Extraction of sentences concerning business performance forecast and economic forecast from summaries of financial statements by deep learning

The proportion of individual investors in security markets has been rising at a rapid rate in Japan in recent times. As a result, the need for technology to support individual investors in making smarter investment decisions is ever increasing. When individual investors make investment decisions, what is the most important information they should hunt for? It is to be able to sense the company's future performance forecast. This is because even if the current performance is in the red (unfavorable) zone, stock prices will tend to rise if it shows that the future performance will recover from the enterprise side. Therefore, in this research, we focus on the financial results as an information source including performance forecasts. The summaries of financial statements include sentences concerning business performance forecast of companies and other associated sentences predicting the upcoming economic conditions. In this study, we extract and classify sentences indicating business performance forecasts and economic forecasts from summaries of financial statements. This allows individual investors to easily grasp the company's performance forecast. Our approach consists of two steps. First, our method extracts sentences relating to “prediction” by using clue expressions. Second, we automatically classify these prediction oriented sentences into two classes by using deep learning. Our method is capable of automatically generating training data for deep learning and greatly omits efforts to create the training data set by hand.