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Risk estimation for short-term financial data through pooling of stable fits

Author

Listed:
  • Marzia De Donno

    (University of Parma)

  • Riccardo Donati

    (Redexe S.r.l.)

  • Gino Favero

    (University of Parma)

  • Paola Modesti

    (University of Parma)

Abstract

We suggest a new, parsimonious, method to fit financial data with a stable distribution. As a result of a stable fitting via maximum likelihood estimation (MLE), we find that some assets have similar values as stability indices, independently of the time interval considered. This fact can be exploited to pool the assets in groups and to choose a parameter $$\alpha $$α as an ex ante stability index, valid for every asset in the pool sector. With this fixed parameter, MLE is used again to obtain the other stable parameters. We discuss an innovative risk measure, based on the Expected Shortfall, which exploits the above procedure. We show that it gives a good estimation of risk even when only short time series are available. Finally, we introduce the notion of Risk Class, which allows us to classify assets according to their risk exposition and to compare different methods for the computation of the Expected Shortfall.

Suggested Citation

  • Marzia De Donno & Riccardo Donati & Gino Favero & Paola Modesti, 2019. "Risk estimation for short-term financial data through pooling of stable fits," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(4), pages 447-470, December.
    • Handle: RePEc:kap:fmktpm:v:33:y:2019:i:4:d:10.1007_s11408-019-00340-5
    DOI: 10.1007/s11408-019-00340-5
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    References listed on IDEAS

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    Cited by:

    1. Maria Cristina Arcuri & Gino Gandolfi & Fabrizio Laurini, 2023. "Robust portfolio optimization for banking foundations: a CVaR approach for asset allocation with mandatory constraints," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(2), pages 557-581, June.

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    More about this item

    Keywords

    Stable distribution; Heavy tails; Stability index; Sector pool; Expected Shortfall; Risk Class;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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