Political risk is widely presumed to affect emerging market equities. However, its impact has historically been difficult to assess due to the lack of quantifiable, systematic, and standardized political risk metrics.
The growing popularity of alternative data derived from natural language processing and sentiment analysis of global news media has opened new opportunities in the political risk space, including novel methods of devising systematic investment and asset allocation frameworks that are uniquely informed by a new generation of political risk indicators.
To take advantage of this development, S&P Dow Jones Indices has collaborated with GeoQuant, an AI-driven political risk data firm, to devise a best-in-class Emerging Markets Political Risk-Tilted Concept Index (hereafter the “Political Risk-Tilted Concept Index” or "Concept Index").
The Concept Index takes the S&P Emerging BMI as its starting point and rebalances country allocations monthly based on GeoQuant's custom "Macro-Government Political Risk Indicator," yielding the Political Risk-Tilted Concept Index by overweighting (underweighting) countries with relatively low (high) political risk.
We find that systematically incorporating political risk as a factor into emerging market equity allocation decisions can potentially drive outperformance relative to the benchmark S&P Emerging BMI. Outperformance is largely attributable to reduced overall volatility and greater insulation from downside risk.
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Over a 2013-2020 back-test period, the Concept Index outperformed the S&P Emerging BMI using a standard set of back-test parameters. Specifically, the Concept Index yielded higher return/risk ratios over three-and five-year horizons, and on a cumulative basis over the full back-tested period, with an annualized excess return of 1.31% relative to its benchmark. It also demonstrated a consistently lower level of volatility, a relatively low annualized tracking error of 2.03%, and a lower monthly average turnover than its benchmark. On a monthly basis, the back-tested Concept Index outperformed the S&P Emerging BMI in the majority of all months, and in a larger majority of down months in which benchmark returns decreased. The back-test also outperformed the S&P Emerging BMI over 2020 despite well-known challenges in forecasting equity market performance during the COVID-19 pandemic.
The Political Risk-Tilted Concept Index is the first of its kind (to the best of our knowledge) and offers novel opportunities to leverage S&P Dow Jones Indices and GeoQuant data to inform emerging market equity allocation decisions.
MEASURING POLITICAL RISK: AN OVERVIEW
GeoQuant is a venture-backed, AI-driven political risk data firm that fuses political science and machine learning to systematically measure and predict political risks in real-time.
Well before COVID-19, the interplay of macro-economic policymaking and government (in)stability, and the lack of high-frequency data to measure these factors, made it notoriously difficult to assess the impact of political risk on equity prices, particularly in emerging markets. Technical advances in monitoring and predicting political risk were necessary.
To that end, GeoQuant has developed a best-in-class set of more than 20 political risk indicators for modeling and understanding the impact of political risk on markets. These indicators enable data-driven and systematic asset allocation in response to measurable, real-time variation in political risk.
Exhibit 1 provides a snapshot of GeoQuant’s core set of risk indicators, which collectively comprise GeoQuant’s "Fundamental Risk Model." The indicators measure the full spectrum of risks that are likely to affect commerce, trading, investment decisions, and intergovernmental relations. All indicators are generated by real-time natural language processing of traditional news media using proprietary algorithms for text-based sentiment analysis, as well as synchronous inputs and review by a team of PhD political economists.