Are Critical Slowing Down Indicators Useful to Detect Financial Crises?

Systemic Risk Tomography: Signals, Measurement and Transmission Channels, edited by Monica Billio, Loriana Pelizzon and Roberto Savona, Iste Press - Elsevier, Elsevier Science & Technology, Chapter 3, p. 73-94, December 2016.

28 Pages Posted: 4 Nov 2016 Last revised: 13 Apr 2017

See all articles by Hayette Gatfaoui

Hayette Gatfaoui

IESEG School of Management (Paris campus); Lille Economy and Management (LEM), UMR 9221

Isabelle Nagot

Université Paris I Panthéon-Sorbonne - Centre d'Economie de la Sorbonne (CES)

Philippe de Peretti

Université Paris I Panthéon-Sorbonne - Centre d'Economie de la Sorbonne (CES)

Date Written: January 15, 2016

Abstract

In this article, we consider financial markets as complex dynamical systems, and check whether the critical slowing down indicators can be used as early warning signals to detect a phase transition. Using various rolling windows, we analyze the evolution of three indicators: i) First-order autocorrelation, ii) Variance, and iii) Skewness. Using daily data for ten European stock exchanges plus the United States, and focusing on the Global Financial Crisis, our results are mitigated and depend both on the series used and the indicator. Using the main log-indices, critical slowing down indicators seem weak to predict the Global Financial Crisis. Using cumulative returns, for almost all countries, an increase in variance and skewness does precede the crisis. However, first-order autocorrelations of both log-indices and cumulative returns do not provide any useful information about the Global Financial Crisis. Thus, only some of the reported critical slowing down indicators may have informational content, and could be used as early warnings.

Keywords: Autocorrelation, Crisis, Critical slowing down, Phase transition, Skewness, Variance

Suggested Citation

Gatfaoui, Hayette and Nagot, Isabelle and de Peretti, Philippe, Are Critical Slowing Down Indicators Useful to Detect Financial Crises? (January 15, 2016). Systemic Risk Tomography: Signals, Measurement and Transmission Channels, edited by Monica Billio, Loriana Pelizzon and Roberto Savona, Iste Press - Elsevier, Elsevier Science & Technology, Chapter 3, p. 73-94, December 2016.. Available at SSRN: https://ssrn.com/abstract=2861258 or http://dx.doi.org/10.2139/ssrn.2861258

Hayette Gatfaoui (Contact Author)

IESEG School of Management (Paris campus) ( email )

Socle de la Grande Arche
1 Parvis de la Defense
Puteaux, Paris 92800
France
0033 1 5591 1010 (Phone)

HOME PAGE: http://www.ieseg.fr/enseignants-et-recherche/enseignant/?id=2443

Lille Economy and Management (LEM), UMR 9221 ( email )

Lille
France
00 33 (0)3 20 13 40 66 (Phone)
00 33 (0)3 20 13 40 70 (Fax)

HOME PAGE: http://lem.cnrs.fr/

Isabelle Nagot

Université Paris I Panthéon-Sorbonne - Centre d'Economie de la Sorbonne (CES) ( email )

106-112 Boulevard de l'hopital
106-112 Boulevard de l'Hôpital
Paris Cedex 13, 75647
France

Philippe De Peretti

Université Paris I Panthéon-Sorbonne - Centre d'Economie de la Sorbonne (CES) ( email )

106-112 Boulevard de l'hopital
106-112 Boulevard de l'Hôpital
Paris Cedex 13, 75647
France

Register to save articles to
your library

Register

Paper statistics

Downloads
83
rank
282,109
Abstract Views
445
PlumX Metrics