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Open AccessArticle

Word Vector Models Approach to Text Regression of Financial Risk Prediction

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School of Big Data Management, Soochow University, Taipei 11102, Taiwan
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Department of Mathematics, Soochow University, Taipei 11102, Taiwan
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Department of Accounting, Soochow University, Taipei 11102, Taiwan
*
Author to whom correspondence should be addressed.
Symmetry 2020, 12(1), 89; https://doi.org/10.3390/sym12010089
Received: 24 November 2019 / Revised: 23 December 2019 / Accepted: 30 December 2019 / Published: 2 January 2020
Linking textual information in finance reports to the stock return volatility provides a perspective on exploring useful insights for risk management. We introduce different kinds of word vector representations in the modeling of textual information: bag-of-words, pre-trained word embeddings, and domain-specific word embeddings. We apply linear and non-linear methods to establish a text regression model for volatility prediction. A large number of collected annually-published financial reports in the period from 1996 to 2013 is used in the experiments. We demonstrate that the domain-specific word vector learned from data not only captures lexical semantics, but also has better performance than the pre-trained word embeddings and traditional bag-of-words model. Our approach significantly outperforms with smaller prediction error in the regression task and obtains a 4%–10% improvement in the ranking task compared to state-of-the-art methods. These improvements suggest that the textual information may provide measurable effects on long-term volatility forecasting. In addition, we also find that the variations and regulatory changes in reports make older reports less relevant for volatility prediction. Our approach opens a new method of research into information economics and can be applied to a wide range of financial-related applications. View Full-Text
Keywords: word vector model; text regression; financial risk prediction; stock return volatility word vector model; text regression; financial risk prediction; stock return volatility
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Yeh, H.-Y.; Yeh, Y.-C.; Shen, D.-B. Word Vector Models Approach to Text Regression of Financial Risk Prediction. Symmetry 2020, 12, 89.

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