In finance, several models are also based on the premise that a Gaussian distribution is followed by random variables. It is now well known that there are always extreme values in empirical evidence and can not be modelled with the Gaussian distribution. Due to their success in modelling financial data departing from the Gaussian distribution, the stable distributions, a class of probability distributions that allow skewness and heavy tails, have received great attention in the last decade. By employing stable Paretian GARCH and Threshold GARCH (TGARCH) models, this paper explores the volatility of Dow Jones Industrial Average stock returns and the trading volume. Our conclusions They suggest that the volume of trading contributes greatly to the volatility of returns on stocks. In addition, with negative shocks having a greater impact on volatility than positive shocks, significant leverage effects occur. The use of stable Paretian GARCH and TGARCH models over Gaussian models supports the probability ratio tests and goodness of fit.
Dr. Atsuyuki Naka
University of New Orleans, USA.
Dr. Ece Oral
Central Bank of the Republic of Turkey, Turkey.
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