Non-parametric estimation of historical volatility

Abstract

Evolving volatility is a dominant feature observed in most financial time series and a key parameter used in option pricing and many other financial risk analyses. A number of methods for non-parametric scale estimation are reviewed and assessed with regard to the stylized features of financial time series. A new non-parametric procedure for estimating historical volatility is proposed based on local maximum likelihood estimation for the t-distribution. The performance of this procedure is assessed using simulated and real price data and is found to be the best among estimators we consider. We propose that it replaces the moving variance historical volatility estimator.

Acknowledgements

We wish to record our gratitude to Clive Granger for helpful comments and guidance during the earlier stages of this work. We are also grateful for additional comments from an anonymous referee and an Associate Editor which have led to significant improvements in the paper.

Notes

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Additional information

Notes on contributors

Martin T Lally

E-mail: [email protected]