| dc.description.abstract | This paper seeks to model the dynamic relationship between stock market returns, volatility and
trading volume in both developed and emerging stock markets. Modeling stock returns volatility
has a tremendous reflection of the stock market microstructure behavior. We model this
relationship using GARCH model, which previously has been used and reproduced most stylized
facts of financial time series data, and compare its results with those of Regime-Switching and
Markov-Switching GARCH. The results indicate evidence of volatility clustering, leverage
effects and leptokurtic distribution for the index returns. Moreover, we find that all the three
stock markets are characterized by return series process staying in low volatility regime for a
long time than in high volatility regime. Markov-Switching GARCH (1, 1) model is reported to
be a better model than GARCH (1, 1). | en_US |
