Time series data analysis

Abstract

In this paper I review the techniques and models based on Neural and the underlying of transforming financial (times series data) to achieve best results. The review exercise enabled the discovery of the fact that researchers have found out existence of some patterns and trends in seemingly random time series. Moreover in the context of business two companies being part of the same political geographical and financial environment might have correlated time series data. The findings have been a result of combined use of Genetic Algorithms and Artificial Neural Networks. In the same context it can be said that applicability of NNs will increase where prediction is increasingly becoming important to gain edge.