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Analysis of Stock Return Volatility Using GARCH Models and Panel Data in Tehran Stock Exchange

Babaei, Arash | 2008

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 39345 (44)
  4. University: Sharif University of Technology
  5. Department: Management and Economics
  6. Advisor(s): Keshavarz Haddad, Gholamreza
  7. Abstract:
  8. Due to its extensive applications in financial analysis, stock market volatility modeling is a considerably important issue for stock market practitioners and academics. Using GARCH models to formulate the conditional variance heteroskedasticity with respect to the advantages of panel data technique such as higher degrees of freedom, more flexibility in the control of the omitted or unobserved variables effects, lead to a significant increase in the accuracy of estimations. In this thesis, in order to examine the similarities and differences between the conditional variance structure of stocks in the inter and intra industries, we have used a general to specific methodology of nested tests which was pioneered by Hendry. Our dataset is consisted of panel samples of sector’s share indices and stocks returns of specific firms in each sector, in the Tehran Stock Exchange from Tir 1384(21 June 2006) to Aban 1387(22 July 2006). The results indicate that there are no similarities in the temporal volatility structures of stocks from the same sector or industry or even in a higher level, for the panel of the sample sectors in any case of mean or volatility pattern and also volatility's mean
  9. Keywords:
  10. Stock Return ; Maximum Likelihood Estimation ; Turbulence ; Panel Data ; General Autoregressive Conditional Heteroskedastic (GARCH)

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