Market Efficiency, Roughness and Long Memory in the PSI20 Index Returns: Wavelet and Entropy Analysis
AbstractIn this study, features of financial returns of PSI20 index, related to market efficiency, are captured using wavelet and entropy based techniques. This characterization includes the following points. First, the detection of long memory, associated to low frequencies, and a global measure of the time series: the Hurst exponent estimated by several methods including wavelets. Second, the degree of roughness, or regularity variation, associated to the Hölder exponent, fractal dimension and estimation based on multifractal spectrum. Finally, the degree of the unpredictability of the series, estimated by approximate entropy. These aspects may also be studied through the concepts of non-extensive entropy and distribution using, for instance, the Tsallis q-triplet. They allow to study the existence of efficiency in the nancial market. On the other hand, the study of local roughness is performed by considering wavelet leaders based entropy. In fact, the wavelet coefficients are computed from a multiresolution analysis, and the wavelet leaders are defined by the local suprema of these coefficients, near the point we are considering. The resulting entropy is more accurate in that detection than the Hölder exponent. These procedures enhance the capacity to identify the occurrence of financial crashes.
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Bibliographic InfoPaper provided by GEMF - Faculdade de Economia, Universidade de Coimbra in its series GEMF Working Papers with number 2013-27.
Length: 32 pages
Date of creation: Dec 2013
Date of revision:
Publication status: Published in Entropy 16: 2768-2788, 2014.
efficiency; long memory; fractal dimension; unpredictability; q-triplet; entropy; wavelets.;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
This paper has been announced in the following NEP Reports:
- NEP-ALL-2014-01-10 (All new papers)
- NEP-ETS-2014-01-10 (Econometric Time Series)
- NEP-ORE-2014-01-10 (Operations Research)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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