Modelling and Forecasting Short-Term Interest Rate Volatility: A Semiparametric Approach
Författare
Summary, in English
This paper employs a semiparametric procedure to estimate the diffusion process of short-term interest rates. The Monte Carlo study shows that the semiparametric approach produces more accurate volatility estimates than models that accommodate asymmetry, levels e¤ect and serial dependence in the conditional variance. Moreover, the semiparametric approach yields robust volatility estimates even if the short rate drift function and the underlying innovation distribution are misspeci.ed. Empirical investigation with the U.S. three-month Treasury bill rates suggests that the semipara-metric procedure produces superior in-sample and out-of-sample forecast of short rate changes volatility compared with the widely used single-factor diffusion models. This forecast improvement has implications for pricing interest rate derivatives.
Avdelning/ar
Publiceringsår
2011
Språk
Engelska
Sidor
692-710
Publikation/Tidskrift/Serie
Journal of Empirical Finance
Volym
18
Issue
4
Fulltext
- Available as PDF - 378 kB
- Download statistics
Dokumenttyp
Artikel i tidskrift
Förlag
North-Holland
Ämne
- Economics
Nyckelord
- Volatility esti- mation
- GARCH modelling
- Nonparametric method
- Forecasts
Status
Published
ISBN/ISSN/Övrigt
- ISSN: 0927-5398