Recurrence Quantification Analysis of Wavelet Pre-Filtered Index Returns

University of Durham Economics and Finance Working Paper

Posted: 28 Jul 2003

See all articles by Antonios Antoniou

Antonios Antoniou

Wealth Associates

Costas E. Vorlow

affiliation not provided to SSRN

Date Written: June 10, 2003

Abstract

We investigate the issue of deterministic vs. stochastic dynamics in financial time series. We demonstrate a way to to reveal nonstochastic dynamical structures in daily stock market index returns, combining Recurrence Quantification Analysis (RQA) and wavelet filtering. Assuming a dynamical system generating the returns sequences, we reproduce its dynamics from the data with minimum assumptions. We reconstruct the phase-space dynamics by time-delay embedding of the wavelet denoised returns, in order to apply the RQA. The results indicate that through wavelet pre-filtering we can obtain very "clean" sequences and reveal nonstochastic dynamics. Our results also suggest the existence of chaos. We provide both quantitative and qualitative evidence supporting our findings.

Keywords: Recurrence plots, Recurrence Quantification Analysis, Wavelets, Financial time-series analysis, Chaos

JEL Classification: G14, G15, C29, Z00

Suggested Citation

Antoniou, Antonios and Vorlow, Constantinos Euripides, Recurrence Quantification Analysis of Wavelet Pre-Filtered Index Returns (June 10, 2003). University of Durham Economics and Finance Working Paper. Available at SSRN: https://ssrn.com/abstract=415361 or http://dx.doi.org/10.2139/ssrn.415361

Antonios Antoniou

Wealth Associates ( email )

Alpine House,
Honeypot Lane
London, NW9 9RX
United Kingdom

Constantinos Euripides Vorlow (Contact Author)

affiliation not provided to SSRN

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