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New methods of estimating volatility and returns

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  • Moawia Alghalith

    (Department of Economics)

Abstract

We present a new method of estimating the asset stochastic volatility and return. In doing so, we overcome some of the limitations of the existing random walk models, such as the GARCH/ARCH models.

Suggested Citation

  • Moawia Alghalith, 2012. "New methods of estimating volatility and returns," Journal of Asset Management, Palgrave Macmillan, vol. 13(1), pages 1-4, February.
    • Handle: RePEc:pal:assmgt:v:13:y:2012:i:1:d:10.1057_jam.2011.34
    DOI: 10.1057/jam.2011.34
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    References listed on IDEAS

    as
    1. Roberto Ferulano, 2009. "A Mixed Historical Formula to forecast volatility," Journal of Asset Management, Palgrave Macmillan, vol. 10(2), pages 124-136, June.
    2. Alghalith, Moawia, 2008. "Recent applications of theory of the firm under uncertainty," European Journal of Operational Research, Elsevier, vol. 186(2), pages 443-450, April.
    3. Jaksa Cvitanic & Fernando Zapatero, 2004. "Introduction to the Economics and Mathematics of Financial Markets," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262532654, December.
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    Citations

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    Cited by:

    1. Kenneth David Strang, 2012. "Man versus math: Behaviorist exploration of post-crisis non-banking asset management," Journal of Asset Management, Palgrave Macmillan, vol. 13(5), pages 348-367, October.
    2. Moawia Alghalith & Christos Floros & Konstantinos Gkillas, 2020. "Estimating Stochastic Volatility under the Assumption of Stochastic Volatility of Volatility," Risks, MDPI, vol. 8(2), pages 1-15, April.
    3. Athanasios Tsagkanos & Konstantinos Gkillas & Christoforos Konstantatos & Christos Floros, 2021. "Does Trading Volume Drive Systemic Banks’ Stock Return Volatility? Lessons from the Greek Banking System," IJFS, MDPI, vol. 9(2), pages 1-13, April.

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