Until recently, emerging market stocks were among the many darlings of the investing world. And why not? For most investors, a potentially diversifying asset class with the prospect of high returns looks as if a present. For energetic managers, EM stocks represent the chance to take a position in a less efficient market segment and thus reveal their investment skills.
However, over the past five years or so, the prospect of EM equities as an asset class has diminished somewhat. This is as a result of the significantly poorer performance of EM stocks in comparison with their developed market counterparts.
EM stock performance in comparison with US stock performance
Five-year annualized returns
| MSCI EM Index | 1.31% |
| S&P 500 | 11.34% |
However, not all EM equity strategies have disillusioned. EM factor strategies – particularly multi-factor EM equity approaches – have performed well each in absolute terms and relative to the broader EM equity universe. Here we offer an summary of the evolving landscape of EM equity investing and describe a multi-factor investment process that has avoided the pitfalls of its EM equity counterparts.
The changing landscape of emerging markets
Some emerging countries haven’t exhausted their development potential lately. Others have fallen victim to political or military unrest. Turkey and Russia, for instance, once played outstanding roles on this area but have since fallen out of favor and are either given much lower weightings in core indices or excluded altogether. On the opposite hand, Saudi Arabia and Thailand, amongst others, have significantly increased their weightings in the identical indices.
Investing in emerging markets has develop into more complicated and due to this fact managers must adopt more sophisticated approaches to successfully understand and manage emerging market portfolios. For example, expertise in Russia and Turkey is not any longer as precious because it once was, so managers must expand their knowledge of the newer entrants within the investable EM basket. Of course, such expertise will not be achieved overnight. Those fundamental managers who don’t depend on a quantitative process must develop the abilities crucial to navigate the brand new EM landscape. This represents an enormous challenge.
MSCI EM Index: Market weights as of March 31, 2023
How to reap equity factor premiums in emerging market stocks
The following graphic shows EM stocks and their performance numbers. In particular, over the past three years, a multi-factor EM strategy built using the method described below has covered the broad EM market represented by the MSCI EM Index, in addition to standard EM equity factor strategies and energetic EM Exchanges outperformed -traded funds (ETFs) usually.
The query is: how was this achievement achieved?
EM Stock Performance: Absolute Returns
| MSCI Emerging Markets Index | Robust EM multi-factor strategy | MSCI Emerging Markets Diversified Multi-Factor Index | Active EM ETF aggregate | EM multi-factor ETF aggregate | |
| course of the yr (December 31, 2022 to June 30, 2023) |
5.10% | 9.18% | 4.33% | 6.04% | 4.53% |
| A yr | 2.22% | 11.76% | 4.27% | 2.78% | 3.29% |
| Three years | 2.71% | 8.08% | 6.61% | 2.78% | 4.65% |
| Five years | 1.31% | 2.33% | 2.22% | 1.96% | 0.68% |
How to develop a sturdy emerging market equity factor strategy
These results are the results of a four-step investment process. At the core of our methodology are six stock aspects which have been validated by dozens of researchers over time: value, momentum, size, low volatility, profitability and low investment. Not only do these aspects have clear economic interpretations, but they’ve also resulted in reliable and well-documented systematic premiums in various regions and market environments. This is partly as a result of their low correlation with one another, as shown within the figure below.
Low factor correlations mean more consistent cyclicality
Long-short factor correlations
Step 1
We first construct portfolios for every individual factor and choose our stocks from the broader EM universe. In the primary phase of our process, we filter stocks based on their unique exposure to a particular factor – for instance, value.
step 2
Next, we evaluate the remaining stocks for his or her individual exposure to the precise factor portfolio in query, in addition to their exposure to other aspects. The goal of this step is to further refine the portfolio stocks based on their overall “factor intensity,” or the sum of their individual exposures (betas) to the broad range of things. In this manner, each individual factor portfolio maintains a powerful bias towards the specified factor and a positive exposure to other aspects without sacrificing exposure to its goal. This is especially useful in a multi-factor context as investors want exposure to all rewarded aspects.
Low factor correlations allow multi-factor investors to smooth out cyclicality
| December 31, 1970 to December 31, 2022 |
Low volatility |
Small Size |
Value | High Momentum |
High profitability |
Low investment |
| Single factor envelopes without factor intensity filters | ||||||
| Exposure to what’s desired Factor propensity |
0.17 | 0.26 | 0.26 | 0.15 | 0.23 | 0.30 |
| Factor intensity | 0.31 | 0.40 | 0.51 | 0.31 | 0.41 | 0.45 |
| Single factor envelopes with factor intensity filter | ||||||
| Exposure to what’s desired Factor propensity |
0.16 | 0.24 | 0.26 | 0.17 | 0.25 | 0.26 |
| Factor intensity | 0.47 | 0.71 | 0.72 | 0.58 | 0.58 | 0.60 |
step 3
After choosing the stocks in our portfolio, we generate portfolio weights for every stock using 4 optimization schemes: maximum deconcentration, diversified risk weighting, maximum decorrelation, and maximum Sharpe ratio.
There are two reasons. First, we wish to remove any residual idiosyncratic, stock-specific risks from our factor portfolios. Our goal is to reap factor premiums, not trade “names.” Second, since no modeling method is error-free, we also wish to mitigate any latent model risk in an optimization model.
Step 4
Finally, we weight each individual factor portfolio equally to create a final multi-factor EM strategy. Why an evenly weighted allocation of all risk aspects? Because it avoids estimation risk and allows investors to make the most of decorrelation and the cyclicality of their premium, because the figure below shows.
Equal weighting maximizes the utility of factor decorrelation
Annual returns of long-short reward aspects
Diploma
Many EM equity strategies have experienced poor absolute and relative performance lately, largely as a result of the changing nature of the EM investable universe. The development of several previous EM leaders stalled or succumbed to political volatility, and plenty of fundamentally focused energetic managers have didn’t adapt.
Our quantitative multi-factor strategy offers an antidote to the challenges of EM equity investing. It has performed well relative to emerging markets usually and with energetic managers within the space. Why? Because the emphasis is on diversification, risk control and crop factor premiums over stock picking.
So there’s hope for investors on the lookout for a sturdy emerging markets equity strategy to enhance their other equity investments.
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Photo credit: ©Getty Images / Dar1930
