论文标题
迈向收入电话和股票价格变动
Towards Earnings Call and Stock Price Movement
论文作者
论文摘要
收益电话由上市公司的管理层主持，以与分析师和投资者讨论公司的财务绩效。在收益电话期间披露的信息是分析师和投资者做出投资决策的重要数据来源。因此，我们利用收入呼叫笔录来预测未来的股票价格动态。我们建议使用深度学习框架对成绩单中的语言进行建模，在该框架中，将注意机制应用于将文本数据编码为vectors的判别网络分类器以预测股票价格变动。我们的经验实验表明，所提出的模型优于传统的机器学习基线和收益呼叫信息可以提高股票价格预测的性能。
Earnings calls are hosted by management of public companies to discuss the company's financial performance with analysts and investors. Information disclosed during an earnings call is an essential source of data for analysts and investors to make investment decisions. Thus, we leverage earnings call transcripts to predict future stock price dynamics. We propose to model the language in transcripts using a deep learning framework, where an attention mechanism is applied to encode the text data into vectors for the discriminative network classifier to predict stock price movements. Our empirical experiments show that the proposed model is superior to the traditional machine learning baselines and earnings call information can boost the stock price prediction performance.
