A Study of Behavioral Biases in Investment Decisions Using Artificial Neural Network

Abstract

Investment decisions are traditionally based on the rationality but traceably this view is contradicted and challenged by studies on behavioral finance which argues that investment decisions are affected by the cognitive error and extreme emotional bias. The impact of heuristic and cognitive driven behavior disposition interrupts the rationality of the decisions. This study aims to predict the role of behavioral biases in the investment decisions of the investors using Artificial Neural Network. It examines the effectiveness of the artificial neural network model in predicting the impact of behavioral biases on the expected rate of return. The data is collected from 310 female investors, which is trained and tested using a neural network to make predictions. Conclusion of the study indicates that the artificial neural network modeling predicts the impact of the behavioral biases on the investment decisions of the female investors with precision on the basis of the parameters considered in the study.