Exchange rate volatility, stock prices and returns in BRICS: The moderating effect of inflation with wavelength analysis - David Umoru; Beauty Igbinovia; Benjamin Odegha (Economic Forum, 2025)
This study aimed to evaluate the conditional effect of exchange rate volatility on stock prices and returns in the emerging markets of BRICS nations. Using daily data from 1 January 2000 to 30 December 2023, wavelet and quantile analysis were conducted. The Markov-regime model was estimated for robustness check. The wavelet scale W1 exhibited a variance of 574.7375 and a relative percentage of 20.95% in explaining stock price variability, whereas wavelet scale W3 had a variance of 288.5577 and a relative proportion of 15.54%, and wavelet scale W2 had a variance of 159.5644 and a relative proportion of 8.59%. The implication was that BRICS stock markets react significantly to cumulative economic trends over the short term and sudden movements in exchange rates. The variance contribution for returns was found to increase with short-term scales, ranging from 0.0156 for W1 to 0.0643 for W3. This increase indicated that stock returns in BRICS countries were moderately reactive to abrupt exchange rate fluctuations, immediate shifts in inflation, and money supply variations. The short-term scales capture the market's rapid responses to economic news and updates. Such sensitivity to transient economic changes aligns with the results of earlier studies. Stock prices rose in response to an increase in the inflation rate across the quantiles, while stock returns were inversely and considerably influenced by the inflation rate. Also, highly significant negative responses of stock returns to variations in the exchange rate were found under both floating and fixed exchange rate regimes. Overall, when internal inflation exerts a strong moderating influence in an economic environment marked by severe volatility, market performance becomes highly responsive to fluctuations in currency values. The findings of this research will aid in the planning and development of policies by all governments, as well as the financial industry
Keywords: 330; variation in money supply; cumulative variance; variance spectrum distribution; quantile regression; Markov-switching regression