The volatility of bank stock prices and macroeconomic fundamentals in the Pakistani context: an application of GARCH and EGARCH models
The volatility of bank stock prices and macroeconomic fundamentals in the Pakistani context: an application of GARCH and EGARCH models

Summary/Abstract: Research Background: The banking sector plays a crucial role in the world’s economic development. This research paper evaluates the volatility spillover, symmetric, and asymmetric effects between the macroeconomic fundamentals, i.e., market risks, interest rates, exchange rates, and bank stock returns, for the listed banks of Pakistan. Purpose of the article: The main purpose of this study is to examine the volatility of Pakistani banking stock returns due to the influence of market risk, interest rates, and exchange rates. Pakistan is selected for the study because the volatility of its banking stock returns is strongly influential in achieving sustainable economic development. Methods: By applying the OLS with the Heteroskedasticity and Autocorrelation Consistent (HAC) covariance matrix, the GARCH (1, 2), and the EGARCH (1, 1), analysis is conducted for the period from January 1, 2009 to December 31, 2019 using samples of 13 listed banks. Findings & Value added: The ARCH parameter is significant in the OLS with the HAC covariance matrix estimation, which is a clear indication of the existence of heteroskedasticity in the squared residuals and the inaccuracy of the OLS with the HAC covariance matrix. The results of the OLS with the HAC covariance matrix suggest using the GARCH model family to accurately measure the volatility of bank stock prices. The results of the mean equation in the GARCH (1, 2) and EGARCH (1, 1) indicate the positive significance of market risk and the low significance of interest and exchange rates, confirming that market returns strongly affect the sensitivity of bank stock returns compared to interest and exchange rates. It should be noted that the ARCH (α) and GARCH (β) parameters of the variance equation fulfill the non-negative conditions of the GARCH model. Furthermore, the leverage parameter (λ) is found to be positively significant for all banks, and volatility is found to be influenced by positive shocks compared to negative shocks. Conclusively, it can be stated that market returns determine the dynamics of the conditional returns of bank stocks.

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