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An Empirical Approach To Financial Crisis Indicators Based On Random Matrices

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  • RAPHAEL DOUADY

    (Stony Brook University, John S. Toll Drive, Stony Brook, NY 11794, USA)

  • ANTOINE KORNPROBST

    (#x2020;Centre d’Economie de la Sorbonne, 106 - 112 Boulevard de l’Hôpital, Paris 75013, France)

Abstract

The aim of this work is to build a class of financial crisis indicators based on the spectral properties of the dynamics of market data. After choosing an appropriate size for a rolling window, the historical market data inside this rolling window are seen every trading day as a random matrix from which a correlation matrix is obtained. Our goal is to study the correlations between the assets that constitute this market and look for reproducible patterns that are indicative of an impending financial crisis. A weighting of the assets in the market is then introduced and is proportional to the daily traded volumes. This manipulation is realized in order to give more importance to the most liquid assets. Our financial crisis indicators are based on the spectral radius of this weighted correlation matrix. The idea behind this type of financial crisis indicators is that large eigenvalues are a sign of dynamic instability. The out-of-sample predictive power of the financial crisis indicators in this framework is then demonstrated, in particular by using them as decision-making tools in a protective put strategy.

Suggested Citation

  • Raphael Douady & Antoine Kornprobst, 2018. "An Empirical Approach To Financial Crisis Indicators Based On Random Matrices," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(03), pages 1-22, May.
    • Handle: RePEc:wsi:ijtafx:v:21:y:2018:i:03:n:s021902491850022x
    DOI: 10.1142/S021902491850022X
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    3. Raphaël Douady, 2019. "Managing the Downside of Active and Passive Strategies: Convexity and Fragilities," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-02488589, HAL.
    4. Lin, Li & Guo, Xin-Yu, 2019. "Identifying fragility for the stock market: Perspective from the portfolio overlaps network," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 132-151.

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