Open AccessCNN based Stock Market Prediction
Author(s) -
S. Guruprasad,
H Chandramouli
Publication year - 2020
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.c5282.029320
Subject(s) - stock market , stock market prediction , convolutional neural network , stock (firearms) , econometrics , computer science , artificial intelligence , economics , engineering , geography , context (archaeology) , archaeology , mechanical engineering
Indian Stock market is highly dynamic and especially after globalization stock market modeling has become even more complex due to influence of multiple parameters. In presence of multiple parameters, some parameters have increased influence than others in prediction of stock market trends. This influence of individual parameters and their joint influence over time is better modeled with Convolutional Neural Network Classifiers. This work models the dynamics of stock market in terms of Convolutional Neural Networks and multiple parameters impacting the stock trend. The proposed solution is implemented for Indian stock market for stocks in different sectors to prove its prediction accuracy.