Long Term and Short Term Investment Strategy for Predicting the Performance of BSE using MLP Model

Background/Objectives: Now a day’s stock market has great influence in the daily life of people. The biggest problem of stock market is that it holds large uncertainties which are directly related to their long term and short term investment. The key objective of researchers in this area is to strengthen economy as well as profit maximization on individual share. Methods/Statistical Analysis: This study, adopted a most popular back propagation training algorithm for predicting the performance of Bombay Stock Exchange of India based on long term and short term basis. In this study, 3500 samples of nine different companies are considered are divided 60% for training, 20% for validation and remaining 20% for testing task. In the initial phase the data underwent five phases which includes variable selection, data preprocessing, training dataset, prediction and evaluation. However the research evaluated through MATLAB tool which consists of training performance, error rate, and output prices. After getting the output from various evaluations made on stock dataset. Findings: It is shown by experimental results the method has given more accurate prediction results. Besides, it takes less training time and epochs for prediction task. It is also found that long term investment also has more successive returns over short term investment. Applications/Improvements: In the present study back propagation method is employed for long term and short term prediction. The different experimental results are carried out on stock data sets. It is also observed by study for long span of time small scale and medium scale companies like HCL and Ambuja Cement have better performance compared to large scale companies like TCS. In contrast, short span of time large scale companies like TCS also have better performance.