Title :
Mathematical analysis of stock market movement
Author :
Nosovskiy, Gleb V.
Author_Institution :
Fac. of Mech. & Math., Moscow State Univ., Russia
Abstract :
One of the most popular today stochastic tool for estimating future movements of financial markets and forecasting daily returns, are GARCH-type processes. In order to use such a model in practice it is necessary to estimate its parameters. There are different ways to do it, but in applications the pseudo maximum likelihood (PSD) estimation is commonly used. Important advantage of this method is that it requires minimum of a priori information concerning probability distributions of innovation processes. The author analyzes the consistency and asymptotic normality properties of PSD estimator for GARCH processes.
Keywords :
maximum likelihood estimation; statistical distributions; stochastic processes; stock markets; GARCH-type processes; PSD estimator asymptotic normality property; daily return forecasting; financial market movement estimation; innovation process probability distributions; parameter estimation; pseudo maximum likelihood estimation; stochastic tool; stock market movement mathematical analysis; Economic forecasting; Geometry; Mathematical analysis; Maximum likelihood estimation; Parameter estimation; Probability distribution; Random variables; Stochastic processes; Stock markets; Technological innovation;
Conference_Titel :
Cyberworlds, 2004 International Conference on
Print_ISBN :
0-7695-2140-1
