A Look Into Risk and Returns: The Predictive Value of Risk Indicators in Emerging Market Equities

Abstract

Emerging Markets (EMs) are known to exhibit greater volatility in risk, meaning the indicators used to track risk fluctuate more than those in developed markets. This raises an important question: does the movement of risk indicators contain information that can aid in predicting returns in EM equity markets? To address this, we focused on five types of risk—credit, financial, political, economic, and composite- using values from several financial services firms. However, we found that changes in risk scores were not correlated across providers during the period studied, leading us to utilize a single provider S&P Global for sovereign credit and the International Country Risk Guide (ICRG) for the remaining risk indicators. We also modeled equity returns using pooled and country-specific Random Forest models, incorporating a range of macroeconomic variables that are relevant for return prediction. Predictive performance was evaluated using R2 and root mean squared error (RMSE), and the contribution of risk indicators was assessed through feature importance. We trained baseline models excluding risk indicators to test whether macroeconomic factors could compensate. Our results highlight the inherent difficulty of predicting equity returns: model performance was poor across the board, with R2 values near or below zero. While models that included risk indicators performed slightly better, the improvement was marginal. These findings suggest that changes in the selected risk indicators provide limited additional predictive value under the modeling approach. However, this does not necessarily mean that such indicators generally have no predictive usefulness. One plausible explanation is that equity indices may already reflect or even precede changes in these risk metrics, making any subsequent shifts in the risk indicators appear to have little effect. Further research could investigate different lags and modeling strategies to understand whether, and under what conditions, these risk indicators might enhance equity return predictions.