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An empirical analysis on the degree of Gaussianity and long memory of financial returns in emerging economies

Giuseppe Pernagallo and Benedetto Torrisi

Physica A: Statistical Mechanics and its Applications, 2019, vol. 527, issue C

Abstract: In this work we investigated empirically if the behaviour of daily log-returns of 12 emerging economies’ stock market indices corroborates the “fat tails” hypothesis and if these series show long memory. These findings are important to assess the probability of observing “extreme” events, the distribution for financial models and the predictability of returns for these economies. Graphical techniques and statistical tests suggest the non-normality of daily returns of these indices, whereas the Student’s t-distribution and the stable Paretian distribution model adequately the data. The Hurst exponents oscillate between 0.51 and 0.62 proving that a certain degree of long memory is present in the series. Our findings show that the stock market of emerging economies is highly similar to stock markets of developed Countries

Keywords: Fat-tails; Financial time series; Hurst exponent; Kernel density; Memory; Stylized facts (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:527:y:2019:i:c:s0378437119307538

DOI: 10.1016/j.physa.2019.121296

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Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

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