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

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  • Pernagallo, Giuseppe
  • Torrisi, Benedetto

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

Suggested Citation

  • Pernagallo, Giuseppe & Torrisi, Benedetto, 2019. "An empirical analysis on the degree of Gaussianity and long memory of financial returns in emerging economies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
    • Handle: RePEc:eee:phsmap:v:527:y:2019:i:c:s0378437119307538
    DOI: 10.1016/j.physa.2019.121296
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    Citations

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    Cited by:

    1. Molina-Muñoz, Jesús & Mora-Valencia, Andrés & Perote, Javier, 2020. "Market-crash forecasting based on the dynamics of the alpha-stable distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    2. Pernagallo, Giuseppe & Torrisi, Benedetto, 2020. "Blindfolded monkeys or financial analysts: Who is worth your money? New evidence on informational inefficiencies in the U.S. stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    3. Xiao, Di & Wang, Jun, 2021. "Attitude interaction for financial price behaviours by contact system with small-world network topology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    4. Salvatore Caruso & Giuseppe Pernagallo, 2021. "On the efficiency of online soccer betting markets: a new methodology based on symbolic series," Economics Bulletin, AccessEcon, vol. 41(3), pages 1451-1460.

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