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Modeling Financial Volatility: Extreme Observations, Nonlinearities and Nonstationarities

Author

Listed:
  • Pedro J. F. de Lima

    (John Hopkins University)

  • Michelle L. Barnes

    (School of Economics, University of Adelaide)

Abstract

This paper presents a selective survey of volatility topics, with emphasis on the measurement of volatility and a discussion of some of the most important time series models commonly employed in its modelling. In particular, the paper details the long memory characteristics of volatility, and discusses its possible origins and impact on option pricing. To conclude, the paper discusses statistical tools that discriminate between nonlinearity and nonstationarity.

Suggested Citation

  • Pedro J. F. de Lima & Michelle L. Barnes, 2000. "Modeling Financial Volatility: Extreme Observations, Nonlinearities and Nonstationarities," School of Economics and Public Policy Working Papers 2000-05, University of Adelaide, School of Economics and Public Policy.
    • Handle: RePEc:adl:wpaper:2000-05
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    File URL: https://media.adelaide.edu.au/economics/papers/doc/wp2000-05.pdf
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    long memory; nonstationarity; nonlinearity; option pricing; volatility;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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