XRR: Explainable Risk Ranking for Financial Reports
學年 110
學期 1
發表日期 2021-09-13
作品名稱 XRR: Explainable Risk Ranking for Financial Reports
作品名稱（其他語言）
著者 Ting-Wei Lin; Ruei-Yao Sun; Hsuan-Ling Chang; Chuan-Ju Wang; Ming-Feng Tsai
作品所屬單位
出版者
會議名稱 ECML-PKDD 2021
會議地點 ONLINE conference
摘要 We propose an eXplainable Risk Ranking (XRR) model that uses multilevel encoders and attention mechanisms to analyze financial risks among companies. In specific, the proposed method utilizes the textual information in financial reports to rank the relative risks among companies and locate top high-risk companies; moreover, via attention mechanisms, XRR enables to highlight the critical words and sentences within financial reports that are most likely to influence financial risk and thus boasts better model explainability. Experimental results evaluated on 10-K financial reports show that XRR significantly outperforms several baselines, yielding up to 7.4% improvement in terms of ranking correlation metrics. Furthermore, in our experiments, the model explainability is evaluated by using finance-specific sentiment lexicons at word level and a newly-provided annotated reference list at the sentence level to examine the learned attention models.
關鍵字 Financial Risk Ranking;Finance Text Mining;Financial Sentiment Analysis
語言 en
收錄於
會議性質 國際
校內研討會地點 無
研討會時間 20210913~20210917
通訊作者
國別 TWN
公開徵稿
出版型式
出處
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機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/121227 )

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