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Absolute Return Volatility

Author

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  • John Cotter

    (University College Dublin)

Abstract

The use of absolute return volatility has many modelling benefits. An illustration is given for the market risk measure, minimum capital requirements.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • John Cotter, 2011. "Absolute Return Volatility," Working Papers 200415, Geary Institute, University College Dublin.
    • Handle: RePEc:ucd:wpaper:200415
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    File URL: http://www.ucd.ie/geary/static/publications/workingpapers/gearywp200415.pdf
    File Function: First version, 2004
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    References listed on IDEAS

    as
    1. repec:bla:manchs:v:70:y:2002:i:5:p:666-81 is not listed on IDEAS
    2. C. Brooks & A. D. Clare & G. Persand, 2002. "A Note on Estimating Market–based Minimum Capital Risk Requirements: A Multivariate GARCH Approach," Manchester School, University of Manchester, vol. 70(5), pages 666-681, September.
    3. John Cotter, 2004. "Minimum capital requirement calculations for UK futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 24(2), pages 193-220, February.
    4. Longin, Francois M., 2000. "From value at risk to stress testing: The extreme value approach," Journal of Banking & Finance, Elsevier, vol. 24(7), pages 1097-1130, July.
    5. Neil Shephard & Ole E. Barndorff-Nielsen, 2003. "Power variation and stochastic volatility: a review and some new results," Economics Series Working Papers 2003-W19, University of Oxford, Department of Economics.
    6. Longin, Francois M, 1996. "The Asymptotic Distribution of Extreme Stock Market Returns," The Journal of Business, University of Chicago Press, vol. 69(3), pages 383-408, July.
    7. Ole E. Barndorff-Nielsen & Svend Erik Graversen & Neil Shephard, 2003. "Power variation & stochastic volatility: a review and some new results," Economics Papers 2003-W19, Economics Group, Nuffield College, University of Oxford.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Luisa Bisaglia & Matteo Grigoletto, 2018. "A new time-varying model for forecasting long-memory series," Papers 1812.07295, arXiv.org.
    2. Luisa Bisaglia & Matteo Grigoletto, 2021. "A new time-varying model for forecasting long-memory series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 139-155, March.
    3. Arouxet, M. Belén & Bariviera, Aurelio F. & Pastor, Verónica E. & Vampa, Victoria, 2022. "Covid-19 impact on cryptocurrencies: Evidence from a wavelet-based Hurst exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).

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    More about this item

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G0 - Financial Economics - - General

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