Lecturer Profile |
Saeid Rezakhah is an associate professor (stage 32) of Amir Kabir University of Technology in Tehran, Iran. He is a doctoral tutor. He received his Ph.D. in probability statistics from Queen Mary and Westfield College, University of London in 1996. He has been a visiting professor at Michigan State University and the University of London. Professor Saeid Rezakhah's research interests include selflike process; hidden markov mixture models, periodically correlated processes, stable distributions, random polynomials; time-series analysis; stable process and information theory, etc. Currently, he has been published more than 30 papers in international academic journals. |
Lecture Abstract |
In this talk a short description of ARCH, GARCH and Markov Switch GARCH processes are presented. Then based on our recent published papers we introduce previleges of the assumption of smooth transition between the effects of positive and negative shocks as the asymmetry property of these effects. We also study the Smooth transition HYGARCH and Markov Switch HYGARCH models which combines long memory and short memory effects. In both cases estimation of the parameters, their properties and forecasting based on these models are studied and some real data sets are used to show the efficiency of our models. |
