Abstract
We examined the presence of volatility at the Karachi Stock Exchange (recently changed the name to Pakistan Stock Exchange) (KSE) by fitting Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) model to 25 years’ index data. We found that the ARCH effects are present in the data indicating the stock market cluster volatility during the period under study. We found persistent high volatility in the stock market and presence of negative leverage effect. Moreover, we tried to identify the factors causing stock market volatility by collecting and analyzing the primary data obtained from 246 individual investors of stock market and 28 brokers listed with KSE. Our results show that investors consider political situation as the most important factor causing turbulence in the stock market. Interviews with the brokers also confirmed this. The second most important factor identified by investors is the herd behavior among investors that results in over- and underpricing of stocks and the overall market shows a volatile behavior. Our findings suggest that individual investor’s behavioral dimensions of involvement, risk attitude, and overconfidence are significantly associated with factors causing market volatility.
Highlights
Financial markets channel the savings to efficient investments to facilitate economic growth and development
We used the data of return series from January 1, 1990, to October 1, 2014, to specify Autoregressive Conditional Heteroskedasticity (ARCH), Generalized ARCH (GARCH), and Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) models to estimate volatility of Karachi Stock Exchange (KSE)-100 index returns
We found that the KSE-100 index returns series exhibited the stylized characteristics such as volatility clustering, excess kurtosis, fat-tiredness, time-varying conditional heteroskedasticity, and “leverage effect.”
Summary
Financial markets channel the savings to efficient investments to facilitate economic growth and development. We observe increased participation of the individual investors in the financial markets over time making them more “peopled.” As a result, their behavior, actions, reactions, and perceptions have a continuous impact on the stock prices that traditional models fail to explain. The objective of this study is to find out the presence of the stock market volatility and its behavioral causes at Karachi Stock Exchange (KSE), the largest and the oldest stock exchange of Pakistan. For this purpose, we use Autoregressive Conditional Heteroskedasticity (ARCH) models and its extension Generalized ARCH (GARCH) model and EGARCH.
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