Long Memory in VIX Futures Volatility
Författare
Summary, in English
This study provides empirical evidence for long memory in the volatility process of VIX futures returns and investigates the practical importance of modelling it when calculating Value-at-Risk (VaR) for VIX futures and pricing VIX options. The analysis is performed using the GARCH, APARCH, FIGARCH and FIAPARCH models with the normal and skewed Student-t distributions. The VaR analysis shows that the long memory FIGARCH and FIAPARCH models produce the best out-of-sample VaR forecasts. The options analysis, however, shows that the long memory in the volatility has an insignificant impact on the prices of hypothetical VIX options.
Avdelning/ar
Publiceringsår
2013
Språk
Engelska
Sidor
31-48
Publikation/Tidskrift/Serie
Review of Futures Markets
Volym
21
Issue
1
Dokumenttyp
Artikel i tidskrift
Förlag
Chicago Board of Trade
Ämne
- Economics
Status
Published
ISBN/ISSN/Övrigt
- ISSN: 0898-011X