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Incorporating Research Reports and Market Sentiment for Stock Excess Return Prediction: A Case of Mainland China
2020
Scientific Programming
The prediction of stock excess returns is an important research topic for quantitative trading, and stock price prediction based on machine learning is receiving more and more attention. This article takes the data of Chinese A-shares from July 2014 to September 2017 as the research object, and proposes a method of stock excess return forecasting that combines research reports and investor sentiment. The proposed method measures individual stocks released by analysts, separates the two
doi:10.1155/2020/8894757
fatcat:hw7h4dko6nenth3ezx5zhg2qlu