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Estimating and Forecasting Asset Volatility and Its Volatility: A Markov-Switching Range Model

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  • J. Piplack

Abstract

This paper proposes a new model for modeling and forecasting the volatility of asset markets. We suggest to use the log range defined as the natural logarithm of the difference of the maximum and the minimum price observed for an asset within a certain period of time, i.e. one trading week. There is clear evidence for a regime-switching behavior of the volatility of the S&P500 stock market index in the period from 1962 until 2007. A Markov-switching model is found to fit the data significantly better than a linear model, clearly distinguishing periods of high and low volatility. A forecasting exercise leads to promising results by showing that some specifications of the model are able to clearly decrease forecasting errors with respect to the linear model in an absolute and mean square sense.

Suggested Citation

  • J. Piplack, 2009. "Estimating and Forecasting Asset Volatility and Its Volatility: A Markov-Switching Range Model," Working Papers 09-08, Utrecht School of Economics.
    • Handle: RePEc:use:tkiwps:0908
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    File URL: https://dspace.library.uu.nl/bitstream/handle/1874/309544/09_08.pdf
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    Cited by:

    1. Wenting Liu & Zhaozhong Gui & Guilin Jiang & Lihua Tang & Lichun Zhou & Wan Leng & Xulong Zhang & Yujiang Liu, 2023. "Stock Volatility Prediction Based on Transformer Model Using Mixed-Frequency Data," Papers 2309.16196, arXiv.org.

    More about this item

    Keywords

    Volatility; range; Markov-switching; GARCH; forecasting;
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