Inflation hedging via tracking portfolios in the BRICS markets - Vedprakash Meshram; Vaibhav Lalwani (Cogent Economics & Finance, 2024)
This study investigates the creation of portfolios that effectively hedge against inflation in the context of the stock markets of Brazil, Russia, India, China, and South Africa (BRICS). Utilizing Ordinary Least Squares (OLS), Ridge, MM, and Quantile regressions, we construct portfolios that closely track the unexpected changes in Consumer Price Index (CPI) inflation. Our empirical analysis, based on data from spanning 2005 to 2023, demonstrates that statistical tracking portfolios outperform benchmark portfolios in tracking inflation, particularly during periods of low inflation uncertainty. Among all the methods, Quantile regression generally shows good tracking performance, though not universally. The findings suggest that these tracking portfolios can assist investors who are seeking to mitigate inflationary risks in volatile emerging markets. This research contributes to the literature by demonstrating out-of-sample performance of tracking portfolios and their application in less stable economic environments. This study provides a critical analysis of constructing inflation-hedging portfolios tailored for the BRICS stock markets, utilizing advanced regression techniques such as OLS, Ridge, MM, and Quantile regressions. The results highlight the superior performance of statistical tracking portfolios in mitigating inflation risks compared to benchmark portfolios, particularly under low inflation uncertainty conditions. By addressing the challenge of inflation hedging in less stable economic environments, this study offers valuable insights for investors and contributes significantly to the field of portfolio management in emerging economies.
Keywords: G11; G12; G17; 330; BRICS; emerging markets; inflation; Inflation hedging; inflation uncertainty; out-of-sample; tracking portfolios