Chaotic Behavior in Financial Market Volatility

27 Pages Posted: 31 Jul 2018

See all articles by Houda Litimi

Houda Litimi

Independent

Ahmed BenSaïda

LaREMFiQ - IHEC

Lotfi BelKacem

University of Sousse - Laboratory Research for Economy, Management and Quantitative Finance (LaREMFiQ)

Oussama Abdallah

Independent

Date Written: July 24, 2018

Abstract

The study of chaotic dynamics in financial time series suffers from the nature of the collected data, which is both finite and noisy. Moreover, researchers have become less enthusiastic since a large body of the literature found no evidence of chaotic dynamics in financial returns. In this paper, we present a robust method for the detection of chaos based on the Lyapunov exponent, which is consistent even for noisy and finite scalar time series. To revitalize the debate on nonlinear dynamics in financial markets, we show that the volatility is chaotic. Applications carried out on eight major daily volatility indexes support the presence of low-level chaos. Further, our out-of-sample analysis demonstrates the superiority of neural networks, compared with other chaotic maps, in the forecasting of market volatility.

Keywords: chaos, Lyapunov exponent, market risk, neural network, nonlinear dynamics

Suggested Citation

Litimi, Houda and BenSaïda, Ahmed and BelKacem, Lotfi and Abdallah, Oussama, Chaotic Behavior in Financial Market Volatility (July 24, 2018). Journal of Risk, Forthcoming. Available at SSRN: https://ssrn.com/abstract=3218968

Houda Litimi

Independent

No Address Available
United States

Ahmed BenSaïda (Contact Author)

LaREMFiQ - IHEC ( email )

B.P. 40, Route de la ceinture
Sahloul 2
Sousse, 4054
Tunisia

Lotfi BelKacem

University of Sousse - Laboratory Research for Economy, Management and Quantitative Finance (LaREMFiQ) ( email )

Sousse
Tunisia

Oussama Abdallah

Independent

No Address Available
United States

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