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Modelling and Forecasting Short-Term Interest Rate Volatility: A Semiparametric Approach

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Author

  • Ai Jun HOU
  • Sandy Suardi

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.

Publishing year

2011

Language

English

Pages

692-710

Publication/Series

Journal of Empirical Finance

Volume

18

Issue

4

Document type

Journal article

Publisher

North-Holland

Topic

  • Economics

Keywords

  • Volatility esti- mation
  • GARCH modelling
  • Nonparametric method
  • Forecasts

Status

Published

ISBN/ISSN/Other

  • ISSN: 0927-5398