Forecasting Net Income Estimate and Stock Price Using Text Mining from Economic Reports
This paper proposes and analyzes a methodology of forecasting movements of the analysts’ net income estimates and those of stock prices. We achieve this by applying natural language processing and neural networks in the context of analyst reports. In the pre-experiment, we applied our method to extr...
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doaj-db68e1083ce34be08b6edec14adc5f662020-11-25T02:14:59ZengMDPI AGInformation2078-24892020-05-011129229210.3390/info11060292Forecasting Net Income Estimate and Stock Price Using Text Mining from Economic ReportsMasahiro Suzuki0Hiroki Sakaji1Kiyoshi Izumi2Hiroyasu Matsushima3Yasushi Ishikawa4Department of Systems Innovation, School of Engineering, The University of Tokyo, Tokyo 113-8656, JapanDepartment of Systems Innovation, School of Engineering, The University of Tokyo, Tokyo 113-8656, JapanDepartment of Systems Innovation, School of Engineering, The University of Tokyo, Tokyo 113-8656, JapanDepartment of Systems Innovation, School of Engineering, The University of Tokyo, Tokyo 113-8656, JapanNikko Asset Management Co., Ltd., Tokyo 107-6242, JapanThis paper proposes and analyzes a methodology of forecasting movements of the analysts’ net income estimates and those of stock prices. We achieve this by applying natural language processing and neural networks in the context of analyst reports. In the pre-experiment, we applied our method to extract opinion sentences from the analyst report while classifying the remaining parts<br />as non-opinion sentences. Then, we performed two additional experiments. First, we employed our proposed method for forecasting the movements of analysts’ net income estimates by inputting the opinion and non-opinion sentences into separate neural networks. Besides the reports, we inputted the trend of the net income estimate to the networks. Second, we employed our proposed method for forecasting the movements of stock prices. Consequently, we found differences between security firms, which depend on whether analysts’ net income estimates tend to be forecasted by opinions or facts in the context of analyst reports. Furthermore, the trend of the net income estimate was found to be effective for the forecast as well as an analyst report. However, in experiments of forecasting movements of stock prices, the difference between opinion sentences and non-opinion sentences was not effective.https://www.mdpi.com/2078-2489/11/6/292text mininganalyst reportforecasting net income estimateforecasting stock price |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Masahiro Suzuki Hiroki Sakaji Kiyoshi Izumi Hiroyasu Matsushima Yasushi Ishikawa |
spellingShingle |
Masahiro Suzuki Hiroki Sakaji Kiyoshi Izumi Hiroyasu Matsushima Yasushi Ishikawa Forecasting Net Income Estimate and Stock Price Using Text Mining from Economic Reports Information text mining analyst report forecasting net income estimate forecasting stock price |
author_facet |
Masahiro Suzuki Hiroki Sakaji Kiyoshi Izumi Hiroyasu Matsushima Yasushi Ishikawa |
author_sort |
Masahiro Suzuki |
title |
Forecasting Net Income Estimate and Stock Price Using Text Mining from Economic Reports |
title_short |
Forecasting Net Income Estimate and Stock Price Using Text Mining from Economic Reports |
title_full |
Forecasting Net Income Estimate and Stock Price Using Text Mining from Economic Reports |
title_fullStr |
Forecasting Net Income Estimate and Stock Price Using Text Mining from Economic Reports |
title_full_unstemmed |
Forecasting Net Income Estimate and Stock Price Using Text Mining from Economic Reports |
title_sort |
forecasting net income estimate and stock price using text mining from economic reports |
publisher |
MDPI AG |
series |
Information |
issn |
2078-2489 |
publishDate |
2020-05-01 |
description |
This paper proposes and analyzes a methodology of forecasting movements of the analysts’ net income estimates and those of stock prices. We achieve this by applying natural language processing and neural networks in the context of analyst reports. In the pre-experiment, we applied our method to extract opinion sentences from the analyst report while classifying the remaining parts<br />as non-opinion sentences. Then, we performed two additional experiments. First, we employed our proposed method for forecasting the movements of analysts’ net income estimates by inputting the opinion and non-opinion sentences into separate neural networks. Besides the reports, we inputted the trend of the net income estimate to the networks. Second, we employed our proposed method for forecasting the movements of stock prices. Consequently, we found differences between security firms, which depend on whether analysts’ net income estimates tend to be forecasted by opinions or facts in the context of analyst reports. Furthermore, the trend of the net income estimate was found to be effective for the forecast as well as an analyst report. However, in experiments of forecasting movements of stock prices, the difference between opinion sentences and non-opinion sentences was not effective. |
topic |
text mining analyst report forecasting net income estimate forecasting stock price |
url |
https://www.mdpi.com/2078-2489/11/6/292 |
work_keys_str_mv |
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