Investors in equities and bonds have been nicely rewarded since the Global Financial Crisis (GFC) as both asset classes have rallied substantially since. It has been a great dual beta trade. But fundamental investors searching for value opportunities have, by and large, struggled to outperform since 2010. Why is that so, and are these two points related?
Part of the answer is that fundamentals – the valuation metrics, such as the price-to-earnings (PE) ratio, which investors use to assess the relative attractiveness of a security’s price – have taken a back seat to central bank policy in driving price determination. All liquid assets, including equities and bonds, have rallied with the rising tide of liquidity provided by the world’s central banks. There has not been much reward for seeking out fundamental value. Either you were in the boat (ie long equities and bonds) as the tide rose or you were not. But where does the journey go from here?
The tide (ie valuations) seems pretty high. Real bond yields are hovering around zero and equities look expensive on measures such as earnings growth and the Shiller Cyclically Adjusted PE (CAPE) ratio. If both bonds and equities are expensive, the question of effective diversification becomes critical. As such, we see that investments using long-only fundamental style tilts, including value, growth or quality, are attracting more interest. But we think that this could be an unintended single factor bet: the bet that fundamentals will drive asset price moves in the near term. This factor (company and security-level fundamentals) could continue to underperform if prices remain disconnected from fundamental drivers. Instead, market technicals and macro issues – namely the size of central bank balance sheets and the methods of quantitative easing – could continue to be the main factor in determining prices.
So, how can investors diversify if the market seems expensive and to not be rewarding fundamentals?
One effective way to diversify is to invest in strategies that do not generate returns based solely on fundamental analysis. These strategies, which take positions based on price movements and other non-fundamental data, are often rules-based systematic strategies.
Systematic trading models utilise computer algorithms that assess data and make investment decisions based on information that is broader than pure fundamental valuations. These quantitative systematic strategies typically include the consideration of price factors (for example, trend, mean reversion, pattern recognition or statistical arbitrage). The bottom line is that if you can invest in quantitative strategies that are not simply long the assets you already own, and are not solely evaluating asset fundamentals, then you might find some diversification away from beta and the potentially unintended bet that fundamentals will drive prices in the short run. And that could be very valuable diversification for one’s portfolio.
This hypothesis is supported by historical performance and correlation statistics. The long-term return profile of highly liquid quantitative strategies has proved compelling as a return generator and portfolio diversifier. Using simple rules-based trend-following strategies as an example, over the past decade to August 2016, the quantitative trend-following SG Trend index has produced a 5.1% annualised return with a very low correlation to the S&P 500 of -0.02.
So, are systematic strategies a panacea in today’s investment environment? Of course not. But investing in strategies that (a) do not depend on staying long expensively priced beta, and (b) do not depend on fundamentals being rewarded by the market in the short term, offer valuable diversification.
The systematic investment universe has grown from an asset base of USD 408 billion in 2009 to some USD 880 billion today, according to Financial Times data. Investors are realising the difference that sophisticated technology can make when it comes to portfolio robustness. Interest in these strategies is creating something of a technological revolution in investment management, combining lessons learned from prior cycles with the precision, speed and cool-headed risk management of machine-based approaches.
As with any investment style, there are risks, including crowding and market reversals. But systematic strategies form part of a diversified portfolio solution. These strategies can help address the lurking risk of limited diversification in traditional portfolios today. Two of the biggest threats facing investors today are (1) that long-only traditional assets (equities and bonds) are expensive compared to history and are less likely to deliver the required returns from here, and (2) the unintended factor bet that the whole portfolio is positioned based on fundamentals, which could continue to be ignored by markets dominated by central banks’ decisions. Investors should therefore examine their portfolios closely to identify potential large factor bets and take steps to counterbalance those. Adding quantitative strategies should diversify those risks.