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Stock Market Efficiency in Developing Economies

Author

Listed:
  • Ronit Mukherji

    (The author is a Research Associate at the Indian Statistical Institute, New Delhi, India. email: ronit.mukherji1992@gmail.com)

Abstract

This article analyses the degree of stock market efficiency in three emerging economies— India, China and Brazil. It tests to see if US stock returns have an influence on endogenous stock returns, even after controlling for domestic macroeconomic variables. A country-specific vector auto-regression model is used to test the short-run effects and the fully modified ordinary least square procedure has been used to find the long-run relationship, thus checking for degree of efficiency in these stock markets. The results indicate that, despite controlling for key domestic stock return determinants, US stock returns have a significant positive relationship with the stock returns of all three countries. JEL Classification: G15, C32, C34

Suggested Citation

  • Ronit Mukherji, 2015. "Stock Market Efficiency in Developing Economies," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 9(4), pages 402-429, November.
    • Handle: RePEc:sae:mareco:v:9:y:2015:i:4:p:402-429
    DOI: 10.1177/0973801015598058
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    References listed on IDEAS

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    More about this item

    Keywords

    Emerging Market Economies; Vector Auto-regression; Panel Cointegration; Fully Modified Ordinary Least Square (FMOLS); Dynamic Ordinary Least Square (DOLS);
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models

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