Analysis of the Effect of News Sentiment on Stock Market Prices through Event Embedding

Stock market price prediction models have remained a prominent challenge for the investors owing to their volatile nature. The impact of macroeconomic events such as news headlines is studied here using standard dataset with closing stock rates chosen period by performing sentiment analysis Random Forest classifier. A BiLSTM time-series forecasting model constructed predict prices polarity headlines. It observed that Classifiers articles an accuracy 84.92%.