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

Abstract

Machine language is a set of algorithms assigned to perform a specific task. Neural networks are inspired by how neurons work in the human brain and the machine language that allows neural networks to be used for data analysis. It identifies patterns of desired output from a set of input data. Thanks to technological advances and their immense benefits, neutral networking has been a popular tool in business and finance for decades. Instead of traditional methods, this technology invents an accurate financial forecasting method. Using both linear and nonlinear transformations in neural networks demonstrates flexibility. This article builds on previous literature to discuss the use of neural networks in the fields of economics and finance. This article provides a brief history of neural networks, followed by a brief description of how neural network systems work. We then review relevant previous literature on this subject. Finally, this paper discusses some limitations of using neural networks. The study found neural networking to be a powerful financial forecasting tool that outperforms traditional techniques.