Dynamic prediction of Indian stock market: an artificial neural network approach

Himanshu Goel · Narinder Pal Singh

30 citations0/0 files storedInternational Journal of Ethics and Systems

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Stock Market Forecasting Methods Neural Networks and Applications Forecasting Techniques and Applications

Abstract

Purpose Artificial neural network (ANN) is a powerful technique to forecast the time series data such as the stock market. Therefore, this study aims to predict the Indian stock market closing price using ANNs. Design/methodology/approach The input variables identified from the literature are some macroeconomic variables and a global stock market factor. The study uses an ANN with Scaled Conjugate Gradient Algorithm (SCG) to forecast the Bombay Stock Exchange (BSE) Sensex. Findings The empirical findings reveal that the ANN model is able to achieve 93% accuracy in predicting the BSE Sensex closing prices. Moreover, the results indicate that the Morgan Stanley Capital International world index is the most important variable and the index of industrial production is the least important in predicting Sensex. Research limitations/implications The findings of the study have implications for the investors of all categories such as foreign institutional investors, domestic institutional investors and investment houses. Originality/value The novelty of this study lies in the fact that there are hardly any studies that use ANN to forecast the Indian stock market using macroeconomic indicators.

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References

2003Time series forecasting using a hybrid ARIMA and neural network model 2014Stock Price Prediction Using the ARIMA Model 2018NSE Stock Market Prediction Using Deep-Learning Models 2002Application of neural networks to an emerging financial market: forecasting and trading the Taiwan Stock Index 2008Stock market prediction of S&P 500 via combination of improved BCO approach and BP neural network 2020Optimizing LSTM for time series prediction in Indian stock market 2010Integration of genetic fuzzy systems and artificial neural networks for stock price forecasting 2014Study of Effectiveness of Time Series Modeling (Arima) in Forecasting Stock Prices

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