Recurrence Quantification Analysis of Financial Markets

Recurrence Quantification Analysis of Financial Markets

João A. Bastos (Instituto Superior de Economia e Gestao, Technical University of Lisbon, Portugal)
Copyright: © 2013 |Pages: 13
DOI: 10.4018/978-1-4666-2509-9.ch003
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Recurrence quantification analysis is a nonlinear time series analysis technique that detects deterministic dependencies in time series. This technique is particularly appropriate for modeling financial time series since it requires no assumptions on stationarity, statistical distribution, and minimum number of observations. This chapter illustrates two applications of recurrence quantification analysis to financial data: a set of international stock indices, and zero-coupon yields of US government bonds.
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Recurrence Plots

This section provides a brief introduction to recurrence plots. A comprehensive description can be found in Marwan et al. (2007). As mention in the introductory section, recurrence plots depict the different occasions when dynamical systems visit the same region of phase space. Given a scalar time series {x(i): i = 1,…,N}, a recurrence plot is constructed by first “embedding” the series into a multi-dimensional space of vectors whose coordinates are the present and lead values of the series, v(i) = {x(i), x(i+τ), x(i+2τ),…, x(i+(m-1)τ)}T.

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