Author(s)

S. M. Abdullah¹, Mohammod Akbar Kabir¹, Kawsar Jahan², Salina Siddiqua³

¹Department of Economics, University of Dhaka, Dhaka, Bangladesh.
²Department of Accounting & Information Systems, University of Dhaka, Dhaka, Bangladesh.
³Department of Development Studies, University of Dhaka, Dhaka, Bangladesh.

An efficient and well behaved capital market can be regarded as a prerequisite for the sustainable financial development for an economy. For making the stock market efficient and reducing uncertainty, volatility measure is necessary for the policy makers. The main objective of this paper is to examine relative ability of various models to forecast future volatility and to devise appropriate volatility model for capturing variability in stock returns of Dhaka Stock Exchange (DSE). By exploiting daily data spanning from 27^th November, 2001 to 31^st July, 2013, it was found that, from volatility persistency perspective MA(2)-GARCH(2, 1) is better due to both in sample and out of sample accuracy. In contrast, from capturing asymmetric effect perspective MA(2)-EGARCH(1, 3) is better. Thus, there was no clear winner and hence the decision should depend on the purpose of the concerned people.

Stock Market, Volatility Forecasting, GARCH, EGARCH, Mean Equation

Abdullah, S. , Kabir, M. , Jahan, K. and Siddiqua, S. (2018) Which Model Performs Better While Forecasting Stock Market Volatility? Answer for Dhaka Stock Exchange (DSE). Theoretical Economics Letters, 8, 3203-3222. doi: 10.4236/tel.2018.814199.