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Aggregation and Model Construction for Volatility Models

Author

Listed:
  • Barndorf-Nielsen, O.E.
  • Shephard, N.

Abstract

In this paper we will rigourously study some of the properties of continuous time stochastic volatility models. We have five main results, including: the stochastic volatility class can be linked to Cox process based models of tick-by-tick financial data; we characterise the moments, autocorrelation function and spectrum of squared returns; based only on discrete time returns, we give a simple consistent and asymptotically normally distributed estimator of continuous time volatility models without any simulation or discretisation error.

Suggested Citation

  • Barndorf-Nielsen, O.E. & Shephard, N., 1998. "Aggregation and Model Construction for Volatility Models," Economics Papers 141, Economics Group, Nuffield College, University of Oxford.
  • Handle: RePEc:nuf:econwp:141
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    Citations

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    Cited by:

    1. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-059, New York University, Leonard N. Stern School of Business-.
    2. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2000. "Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian," Multinational Finance Journal, Multinational Finance Journal, vol. 4(3-4), pages 159-179, September.
    3. John M. Maheu & Thomas H. McCurdy, 2002. "Nonlinear Features of Realized FX Volatility," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 668-681, November.
    4. Phoebe Koundouri & Nikolaos Kourogenis & Nikitas Pittis & Panagiotis Samartzis, 2015. "Factor Models as 'Explanatory Unifiers' versus 'Explanatory Ideals' of Empirical Regularities of Stock Returns," DEOS Working Papers 1507, Athens University of Economics and Business.
    5. Yue Fang, 2000. "When Should Time be Continuous? Volatility Modeling and Estimation of High-Frequency Data," Econometric Society World Congress 2000 Contributed Papers 0843, Econometric Society.
    6. Rüdiger Frey & Wolfgang J. Runggaldier, 1999. "Risk-minimizing hedging strategies under restricted information: The case of stochastic volatility models observable only at discrete random times," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 50(2), pages 339-350, October.
    7. Stavros Degiannakis & Evdokia Xekalaki, 2007. "Assessing the performance of a prediction error criterion model selection algorithm in the context of ARCH models," Applied Financial Economics, Taylor & Francis Journals, vol. 17(2), pages 149-171.

    More about this item

    Keywords

    MODELS;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation

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