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Random Walk Analysis with Multiple Structural Breaks: Case Study in Emerging Market of S&P BSE Sectoral Indices Stocks

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  • G Sheelapriya
  • R Murugesan

Abstract

As the consequences of high volatile and time varying mean in the financial series, it causes behavioural changes in the stochastic trend is known as a structural break. The aim is to investigate the number of unknown structural breaks for the emerging market of S&P 500 indices which are listed on BSE, by employing BP unit root tests. This empirical study examines the random walk hypothesis by testing the unit root in the presence of unknown structural breaks. The concern in the traditional unit root test is to fail the rejection of null hypothesis. This issue has been trounced by the BP tests and it significantly locates the unknown structural breaks in the data containing differed error distribution and error heteroskedasticity. In this paper, ADF, Phillips Perron and KPSS tests have been employed to examine the unit root hypothesis, and hence to predict the unknown structural breaks. Then all the sectoral indices have been forecasted in the presence of the structural breaks using Markov switching AR (1) process.

Suggested Citation

  • 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.
    • Handle: RePEc:asi:ajoerj:v:4:y:2014:i:11:p:503-513:id:3820
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