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Stochastic conditonal range, a latent variable model for financial volatility

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  • Galli, Fausto

Abstract

In this paper we introduce a parameter driven model for the dynamics of range, the stochastic conditional range (SCR). We propose to estimate its parameters by Kalman filter, importance sampling and simulated maximum likelihood depending on the hypotheses on the distributional form of the innovations. The model is applied to a large subset of the S&P 500 components. A comparison with of its fitting and forecasting abilities with the CARR model shows that the new approach can provide an interesting alternative.

Suggested Citation

  • Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54841, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:54841
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    References listed on IDEAS

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    Cited by:

    1. Xinyu Wu & Haibin Xie, 2019. "Volatility forecasting using stochastic conditional range model with leverage effect," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 35(5), pages 1156-1170, September.

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    More about this item

    Keywords

    Financial econometrics; range; volatility; importance sampling; indirect inference;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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