Estimating Long Memory Volatility Using High-Frequency Data of Asian Stock Markets

13 Pages Posted: 21 Aug 2015 Last revised: 28 Jul 2016

See all articles by Geeta Duppati

Geeta Duppati

Waikato Management School; Waikato Management School

Anoop Kumar

Birla Institute of Technology and Science (BITS), Rajasthan Campus

Frank Scrimgeour

University of Waikato - Management School

Date Written: August 20, 2015

Abstract

This article analyzed the presence of long memory in volatility in 5 Asian equity indices namely SENSEX, CNIA, NIKKEI225, KO11 and FTSTI, using 5 minutes intraday return series ranging from 05-jan-2015 to 06-Aug-2015. The study employed ARFIMA-FIGARCH model and ARFIMA-APARCH model and compared them with GARCH (1,1) model and APARACH(1,1) in terms of in-sample forecast accuracy. The results confirmed the presence of long memory in both the return and volatility series for all the five markets under study. Among the group, CNIA and STI showed most persistence in both the return and conditional volatility. In terms of forecast measures, the long-memory GARCH models were found to be performing better compared to the short-memory GARCH models.

Keywords: Long memory, High-frequency, Equity markets, FIGARCH

JEL Classification: G12, G14, C58

Suggested Citation

Duppati, Geeta and Kumar, Anoop and Scrimgeour, Frank, Estimating Long Memory Volatility Using High-Frequency Data of Asian Stock Markets (August 20, 2015). 28th Australasian Finance and Banking Conference, Available at SSRN: https://ssrn.com/abstract=2648937 or http://dx.doi.org/10.2139/ssrn.2648937

Geeta Duppati (Contact Author)

Waikato Management School ( email )

Private Bag 3105
Hamilton, 3105
New Zealand
+64 7 838 4477 (Phone)

Waikato Management School ( email )

Hamilton, Waikato
New Zealand
+64 7 838 4477 (Phone)

Anoop Kumar

Birla Institute of Technology and Science (BITS), Rajasthan Campus

Pilani Campus
Vidya Vihar
Pilani, Rajasthan 333 031
India

Frank Scrimgeour

University of Waikato - Management School ( email )

Hamilton
New Zealand

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
168
Abstract Views
1,266
Rank
320,874
PlumX Metrics