Open AccessStock Market Prediction using Artificial Neural Network & Text Mining
Author(s) -
*Dr.Jibendu Kumar Mantri*,
Amiya Kumar Sahoo,
Subal Kumar Pradhan,
Debabrat Dehury
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.e6624.018520
Subject(s) - stock market , autoregressive conditional heteroskedasticity , artificial neural network , econometrics , estimator , volatility (finance) , stock market prediction , stock (firearms) , stock price , computer science , economics , financial economics , artificial intelligence , mathematics , engineering , statistics , geography , geology , mechanical engineering , paleontology , context (archaeology) , archaeology , series (stratigraphy)
The art of prediction of stock market volatility has always been a most challenged interdisciplinary research problem among scientist due to its highly non- linear nature of market flow. This paper tries to analysis the historical data of BSE Sensex using extreme volatilities estimators, GARCH, ANN and new proposed Text Mining approach for stock market predictions. Finally experimental results illustrates that the new proposed Text model can able to predict the volatilities of the stock price better than other models.