Volatility Long Memory on Option Valuation: Component Garch versus Fractionally Integrated GARCH

37 Pages Posted: 24 Jul 2009 Last revised: 19 Nov 2009

Date Written: July 23, 2009

Abstract

Volatility long memory is a stylized fact that has been documented for a long time. Existing literature have two ways to model volatility long memory: component volatility models and fractionally integrated volatility models. This paper develops a new fractionally integrated GARCH model, and investigates its performance by using the Standard and Poor’s 500 index returns and cross-sectional European option data. The fractionally integrated GARCH model significantly outperforms the simple GARCH(1, 1) model by generating 37% less option pricing errors. With stronger volatility persistence, it also dominates a component volatility model, who has enjoyed a reputation for its outstanding option pricing performance, by generating 15% less option pricing errors. We also confirm the fractionally integrated GARCH model’s robustness with the latest option prices. This paper indicates that capturing volatility persistence represents a very promising direction for future study.

Keywords: option valuation, long memory, fractional integration, NGARCH, long-run

JEL Classification: C22,G13

Suggested Citation

Wang, Yintian, Volatility Long Memory on Option Valuation: Component Garch versus Fractionally Integrated GARCH (July 23, 2009). Available at SSRN: https://ssrn.com/abstract=1438001 or http://dx.doi.org/10.2139/ssrn.1438001

Yintian Wang (Contact Author)

Tsinghua University ( email )

Beijing, 100084
China

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

Paper statistics

Downloads
197
Abstract Views
1,033
Rank
278,522
PlumX Metrics