Semi-chaotic financial series and neural network. Forecasting : Evidence from European Stock Markets
Costas Siriopoulos, Raphael N. Markellos · Yugoslav journal of operations research · 1996
This study examines time series from five European Stock Markets (UK. Germany, Belgium, Spain and Greece). Based on empirical evidence concerning nonlinear dependence, long-term memory effects and low-dimensional chaos, we assess the predictability of the series and determine the appropriate parameters for neural network modelling. We apply artificial neural network forecasting data sets from the semi-chaotic Greek Stock.Exchange and utilise the outputs in the construction of a trading system. It is found that the neural network trading system performs significantly above random chance and other investment strategies.