Conditional Heteroskedasticity in Long Memory Model 'FIMACH' for Return Volatilities in BRICS Equity Markets

20 Pages Posted: 20 Aug 2015

See all articles by Sabur Mollah

Sabur Mollah

Sheffield University Management School, University of Sheffield; Swansea Management School, Swansea University; Hull University Business School; Hull University Business School

AMM Quoreshi

Blekinge Tekniska Högskola

Date Written: August 19, 2015

Abstract

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

Suggested Citation

Mollah, Sabur and Quoreshi, AMM, Conditional Heteroskedasticity in Long Memory Model 'FIMACH' for Return Volatilities in BRICS Equity Markets (August 19, 2015). Available at SSRN: https://ssrn.com/abstract=2647307 or http://dx.doi.org/10.2139/ssrn.2647307

Sabur Mollah

Sheffield University Management School, University of Sheffield ( email )

Conduit Road
Sheffield, Sheffield S10 1FL
United Kingdom

Swansea Management School, Swansea University ( email )

Singleton Park
Swansea, Wales SA2 8PP
United Kingdom

Hull University Business School ( email )

Cottingham Road
Hull, Great Britain HU6 7RX
United Kingdom

Hull University Business School ( email )

Cottingham Road
Hull, Hull HU6 7RX
United Kingdom

AMM Quoreshi (Contact Author)

Blekinge Tekniska Högskola ( email )

SE- 37179
Karlskrona, blekinge 371 79
Sweden

Register to save articles to
your library

Register

Paper statistics

Downloads
18
Abstract Views
320
PlumX Metrics