Conditional Heteroskedasticity in Long Memory Model 'FIMACH' for Return Volatilities in BRICS Equity Markets
20 Pages Posted: 20 Aug 2015
Date Written: August 19, 2015
This paper introduces a new class of long memory model for volatility of stock returns, and applies the model on squared returns for BRICS (Brazil, Russia, India, China, and South Africa) countries. The conditional first- and second-order moments are provided. The CLS, FGLS and QML estimators are discussed. Empirically, we find evidence of long memory for squared return series for BRICS countries. In its estimation, the FIMACH model outperforms the FIGARCH and ARFIMA models.
Keywords: Long Memory Conditional Heteroskedastic Model, Return Volatility, BRICS
JEL Classification: C13, C22, C25, C51, G01, G12, G14, G17
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