Quantile Regression Estimation of Stock Market Volatility and its Causes
DOI:
https://doi.org/10.51983/ajsat-2017.6.2.991Keywords:
GARCH Model, Quantile Regression, Stock Market, Volatility, ReturnAbstract
Stock market volatility is the amount of uncertainty or risk about the size of changes in stock market security value. In this study, GARCH model was built to generate stock price volatility and quantile regression estimation was used to determine the cause of volatility in stock market at different quantile level. The study provides the graphical presentation of the coefficients estimated and the variables employed. The results of the study showed that the previous residuals (ARCH effect) are significantly contributed to stock market volatility at lower quantile level (0.1, 0.25, and 0.5) and the previous volatility significant only at higher quantile level (0.9), while only exchange rate return is significant among the external causes considered.
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