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Predicting Systemic Risk with Entropic Indicators

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  • Nikola Gradojevic

    (IÉSEG School of Management (LEM-CNRS), Lille Catholic University, France; Faculty of Technical Sciences, University of Novi Sad, Serbia; The Rimini Centre for Economic Analysis, Italy)

  • Marko Caric

    (Faculty of Economics and Engineering Management, Business Academy, Serbia)

Abstract

This paper concentrates on quantifying the behavioral aspects of systemic risk by using a novel approach based on entropy. More specifically, we study aggregate market expectations and the predictability of the systemic risk before and during the financial crisis in 2008. Two underlying signals for estimating entropic risk measures are considered: 1) skewness premium of deepest out-of-the-money options, and 2) implied volatility ratio in regards to deepest out-of-the-money options. The findings confirm the predictive and contemporaneous usefulness of our entropy setting in market risk management. The degree of predictability is closely linked to both the type of entropy and the nature of the underlying signal.

Suggested Citation

  • Nikola Gradojevic & Marko Caric, 2015. "Predicting Systemic Risk with Entropic Indicators," Working Paper series 15-14, Rimini Centre for Economic Analysis.
  • Handle: RePEc:rim:rimwps:15-14
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    References listed on IDEAS

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    1. Lisa Borland, 2002. "A theory of non-Gaussian option pricing," Quantitative Finance, Taylor & Francis Journals, vol. 2(6), pages 415-431.
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    Cited by:

    1. Casarin, Roberto & Costola, Michele, 2019. "Structural changes in large economic datasets: A nonparametric homogeneity test," Economics Letters, Elsevier, vol. 176(C), pages 55-59.
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