Revisiting the European sovereign bonds with a permutation-information-theory approach

Abstract

In this paper we study the evolution of the informational efficiency in its weak form for seventeen European sovereign bonds time series. We aim to assess the impact of two specific economic situations in the hypothetical random behavior of these time series: the establishment of a common currency and a wide and deep financial crisis. In order to evaluate the informational efficiency we use permutation quantifiers derived from information theory. Specifically, time series are ranked according to two metrics that measure the intrinsic structure of their correlations: permutation entropy and permutation statistical complexity. These measures provide the rectangular coordinates of the complexity-entropy causality plane; the planar location of the time series in this representation space reveals the degree of informational efficiency. According to our results, the currency union contributed to homogenize the stochastic characteristics of the time series and produced synchronization in the random behavior of them. Additionally, the 2008 financial crisis uncovered differences within the apparently homogeneous European sovereign markets and revealed country-specific characteristics that were partially hidden during the monetary union heyday.

20 years of ordinal patterns: Perspectives and challenges

“…The ordinal pattern probabilities and the H × C plane have been used in many different applications, among which we can mention the analysis and characterization of stochastic and coherence resonances [8,9]; of the nonlinear dynamics of chaotic lasers [10][11][12]; of the Libor market [13]; of large-scale atmospheric patterns [14,15]; of handwriten signatures [16]; of the Ecosystem Gross Primary productivity [17]; of transportation media [18]; of electric load consumption [19]; of cardiac [20,21] and brain 31001-p2 signals (Electroencephalography (EEG) and Magnetoencephalography (MEG) [22][23][24]); of textures in synthetic aperture radar (SAR) imagery [25]. Next, we discuss a few specific examples of application of these concepts in different fields.…”

Analysis of ischaemic crisis using the informational causal entropy-complexity plane

“…The use of quantifiers based on Information Theory, like entropy and statistical complexity, evaluated using the symbolic methodology proposed by Bandt and Pompe 7 in order to estimate the required probabilities (which take into account in a natural way the time causality of generated time series) has led to interesting results regarding the characterization of nonlinear chaotic dynamics, improving the understanding of their associated time series. In particular, allowing to define a causal entropy-complexity plane a diagnostic tool for discrimination of stochastic and chaotic signals, being its application goes across several disciplines, like physics, [8][9][10][11][12][13][14][15][16][17] hydrology and geophysics, [18][19][20][21][22] random and pseudorandom numbers, [23][24][25] biology, medicine, and econophysics, [26][27][28][29][30][31][32] among others. Even though these measures were successfully used to distinguish between chaos and noise, in this paper we are interested in characterizing the physiological states during an ischaemic process instead of the generating nature of dynamics itself.…”