Forecasting Emerging Market Volatility in Crisis Period: Comparing Traditional GARCH with High-Frequency Based Models

Abdullah Yalaman () and Shabir A. A. Saleem ()
Additional contact information
Abdullah Yalaman: School of Business Administration, Eskisehir Osmangazi Universitesi IIBF
Shabir A. A. Saleem: School of Business Administration, Eskisehir Osmangazi Universitesi IIBF

A chapter in Global Financial Crisis and Its Ramifications on Capital Markets, 2017, pp 475-492 from Springer

Abstract: Abstract This chapter discusses the topic of modeling and forecasting volatility in emerging market and presents the strength and weakness of the several high-frequency based approaches available in the literature. We compare the forecasting performance of traditional GARCH with high-frequency based models namely, HAR-RV, HAR-RV-J, and HAR-RV-CJ under the financial crisis and non-financial crisis periods. We extend our study scope by focusing not only on general market index BIST-30, but also on each constituent of market index. Our empirical results indicate that the global financial crisis does not affect the forecasting performance of the models in emerging markets. All high-frequency based volatility forecasting models perform better than the traditional ARCH-class models in both non-crisis and crisis periods. We conclude our paper with the statement that high-frequency based models do not affect the structural break in the underlying process. The best outperforming model among the high-frequency based volatility models for both stable and turmoil period is HAR-RV-CJ model. The empirical findings for the individual stocks are consistent with the general market index ISE-30.

Keywords: Stochastic Volatility; Forecast Performance; Market Index; Crisis Period; Stochastic Volatility Model (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:conchp:978-3-319-47021-4_33

Ordering information: This item can be ordered from
http://www.springer.com/9783319470214

DOI: 10.1007/978-3-319-47021-4_33

Access Statistics for this chapter

More chapters in Contributions to Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().