{"type":"ScholarlyArticle","title":"Financial Risk Prediction with Multi-Round Q&A Attention Network","authors":[{"name":"Zhen Ye","slug":"zhen-ye","given":"Zhen","family":"Ye","affiliation":"School of Information , Renmin University of China"},{"name":"Yu Qin","slug":"yu-qin","given":"Yu","family":"Qin","affiliation":"School of Information , Renmin University of China"},{"name":"Wei Xu","slug":"wei-xu","given":"Wei","family":"Xu","affiliation":"School of Information , Renmin University of China"}],"abstract":"Financial risk is an essential indicator of investment, which can help investors to understand the market and companies better. Among the many influencing factors of financial risk, researchers find the earnings conference call is the most significant one. Predicting financial volatility after the earnings conference call has been critical to beneficiaries, including investors and company managers. However, previous work mainly focuses on the feature extraction from the word-level or document-level.The vital structure of conferences, the alternate dialogue, is ignored. In this paper, we introduced our Multi-Round Q&A Attention Network, which brings into account the dialogue form in the first place. Based on the data of earnings call transcripts, we apply our model to extract features of each round of dialogue through a bidirectional attention mechanism and predict the volatility after the earnings conference call events. The results prove that our model significantly outperforms the previous state-of-the-art methods and other baselines in three different periods.","doi":"10.24963/ijcai.2020/631","url":"https://ijcai.org/proceedings/2020/631","pdf":"https://ijcai.org/proceedings/2020/0631.pdf","markdown":"https://ijcai.org/proceedings/2020/631.md","bibtex":"https://ijcai.org/proceedings/2020/bibtex/631","volume":{"slug":"2020","title":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2020","url":"https://ijcai.org/proceedings/2020/","year":2020,"location":"Yokohama","dates":"January 2021 (postponed from 11-17 July 2020)","editors":"Christian Bessiere","isbn":"978-0-9992411-6-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2020"},"section":"Special Track on AI in FinTech","track":"Special Track on AI in FinTech","number":631,"pages":{"first":4576,"last":4582},"keywords":["AI for risk and security: AI for financial risk analytics","AI for risk and security: AI for financial risk factors and prediction","Foundation for AI in FinTech: Analyzing big financial data"],"videos":[{"label":"Video","url":"https://videos.ijcai20.org/24599/file_24599.m3u8","length_sec":279,"provider":"hls"}],"references":[{"position":1,"raw":"[Agarwal et al., 2017] Vikas Agarwal, Y Eser Arisoy, and Narayan Y Naik. Volatility of aggregate volatility and hedge fund returns. Journal of Financial Economics, 125(3):491-510, 2017.","title":"Volatility of aggregate volatility and hedge fund returns","authors":"Vikas Agarwal, Y Eser Arisoy, Narayan Y Naik","year":"2017","venue":"Journal of Financial Economics","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Arora et al., 2017] Sanjeev Arora, Yingyu Liang, and Tengyu Ma. A simple but tough-to-beat baseline for sen- tence embeddings. In Proceedings of ICLR, 2017.","title":"A simple but tough-to-beat baseline for sentence embeddings","authors":"Sanjeev Arora, Yingyu Liang, Tengyu Ma","year":"2017","venue":"Proceedings of ICLR","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Bernard and Thomas, 1989] Victor L Bernard and Jacob K Thomas. Post-earnings-announcement drift: delayed price response or risk premium? Journal of Accounting re- search, 27:1-36, 1989.","title":"Post-earnings-announcement drift: delayed price response or risk premium?","authors":"Thomas ; Bernard, L Victor, Jacob K Bernard, Thomas","year":"1989","venue":"Journal of Accounting research","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Devlin et al., 2019] Jacob Devlin, Ming-Wei Chang, Ken- ton Lee, and Kristina Toutanova. BERT: Pre-training of deep bidirectional transformers for language understand- ing. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 4171-4186, Minneapo- lis, Minnesota, June 2019. Association for Computational Linguistics.","title":"BERT: Pre-training of deep bidirectional transformers for language understanding","authors":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova","year":"2019","venue":"Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Fama, 1995] Eugene F Fama. Random walks in stock mar- ket prices. Financial analysts journal, 51(1):75-80, 1995.","title":"Random walks in stock market prices","authors":"Eugene F Fama","year":"1995","venue":"Financial analysts journal","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[French et al., 1987] Kenneth R French, G William Schw- ert, and Robert F Stambaugh. Expected stock returns and volatility. Journal of financial Economics, 19(1):3-29, 1987.","title":"Expected stock returns and volatility","authors":"G Kenneth R French, Robert F William Schwert, Stambaugh","year":"1987","venue":"Journal of financial Economics","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Keith and Stent, 2019] Katherine Keith and Amanda Stent. Modeling financial analysts' decision making via the prag- matics and semantics of earnings calls. In Proceedings of ACL, pages 493-503, Florence, Italy, July 2019. Associa- tion for Computational Linguistics.","title":"Modeling financial analysts' decision making via the pragmatics and semantics of earnings calls","authors":"Stent Keith, Katherine Keith, Amanda Stent","year":"2019","venue":"Proceedings of ACL","doi":null,"url":null,"internal_url":null},{"position":8,"raw":"[Kogan et al., 2009] Shimon Kogan, Dimitry Levin, Bryan R Routledge, Jacob S Sagi, and Noah A Smith. Predicting risk from financial reports with regression. In Proceedings of NAACL-HLT, pages 272-280. Association for Compu- tational Linguistics, 2009.","title":"Predicting risk from financial reports with regression","authors":"Shimon Kogan, Dimitry Levin, Jacob S Bryan R Routledge, Noah A Sagi, Smith","year":"2009","venue":"Proceedings of NAACL-HLT","doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Larcker and Zakolyukina, 2012] David F Larcker and Anastasia A Zakolyukina. Detecting deceptive discus- sions in conference calls. Journal of Accounting Research, 50(2):495-540, 2012.","title":"Detecting deceptive discussions in conference calls","authors":"F David, Anastasia A Larcker, Zakolyukina","year":"2012","venue":"Journal of Accounting Research","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Loughran and McDonald, 2011] Tim Loughran and Bill McDonald. When is a liability not a liability? textual analysis, dictionaries, and 10-ks. The Journal of Finance, 66(1):35-65, 2011.","title":"When is a liability not a liability? textual analysis, dictionaries, and 10-ks","authors":"Mcdonald Loughran, Tim Loughran, Bill Mcdonald","year":"2011","venue":"The Journal of Finance","doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[Moreira and Muir, 2017] Alan Moreira and Tyler Muir. Volatility-managed portfolios. The Journal of Finance, 72(4):1611-1644, 2017.","title":"Volatility-managed portfolios","authors":"Alan Moreira, Tyler Muir","year":"2017","venue":"The Journal of Finance","doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Qin and Yang, 2019] Yu Qin and Yi Yang. What you say and how you say it matters: Predicting stock volatility us- ing verbal and vocal cues. In Proceedings of ACL, pages 390-401, 2019.","title":"What you say and how you say it matters: Predicting stock volatility using verbal and vocal cues","authors":"Yu Qin, Yi Yang","year":"2019","venue":"Proceedings of ACL","doi":null,"url":null,"internal_url":null},{"position":13,"raw":"[Rekabsaz et al., 2017] Navid Rekabsaz, Mihai Lupu, Artem Baklanov, Alexander Dür, Linda Andersson, and Allan Hanbury. Volatility prediction using financial disclosures sentiments with word embedding-based ir models. In Pro- ceedings of ACL, pages 1712-1721, 2017.","title":"Volatility prediction using financial disclosures sentiments with word embedding-based ir models","authors":"Navid Rekabsaz, Mihai Lupu, Artem Baklanov, Alexander Dür, Linda Andersson, Allan Hanbury","year":"2017","venue":"Proceedings of ACL","doi":null,"url":null,"internal_url":null},{"position":14,"raw":"[Sadka, 2006] Ronnie Sadka. Momentum and post-earnings- announcement drift anomalies: The role of liquidity risk. Journal of Financial Economics, 80(2):309-349, 2006.","title":"Momentum and post-earningsannouncement drift anomalies: The role of liquidity risk","authors":"Ronnie Sadka","year":"2006","venue":"Journal of Financial Economics","doi":null,"url":null,"internal_url":null},{"position":15,"raw":"[Theil et al., 2019] Christoph Kilian Theil, Samuel Broscheit, and Heiner Stuckenschmidt. Profet: Pre- dicting the risk of firms from event transcripts. In Proceedings of IJCAI, pages 5211-5217. AAAI Press, 2019.","title":"Profet: Predicting the risk of firms from event transcripts","authors":"Christoph Kilian Theil, Samuel Broscheit, Heiner Stuckenschmidt","year":"2019","venue":"Proceedings of IJCAI","doi":null,"url":null,"internal_url":"/proceedings/2019/724"},{"position":16,"raw":"[Wang et al., 2013] Chuan-Ju Wang, Ming-Feng Tsai, Tse Liu, and Chin-Ting Chang. Financial sentiment analysis for risk prediction. In Proceedings of the Sixth Interna- tional Joint Conference on Natural Language Processing, pages 802-808, 2013.","title":"Financial sentiment analysis for risk prediction","authors":"Chuan-Ju Wang, Ming-Feng Tsai, Tse Liu, Chin-Ting Chang","year":"2013","venue":"Proceedings of the Sixth International Joint Conference on Natural Language Processing","doi":null,"url":null,"internal_url":null},{"position":17,"raw":"[Wang et al., 2019] Jingjing Wang, Changlong Sun, Shoushan Li, Xiaozhong Liu, Luo Si, Min Zhang, and Guodong Zhou. Aspect sentiment classification towards question-answering with reinforced bidirectional attention network. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 3548-3557, Florence, Italy, July 2019. Association for Computational Linguistics.","title":"Aspect sentiment classification towards question-answering with reinforced bidirectional attention network","authors":"Jingjing Wang, Changlong Sun, Shoushan Li, Xiaozhong Liu, Luo Si, Min Zhang, Guodong Zhou","year":"2019","venue":"Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics","doi":null,"url":null,"internal_url":null},{"position":18,"raw":"[Yang et al., 2016] Zichao Yang, Diyi Yang, Chris Dyer, Xi- aodong He, Alex Smola, and Eduard Hovy. Hierarchical attention networks for document classification. In Pro- ceedings of NAACL-HLT, pages 1480-1489, 2016.","title":"Hierarchical attention networks for document classification","authors":"Yang","year":"2016","venue":"Proceedings of NAACL-HLT","doi":null,"url":null,"internal_url":null},{"position":19,"raw":"[Yang et al., 2019] Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan Salakhutdinov, and Quoc V. Le. Xlnet: Generalized autoregressive pretraining for lan- guage understanding. CoRR, abs/1906.08237, 2019.","title":"Xlnet: Generalized autoregressive pretraining for language understanding","authors":"Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G Carbonell, Ruslan Salakhutdinov, V Quoc, Le","year":"2019","venue":null,"doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}