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The Study of Nonlinear Behavior of Stock Price Index in Iran’s Securities Market (Smooth Transition Regression Approach)

Author

Listed:
  • Mohammad Nabi Shahiki Tash
  • Moslem Moradzadeh
  • Habibollah Salarzehi

Abstract

By a brief glance over the carried out studies in the field of securities market, it would be observed that in most articles, linear models have been used for time series modeling, while the results of this study reveals that the stock price index in Tehran Securities Market, has a nonlinear behavior .Therefore, it could beinferred that in most time series modeling in financial market field, have had miscalculations. This article has benefited from the positive specifications of smooth transition regression model as an approach .The results of this study show that the seasonal data for stock price index in Tehran Securities Market from 1996 to 2011 have had nonlinear behavior .Therefore, the stock price index has smooth transition auto-regression behavior (LSTAR), and consequently we can apply nonlinear STAR models for the analysis of nonlinear behavior analysis of these variables.

Suggested Citation

  • Mohammad Nabi Shahiki Tash & Moslem Moradzadeh & Habibollah Salarzehi, 2014. "The Study of Nonlinear Behavior of Stock Price Index in Iran’s Securities Market (Smooth Transition Regression Approach)," International Journal of Management Sciences, Research Academy of Social Sciences, vol. 2(10), pages 479-486.
    • Handle: RePEc:rss:jnljms:v2i10p4
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