Neural Network Revisited: Perception on Modified Poincare Map of Financial Time Series Data
arXiv:cond-mat/0403620 · doi:10.1016/j.physa.2004.06.095
Abstract
Artificial Neural Network Model for prediction of time-series data is revisited on analysis of the Indonesian stock-exchange data. We introduce the use of Multi-Layer Perceptron to percept the modified Poincare-map of the given financial time-series data. The modified Poincare-map is believed to become the pattern of the data that transforms the data in time-t versus the data in time-t+1 graphically. We built the Multi-Layer Perceptron to percept and demonstrate predicting the data on specific stock-exchange in Indonesia.
10 pages, 11 figures