@inproceedings{a720bb010469477abce83488bd183da7,
title = "China stock market regimes prediction with artificial neural network and markov regime switching",
abstract = "This paper provides an analysis of the Shanghai Stock Exchange Composite Index Movement Forecasting for the period 1999-2009 using two competing non-linear models, univariate Markov Regime Switching model and Artificial Neural Network Model (RBF). The experiment shows that RBF is a useful method for forecasting the regime duration of the Moving Trends of Stock Composite Index. The framework employed also proves useful for forecasting Stock Composite Index turning points. The empirical results in this paper show that ANN method is preferable to Markov-Switching model to some extent.",
keywords = "Artificial neural networks, Nonparametric estimation, RBF, Regime switching",
author = "David Liu and Lei Zhang",
year = "2010",
language = "English",
isbn = "9789881701299",
series = "WCE 2010 - World Congress on Engineering 2010",
pages = "378--383",
booktitle = "WCE 2010 - World Congress on Engineering 2010",
note = "World Congress on Engineering 2010, WCE 2010 ; Conference date: 30-06-2010 Through 02-07-2010",
}