2024 : 5 : 27

Zahra Mila Elmi

Academic rank: Professor
ORCID:
Education: PhD.
ScopusId:
Faculty: Faculty of Economics and Administrative Sciences
Address:
Phone: 09112153929

Research

Title
Modeling Tehran Stock Exchange Volatility; GARCH Approach
Type
JournalPaper
Keywords
GARCH Volatility Forecast Tehran Stock Exchange
Year
2014
Journal Journal of Applied Science and Agriculture
DOI
Researchers Esmaiel Abounoori ، Zahra Mila Elmi ، younes nademi

Abstract

The volatility of financial markets has been the object of numerous developments and applications over the past two decades, both theoretically and empirically. Portfolio managers, option traders and market makers all are interested in the possibility of forecasting volatility, with a reasonable level of accuracy. That is so important, in order to obtain either higher profits or less risky positions. Objective: we have compared different GARCH models with both Gaussian and fat-tailed conditional distribution for residuals in terms of their ability to describe and forecast volatility. Results: The best model based on MSE criteria is GARCH with normal distribution, second model is GARCH with t distribution and third model is EGARCH (1,1) with normal distribution. Conclusion: Results indicate that leverage effect exists in asymmetric models with normal distribution, but this effect does not exist in asymmetric models with t-student and GED distributions.