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Stock Return Predictability in Iranian Stock Market: the Application of Multifactor and Autoregressive Models Rahimi Mohammad, Shahabadi Aboulfazl Faculty of Economics and Social Sciences, Bu-Ali Sina University, Hamedan, Iran JEL Classification: G12; G14: G17 Online published on 15 April, 2014. Abstract The article examines whether the stock market is predictable, and provides evidence that several basic financial and economic factors have predictive power for the market excess return. The explanatory power of the Multifactor and Autoregressive (AR) models to the expected return of the Tehran Stock Exchange (TSE) compared with the monthly data from the 2002:01 to 2011:12. We find evidence that the predictability of Iranian stock market is at high level. The results shows that the multifactor model built with global stock market return, exchange rate and oil price factors perform considerably better than the pure autoregressive model. Top Keywords Predictability, Multifactor model, Autoregressive model, Iran. Top | |
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