Volatility patterns of stock prices

Abstract

Research on stock exchange markets is essential to stock market investors as it offers sensitivities to risk management. This research investigates the patterns of the volatility of stock market prices in ten African stock markets. We estimated the dynamic GARCH model of Engle using the method of maximum likelihood estimation. Daily time series from January 1, 2021 to December 30, 2022, were obtained from African Stock (Securities) Exchange database. The findings established the existence of a normally distributed Senegalese stock market as against time-varying volatility of stock prices in Nigeria, Ghana, Mali, Burkina Faso, Togo, Niger Republic, Benin Republic, Ivory Coast, and Gambian. Hence, the likelihood that an asset or stock is being overpriced (overvalued) or underpriced (undervalued) in the Senegal stock market is low. It is therefore easier for stock traders and investors in Senegal to pick entry and exit points. Unfortunately, this cannot be said of the investors in stock markets of other countries. In effect, the closing price of a stock is most often heavily deviated with significant outliers. This further infers that variations of stock prices in these markets are very wide, heavy, and unpredicted. Hence, it is a case of the volatility of volatilities.

Keywords

• volatility
• african stock market
• time-varying conditional standard deviation
• patterns of volatility
• variation of stock prices
• leptokurtic distribution