Artificial Neural Network Analysis in Finance: Evidence using a Literature Review

Abstract

Machine language is a sequence of algorithm assign to do a particular task. Neural Networking is inspired by the operation of neurons in the human brain and machine language made possible to use neural networking in data analysis. It identifies a pattern of the desired output by a set of input data. Due to the advancement of technology and its immense benefits, Neutral networking has been a popular tool in the fields of economics and finance for past decades. Instead of traditional methods accurate financial forecasting methods are invented through this technology. The usage of linear as well as the nonlinear transformation in neural networking shows the flexibility in this regard. This paper discusses the utilization of neural networking in the field of Economics and Finance by using the past literature. After providing a brief history on neural networking the paper elaborate simply on how neural network system works. Then, it includes review of relevant past literature on the topic. Finally, the paper discusses some of the limitation of using neural networking. According to the findings of the study neural networking is a powerful tool for financial forecasting which can overpower the advantages of traditional methods.