The potential investment opportunity represented by small-cap stocks within the emerging markets space — both in terms of returns and low correlation to traditional markets — is clear to many investors.
Our thesis, within this piece, is that we believe the way to maximize potential returns out of the emerging market small-cap space is a truly active investment approach of a systematic and quantitative nature.
Arguably, there are two ingredients to successful active management: a broad and diversified set of investible assets and an investment approach which seeks to maximize the alpha from the opportunity offered by such a set.
As for the first requirement — broad and diversified opportunity set — the EM small-cap segment qualifies with top marks.
To our count, this segment offers more than 4,800 stocks, thus offering the opportunity to apply return forecasting (the necessary premise to active management) to the widest possible opportunity set.
Furthermore, EM small-cap stocks display a considerable diversity in terms of their blend of characteristics, such as value (the single most relevant), growth, quality and technical attributes, thus providing the most fitting “bricks” for portfolio construction.
As for the second requirement — an investment approach which makes the most of the broad and diversified investible universe — EM small-cap, we argue, is the space where the discipline of a systematic and quantitative approach offers the biggest edge over the traditional discretionary one.
The advantage of a quantitative systematic approach, within the EM small-cap segment, can be seen along two key elements of the investment process: return forecasting and portfolio construction.
Empirical evidence suggests that an expert quantitative system has produced more accurate forecasts for emerging markets than it has for developed markets, and has been more accurate still for EM small cap. The higher forecast accuracy we have seen in EM small-cap can be explained by several reasons.
First of all, the discipline imposed by a systematic approach — which helps to counter well-documented cognitive biases and behavioral errors — is the more effective the more volatile a market is. Hence its value in EM small-cap markets, which can be notoriously very volatile.
Secondly, coverage from both investment analysts and investors is lower for EM small cap than for broad EM, which itself is much lower than coverage of developed markets. Lower coverage translates into the potential for larger and more persistent inefficiencies within EM small cap. This offers a strong environment for quantitative systems, geared, by design, to uncover and exploit pricing anomalies.
Thirdly, the challenge of using data which are timely, quantitatively sufficient, and “clean” is dealt with much more effectively by quantitative systems, whose very essence is dealing with data, rather than by traditional, essentially discretionary, managers. As it is well known, emerging markets are problematic when it comes to data, both in terms of their availability and, perhaps even more, in terms of their quality. Hence the advantage offered by a systematic and quantitative approach.
Coming to portfolio construction, one issue which is requiring increasing attention from investment managers is minimizing transaction costs which, in the current low-rate environment, can significantly eat into returns. Such a phenomenon is common across strategies and asset classes but its negative impact is higher in markets characterized by lower efficiency, liquidity and transparency, such as EM small cap, resulting in higher and more variable transaction costs.
Modeling all-in transaction costs within the portfolio construction process, as a way to help minimize them, is very much the “home turf” of quantitative managers, providing an advantage over traditional discretionary managers.
Another differentiating aspect deserves attention within the portfolio construction phase. For quantitative systematic investing the marginal cost of extending in-depth analysis to an additional security is negligible. Such an attribute not only makes possible the efficient coverage of a broad investible universe, but it also makes it relatively inexpensive to replace an expensive stock in the portfolio with a cheaper one with similarly desirable characteristics. A traditional discretionary manager, on the other hand, may spend considerable resources on fundamental research on each stock. If a stock candidate for inclusion in the portfolio turns out to be more expensive than expected, the traditional fundamental manager is faced with the unappealing choice between re-starting the expensive fundamental analysis on possible replacement stocks or trading at the increased cost.
All along the investment process, therefore, the quantitative systematic approach to EM small cap allows for a “higher level of activeness” of a portfolio, which is normally indicated by its high Active Share (as a measure of a portfolio’s degree of active management) and by its low valuations compared to market benchmarks. Importantly, both high Active Share and low valuations have been empirically shown to be positively correlated with the potential for alpha.
Quantitative systematic approaches to investment management are normally thought to be the preserve of developed, liquid, and transparent markets. Yet the economic rationale, supported by empirical evidence, indicates that the EM small-cap is the market segment where the discipline of active quantitative systems may yield the biggest edge over the discretion of traditional fundamental managers.
Patrick McCafferty is senior vice president and portfolio manager at Acadian.
