Eur. Phys. J. B 60, 111-121 (2007)
https://doi.org/10.1140/epjb/e2007-00316-y

Inefficiency in Latin-American market indices

¹ Centro de Investigaciones Ópticas, C.C. 124 Correo Central, 1900 La Plata, Argentina
² Departamento de Ciencias Básicas, Facultad de Ingeniería, Universidad Nacional de La Plata (UNLP), 1900 La Plata, Argentina
³ Departamento de Física, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, 1900 La Plata, Argentina
⁴ Banco Central do Brasil, SBS Quadra 3, Bloco B, 9 andar, DF, 70074-900, Brazil
⁵ Instituto de Física, Pontificia Universidad Católica de Valparaíso (PUCV), 23-40025, Valparaíso, Chile
⁶ Chaos & Biology Group, Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Pabellón II, Ciudad Universitaria, 1428 Ciudad de Buenos Aires, Argentina
⁷ Centre for Bioinformatics, Biomarker Discovery and Information-Based Medicine, School of Electrical Engineering and Computer Science, The University of Newcastle, University Drive, Callaghan, NSW, 2308, Australia

Corresponding author: ^a lucianoz@ciop.unlp.edu.ar

Received: 23 July 2007
Revised: 14 September 2007
Published online: 23 November 2007

Abstract

We explore the deviations from efficiency in the returns and volatility returns of Latin-American market indices. Two different approaches are considered. The dynamics of the Hurst exponent is obtained via a wavelet rolling sample approach, quantifying the degree of long memory exhibited by the stock market indices under analysis. On the other hand, the Tsallis q entropic index is measured in order to take into account the deviations from the Gaussian hypothesis. Different dynamic rankings of inefficieny are obtained, each of them contemplates a different source of inefficiency. Comparing with the results obtained for a developed country (US), we confirm a similar degree of long-range dependence for our emerging markets. Moreover, we show that the inefficiency in the Latin-American countries comes principally from the non-Gaussian form of the probability distributions.