is an obvious better answer that, when discovered, is easily accepted by anyone as being better.
Using a multi-factor approach to pick stocks that can outperform
But equity prices are rarely of that type. Most observers will note that markets tend to focus successively on specific events, seen as drivers for some time, although their true impact on equity prices can be questioned. In the US, at present, discussions about the Trump tariffs are all that matters, for instance, but are they really that important?
Smart beta, and more specifically multi-factor investing, takes another view. By using algorithms to select stocks, the aim is to focus on information about stocks that have been proven over decades to be capable of generating outperformance consistently. One way is to invest on the basis of four factors known to have generated outperformance:
- Low volatility.
A multi-factor approach to create ‘all-weather’ outperformance
The advantage of this approach is that instead of falling victim to the same emotions or trends, it actually capitalises on taking advantage of the systematic behavioural biases of investors. In the case of US equities, the goal is to outperform the S&P 500 index. And because it relies on the diversification of the sources of information behind these four factors, it can generate ‘all-weather’ outperformance in the medium to long-term.
The table below shows that when applied to S&P 500 stocks, a balanced approach allocating a quarter of the active risk budget (tracking error risk) to each of those four factors not only overcame the surprises of 2016, but actually benefited from the significant mood shifts in the US market during that period: this multi-factor strategy generated excess performance. It did so again both in 2017 and the first quarter of 2018. Can it beat the S&P 500? Yes, it can!
Performance attribution of a multi-factor strategy investing in S&P 500 stocks
Note: performance gross of fees, in %; all figures in USD. Source: BNP Paribas Asset Management, as of 09/04/2018