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The Random-Walk Hypothesis on the Indian Stock Market

Author

Listed:
  • Ankita Mishra
  • Vinod Mishra
  • Russell Smyth

Abstract

We test the random-walk hypothesis for the Indian stock market by applying three unit root tests with two structural breaks. We find that unit root tests that allow for two structural breaks alone are not able to reject the unit root null; however, a recently developed unit root test that simultaneously accounts for heteroskedasticity and structural breaks finds that the stock indexes are mean reverting. Our results point to the importance of addressing heteroskedasticity when testing for a random walk with high-frequency financial data.

Suggested Citation

  • Ankita Mishra & Vinod Mishra & Russell Smyth, 2015. "The Random-Walk Hypothesis on the Indian Stock Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 51(5), pages 879-892, September.
    • Handle: RePEc:mes:emfitr:v:51:y:2015:i:5:p:879-892
    DOI: 10.1080/1540496X.2015.1061380
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    Cited by:

    1. Kulikova, Maria V. & Taylor, David R. & Kulikov, Gennady Yu., 2024. "Evolving efficiency of the BRICS markets," Economic Systems, Elsevier, vol. 48(1).
    2. Dash, M., 2019. "Testing the Random Walk Hypothesis in the Indian Stock Market Using ARIMA Modelling," Journal of Applied Management and Investments, Department of Business Administration and Corporate Security, International Humanitarian University, vol. 8(2), pages 71-77, May.
    3. Nartea, Gilbert V. & Valera, Harold Glenn A. & Valera, Maria Luisa G., 2021. "Mean reversion in Asia-Pacific stock prices: New evidence from quantile unit root tests," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 214-230.
    4. Mishra, Vinod & Smyth, Russell, 2014. "Is monthly US natural gas consumption stationary? New evidence from a GARCH unit root test with structural breaks," Energy Policy, Elsevier, vol. 69(C), pages 258-262.
    5. Hooi Hooi Lean & Vinod Mishra & Russell Smyth, 2016. "Conditional convergence in US disaggregated petroleum consumption at the sector level," Applied Economics, Taylor & Francis Journals, vol. 48(32), pages 3049-3061, July.
    6. Hooi Hooi Lean & Russell Smyth, 2015. "Testing for weak-form efficiency of crude palm oil spot and future markets: new evidence from a GARCH unit root test with multiple structural breaks," Applied Economics, Taylor & Francis Journals, vol. 47(16), pages 1710-1721, April.
    7. Mishra, Ankita & Mishra, Vinod, 2018. "Is there conditional convergence in the per capita incomes of BIMAROU states in India?," Economic Modelling, Elsevier, vol. 70(C), pages 429-437.
    8. Hooi Hooi Lean & Vinod Mishra & Russell Smyth, 2015. "Is investing in Islamic stocks profitable? Evidence from the Dow Jones Islamic market indexes," Monash Economics Working Papers 33-15, Monash University, Department of Economics.
    9. Narayan, Paresh Kumar & Ahmed, Huson Ali, 2014. "Importance of skewness in decision making: Evidence from the Indian stock exchange," Global Finance Journal, Elsevier, vol. 25(3), pages 260-269.
    10. G. Sheelapriya & R. Murugesan, 2014. "Random walk analysis with multiple structural breaks: Case study in emerging market of S&P BSE sectoral indices stocks," Asian Journal of Empirical Research, Asian Economic and Social Society, vol. 4(11), pages 503-513, November.
    11. Qishui Chi & Jieyi Huo, 2017. "An Empirical Study on the Stock Price Volatility of Small and Medium Enterprise Board in China," Research in World Economy, Research in World Economy, Sciedu Press, vol. 8(2), pages 12-24, December.
    12. Janet Jyothi Dsouza & T. Mallikarjunappa, 2015. "Does the Indian Stock Market Exhibit Random Walk?," Paradigm, , vol. 19(1), pages 1-20, June.
    13. Adedoyin Isola LAWAL & Ezekiel OSENI & Abiola John ASALEYE & Bukola LAWAL-ADEDOYIN & Rachael OJEKA-JOHN, 2021. "Is the Stock Market Efficient? Evidence from Nonlinear Unit Root Tests for Nigeria," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 11(5), pages 384-395, May.

    More about this item

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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