Stock Price Analysis Using Combination of Analyst Reports and Several Documents

In this paper, we propose a methodology of forecasting the direction and extent of volatility in mid-to long-term excess returns of stock prices by applying natural language processing and neural networks in the context of analyst reports. Analyst reports are prepared by analysts in the research departments of stock brokerage firms. We examine the contents of reports for useful information on forecasting the movements of stock prices. First, our method extracts opinion sentences from the reports while the remaining parts are classified as non-opinion sentences. Second, our method predicts stock price movements by inputting the opinion and non-opinion sentences into separate neural networks.