Stock Market Price Prediction Employing Artificial Neural Network Optimized by Gray Wolf Optimization

2019 ◽  
pp. 77-87
Author(s):  
Sipra Sahoo ◽  
Mihir Narayan Mohanty
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Stock Market ◽  
Market Price ◽  
Gray Wolf ◽  
Price Prediction ◽  
Artificial Neural

scholarly journals Optimization of Artificial Neural Network for Stock Market Price Prediction Using an Enhanced Firefly Algorithm

2019 ◽  
Vol 13 (9) ◽  
pp. 532-543
Author(s):  
Ameen Ahmed Oloduowo ◽  
Fashoto Stephen Gbenga ◽  
Ogeh Clement ◽  
Balogun Abdullateef ◽  
Mashwama Petros
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Stock Market ◽  
Firefly Algorithm ◽  
Market Price ◽  
Price Prediction ◽  
Artificial Neural

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

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Himanshu Goel ◽  
Narinder Pal Singh
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Stock Market ◽  
Institutional Investors ◽  
Time Series Data ◽  
Gradient Algorithm ◽  
Series Data ◽  
Content Type ◽  
Artificial Neural ◽  
Indian Stock Market

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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