The Random-Walk Hypothesis on the Indian Stock Market
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- 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.
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- 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.
- Narayan, Paresh & Ali Ahmed, Huson, 2014. "Importance of Skewness in Decision Making: Evidence from the Indian Stock Exchange," Working Papers fe_2014_11, Deakin University, Department of Economics.
- Mishra, Vinod & Smyth, Russell, 2014.
"Is monthly US natural gas consumption stationary? New evidence from a GARCH unit root test with structural breaks,"
Elsevier, vol. 69(C), pages 258-262.
- Vinod Mishra & Russell Smyth, 2014. "Is Monthly US Natural Gas Consumption Stationary? New Evidence from a GARCH Unit Root Test with Structural Breaks," Monash Economics Working Papers 09-14, Monash University, Department of Economics.
- Hooi Hooi Lean & Vinod Mishra & Russell Smyth, 2016.
"Conditional convergence in US disaggregated petroleum consumption at the sector level,"
Taylor & Francis Journals, vol. 48(32), pages 3049-3061, July.
- Hooi Hooi Lean & Russell Smyth, 2015. "Conditional Convergence in US Disaggregated Petroleum Consumption at the Sector Level," Monash Economics Working Papers 03-15, Monash University, Department of Economics.
- 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.
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KeywordsIndia; Unit root; Structural Break; Stock Market; Random Walk;
- 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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