We believe that rigorous, bottom-up analysis of securities based on an environmental, social and governance (“ESG”) lens offers several positives for emerging markets investors, including the potential to mitigate risk and generate superior long-term returns. However, both quantitative and fundamental investment strategies have anchored behavioral biases that prevent ESG research from garnering a more prevalent role in emerging markets investing. In this piece, we explore the root of these biases and how investors can rethink their strategies to take advantage of this missed opportunity.
The Quandary of Quant
There is no doubt that there are merits to the quantitative investment processes, none more appealing than the removal of the negative bias in decision making. However, a quantitative investing strategy is only as effective as its underlying data. Data needs to be accessible and available, cost efficient to attain, have integrity in its quality and offer enough history to make it statistically reliable. Unfortunately, in the context of ESG in emerging markets, this is not yet the case.
The data sets that are compiled are relatively immature and present a number of concerns. First, in emerging markets the leading provider has only been providing information since 2007, despite the fact that quant investors often utilize decades worth of data to build reliable models. Second, reliability issues are also a concern. While some companies report widely and completely, others are selective or haphazard in their reporting and there are no universally adopted standards. For example, a company may report with complete transparency greenhouse gas emissions in its country of domicile, but may not show that emissions have been outsourced to another jurisdiction where the company does not report any data. Hence, the true picture of the company’s performance may be vastly different to what has been disclosed.
There is another pressing concern with a purely quantitative approach. Without exception, a data-driven process embeds relativity into its assessment of securities across geographies or sectors. The result is that often an investor is forced to choose between two poor choices, where one is relatively better on ESG grounds but remains a poor choice in isolation. The consequence is that a data driven methodology will end up with toxic positions in their portfolio.
The counter argument to the quant approach is to focus on a fundamental or qualitative investment methodology incorporating ESG. This brings a whole other set of problems and makes an investor particularly vulnerable to heuristic bias.
The issues that fundamental managers are confronted with are predominantly related to the seductive charm of value or the allure of stellar growth.There always seems to be a price at which a fundamental manager will tolerate certain poor qualities, hiding under the veils of it being ‘discounted in the price’ or ‘growth cures all problems’. Even the most talented of analysts can fall victim to the tendency to interpret information in a way that confirms preconceptions.
Typically, when an analyst builds a valuation model to determine the prospective value, some form of discount rate and prospective growth rate is used to arrive at a perceived fair value. Given any prior held beliefs about the ESG qualities of the company, an analyst can skew their numbers accordingly. The analyst may not even know they are consciously biasing their models this way, but inevitably it does happen.
Risk management factors are another vital ingredient in this lethal cocktail. Far too often the relative index weight of a security plays a crucial role in determining whether a position is held in a portfolio, even if the company’s ESG practices are subpar. Investors that have an unhealthy focus on metrics such as tracking error will get concerned when they do not hold companies that comprise large positions in the index and will often choose to ‘down-weight’ a holding rather than not owning it. This becomes even more pronounced when faced with a strong valuation argument.
Combatting These Problems
To combat the biases that permeate the emerging markets investment universe, an investor needs to actively combine unbiased data analysis with qualitative insight. Serious investors in emerging markets need to be able to disintermediate decision making away from price and relative risk considerations. This is not to say investors should ignore price, quite the contrary. Paying attention to valuation is a vital part of the process and it is one of the few areas that you can control as an investor. Finally, while attention should be paid to the reference benchmark and ESG data rankings, it should not serve to mask the risk of permanent impairment of capital due to the perception of lower relative risk.
These problems present a unique opportunity for those investors that are willing to venture into previously uncharted waters. Bridging the gap between quantitative data gathering and building the links between strong governance, sustainability practices and returns to shareholders allows an investor to successfully build a differentiated investment portfolio in emerging markets where the probabilistic risk of permanent loss is tempered. We believe that embedding ESG into the investment process in this way provides a substantial long-term investment opportunity in the emerging markets.
Craig Mercer is ESG Specialist for Dalton Investments.