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| Review of Textual Sentiment Research in Financial Markets |
Li Helong1,Ren Changsong1,Liu Xinru1,Wang Cunhua2( ) |
1School of Economics and Finance, South China University of Technology, Guangzhou 510006, China
2School of Economics and Management, North China Institute of Aerospace Engineering, Langfang 065000, China |
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Abstract [Objective] This paper analyzes and summarizes the current situation of the development of text sentiment in financial markets, and provides reference for subsequent related research. [Coverage] We used “financial market”, “text sentiment analysis”, “text sentiment” and “investor sentiment” as keywords to search on academic platforms such as CNKI, Web of Science and Google Academic, and extended the search for relevant literatures. A total of 115 papers were reviewed. [Methods] We classified the extracted text sentiment according to the type of the source financial text, then introduced the framework of text sentiment analysis, and finally sorted out the relevant research results on the impact of text sentiment on the financial markets. [Results] Text sentiment in financial markets can be divided into information reporting sentiment, news media sentiment and social media sentiment. In the construction of sentiment indicators, dictionary-based methods and machine learning-based methods are widely used. The above three text sentiments have a certain impact on the financial markets. [Limitations] Due to the universality of text analysis methods in various fields, the selected literature on the framework of text sentiment analysis is not entirely focused on the financial markets. [Conclusions] When constructing financial text sentiment indicators, we should choose the appropriate sentiment analysis method according to the text characteristics, research conditions and research objectives.
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Received: 24 August 2022
Published: 22 March 2023
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| Fund:Fundamental Research Funds for the Central Universities(ZDPY202209);Guangzhou Philosophy and Social Science Planning Project(2022GZYB08);Doctoral Fund of North China Institute of Aerospace Engineering(BKY-2018-30) |
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Corresponding Authors:
Wang Cunhua，ORCID：0009-0009-4153-220X，E-mail：forum300@163.com。
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| [1] |
de Long J B D, Shleifer A, Summers L H, et al. Noise Trader Risk in Financial Markets[J]. Journal of Political Economy, 1990, 98(4): 703-738.
doi: 10.1086/261703
|
| [2] |
Baker M, Wurgler J. Investor Sentiment and the Cross-Section of Stock Returns[J]. The Journal of Finance, 2006, 61(4): 1645-1680.
doi: 10.1111/jofi.2006.61.issue-4
|
| [3] |
伍燕然, 韩立岩. 不完全理性、投资者情绪与封闭式基金之谜[J]. 经济研究, 2007, 42(3): 117-129.
|
| [3] |
(Wu Yanran, Han Liyan. Imperfect Rationality, Sentiment and Closed End Fund Puzzle[J]. Economic Research Journal, 2007, 42(3): 117-129.)
|
| [4] |
易志高, 茅宁. 中国股市投资者情绪测量研究: CICSI的构建[J]. 金融研究, 2009(11): 174-184.
|
| [4] |
(Yi Zhigao, Mao Ning. Research on the Measurement of Investor Sentiment in Chinese Stock Market: The CICSI’s Construction[J]. Journal of Financial Research, 2009(11): 174-184.)
|
| [5] |
Brown G W, Cliff M T. Investor Sentiment and the Near-Term Stock Market[J]. Journal of Empirical Finance, 2004, 11(1): 1-27.
doi: 10.1016/j.jempfin.2002.12.001
|
| [6] |
王美今, 孙建军. 中国股市收益、收益波动与投资者情绪[J]. 经济研究, 2004, 39(10): 75-83.
|
| [6] |
(Wang Meijin, Sun Jianjun. Stock Market Returns, Volatility and the Role of Investor Sentiment in China[J]. Economic Research Journal, 2004, 39(10): 75-83.)
|
| [7] |
Lemmon M, Portniaguina E. Consumer Confidence and Asset Prices: Some Empirical Evidence[J]. The Review of Financial Studies, 2006, 19(4): 1499-1529.
doi: 10.1093/rfs/hhj038
|
| [8] |
Loughran T, McDonald B. When is a Liability not a Liability? Textual Analysis, Dictionaries, and 10-Ks[J]. The Journal of Finance, 2011, 66(1): 35-65.
doi: 10.1111/jofi.2011.66.issue-1
|
| [9] |
Nassirtoussi A K, Aghabozorgi S, Wah T Y, et al. Text Mining for Market Prediction: A Systematic Review[J]. Expert Systems with Applications, 2014, 41(16): 7653-7670.
doi: 10.1016/j.eswa.2014.06.009
|
| [10] |
Nassirtoussi A K, Aghabozorgi S, Wah T Y, et al. Text Mining of News-Headlines for FOREX Market Prediction: A Multi-Layer Dimension Reduction Algorithm with Semantics and Sentiment[J]. Expert Systems with Applications, 2015, 42(1): 306-324.
doi: 10.1016/j.eswa.2014.08.004
|
| [11] |
Xu Q F, Wang L K, Jiang C X, et al. A Novel UMIDAS-SVQR Model with Mixed Frequency Investor Sentiment for Predicting Stock Market Volatility[J]. Expert Systems with Applications, 2019, 132(C): 12-27.
|
| [12] |
张同明, 张宁. 股票市场投资者情绪指数研究综述[J]. 计算机科学, 2021, 48(S1): 143-150.
|
| [12] |
(Zhang Tongming, Zhang Ning. Review of Research on Investor Sentiment Index in Stock Market[J]. Computer Science, 2021, 48(S1): 143-150.)
|
| [13] |
何诚颖, 陈锐, 薛冰, 等. 投资者情绪、有限套利与股价异象[J]. 经济研究, 2021, 56(1): 58-73.
|
| [13] |
(He Chengying, Chen Rui, Xue Bing, et al. Investor Sentiment, Limited Arbitrage and Stock Price Anomalies[J]. Economic Research Journal, 2021, 56(1): 58-73.)
|
| [14] |
Fu J H, Wu X, Liu Y F, et al. Firm-Specific Investor Sentiment and Stock Price Crash Risk[J]. Finance Research Letters, 2021, 38: 101442.
doi: 10.1016/j.frl.2020.101442
|
| [15] |
姚尧之, 王坚强, 刘志峰. 混频投资者情绪与股票价格行为[J]. 管理科学学报, 2018, 21(2): 104-113.
|
| [15] |
(Yao Yaozhi, Wang Jianqiang, Liu Zhifeng. Mixed-Frequency Investor Sentiment and Stock Price Behavior[J]. Journal of Management Sciences in China, 2018, 21(2): 104-113.)
|
| [16] |
岑咏华, 谭志浩, 吴承尧. 财经媒介信息对股票市场的影响研究:基于情感分析的实证[J]. 数据分析与知识发现, 2019, 3(9): 98-114.
|
| [16] |
(Cen Yonghua, Tan Zhihao, Wu Chengyao. Impacts of Financial Media Information on Stock Market: An Empirical Study of Sentiment Analysis[J]. Data Analysis and Knowledge Discovery, 2019, 3(9): 98-114.)
|
| [17] |
部慧, 解峥, 李佳鸿, 等. 基于股评的投资者情绪对股票市场的影响[J]. 管理科学学报, 2018, 21(4): 86-101.
|
| [17] |
(Bu Hui, Xie Zheng, Li Jiahong, et al. Investor Sentiment Extracted from Internet Stock Message Boards and Its Effect on Chinese Stock Market[J]. Journal of Management Sciences in China, 2018, 21(4): 86-101.)
|
| [18] |
Antweiler W, Frank M Z. Is all that Talk Just Noise? The Information Content of Internet Stock Message Boards[J]. The Journal of Finance, 2004, 59(3): 1259-1294.
doi: 10.1111/jofi.2004.59.issue-3
|
| [19] |
Jiang F W, Lee J, Martin X, et al. Manager Sentiment and Stock Returns[J]. Journal of Financial Economics, 2019, 132(1): 126-149.
doi: 10.1016/j.jfineco.2018.10.001
|
| [20] |
唐国豪, 姜富伟, 张定胜. 金融市场文本情绪研究进展[J]. 经济学动态, 2016(11): 137-147.
|
| [20] |
(Tang Guohao, Jiang Fuwei, Zhang Dingsheng. Research Progress of Text Emotion in Financial Market[J]. Economic Perspectives, 2016(11): 137-147.)
|
| [21] |
欧阳资生, 李虹宣. 网络舆情对金融市场的影响研究: 一个文献综述[J]. 统计与信息论坛, 2019, 34(11): 122-128.
|
| [21] |
(Ouyang Zisheng, Li Hongxuan. A Review of Research on the Impact of Internet Public Opinion on Financial Markets[J]. Statistics & Information Forum, 2019, 34(11): 122-128.)
|
| [22] |
沈艳, 陈赟, 黄卓. 文本大数据分析在经济学和金融学中的应用:一个文献综述[J]. 经济学(季刊), 2019, 18(4): 1153-1186.
|
| [22] |
(Shen Yan, Chen Yun, Huang Zhuo. A Literature Review of Textual Analysis in Economic and Financial Research[J]. China Economic Quarterly, 2019, 18(4): 1153-1186.)
|
| [23] |
Courtis J K. Annual Report Readability Variability: Tests of the Obfuscation Hypothesis[J]. Accounting, Auditing & Accountability Journal, 1998, 11(4): 459-472.
|
| [24] |
Lo K, Ramos F, Rogo R. Earnings Management and Annual Report Readability[J]. Journal of Accounting and Economics, 2017, 63(1): 1-25.
doi: 10.1016/j.jacceco.2016.09.002
|
| [25] |
Duan J W, Ding X, Zhang Y, et al. TEND: A Target-Dependent Representation Learning Framework for News Document[J]. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2019, 27(12): 2313-2325.
doi: 10.1109/TASLP.6570655
|
| [26] |
王丽佳, 卢国祥. 基于社会网络的股票动态价格研究[J]. 投资研究, 2017, 36(5): 81-91.
|
| [26] |
(Wang Lijia, Lu Guoxiang. Research on Stock Price Dynamics Based on Social Networks[J]. Review of Investment Studies, 2017, 36(5): 81-91.)
|
| [27] |
Ye M J, Li G Z. Internet Big Data and Capital Markets: A Literature Review[J]. Financial Innovation, 2017, 3(1): 6.
doi: 10.1186/s40854-017-0056-y
|
| [28] |
Lin C H, He Y L, Everson R, et al. Weakly Supervised Joint Sentiment-Topic Detection from Text[J]. IEEE Transactions on Knowledge and Data Engineering, 2012, 24(6): 1134-1145.
doi: 10.1109/TKDE.2011.48
|
| [29] |
Zhang X, Shi J W, Wang D, et al. Exploiting Investors Social Network for Stock Prediction in China’s Market[J]. Journal of Computational Science, 2018, 28: 294-303.
doi: 10.1016/j.jocs.2017.10.013
|
| [30] |
石善冲, 朱颖楠, 赵志刚, 等. 基于微信文本挖掘的投资者情绪与股票市场表现[J]. 系统工程理论与实践, 2018, 38(6): 1404-1412.
doi: 10.12011/1000-6788(2018)06-1404-09
|
| [30] |
(Shi Shanchong, Zhu Yingnan, Zhao Zhigang, et al. The Investor Sentiment Mined from WeChat Text and Stock Market Performance[J]. Systems Engineering-Theory & Practice, 2018, 38(6): 1404-1412.)
doi: 10.12011/1000-6788(2018)06-1404-09
|
| [31] |
段江娇, 刘红忠, 曾剑平. 中国股票网络论坛的信息含量分析[J]. 金融研究, 2017(10): 178-192.
|
| [31] |
(Duan Jiangjiao, Liu Hongzhong, Zeng Jianping. Analysis on the Information Content of China’s Internet Stock Message Boards[J]. Journal of Financial Research, 2017(10): 178-192.)
|
| [32] |
戴德宝, 兰玉森, 范体军, 等. 基于文本挖掘和机器学习的股指预测与决策研究[J]. 中国软科学, 2019(4): 166-175.
|
| [32] |
(Dai Debao, Lan Yusen, Fan Tijun, et al. Stock Forecast with Investors Sentiment by Text Mining and Machine Learning[J]. China Soft Science, 2019(4): 166-175.)
|
| [33] |
Mittal A, Goel A. Stock Prediction Using Twitter Sentiment Analysis[OL]. [2022-01-13]. http://cs229.stanford.edu/proj2011/GoelMittal-StockMarketPredictionUsingTwitterSentimentAnalysis.pdf.
|
| [34] |
王夫乐, 王相悦. 社会情绪是否会影响股市收益——来自新浪微博的证据[J]. 山西财经大学学报, 2017, 39(2): 35-46.
|
| [34] |
(Wang Fule, Wang Xiangyue. Does Social Emotion Affect Stock Return—The Evidence from Sina Weibo[J]. Journal of Shanxi University of Finance and Economics, 2017, 39(2): 35-46.)
|
| [35] |
汪昌云, 武佳薇. 媒体语气、投资者情绪与IPO定价[J]. 金融研究, 2015(9): 174-189.
|
| [35] |
(Wang Changyun, Wu Jiawei. Media Tone, Investor Sentiment and IPO Pricing[J]. Journal of Financial Research, 2015(9): 174-189.)
|
| [36] |
于琴, 张兵, 虞文微. 新闻情绪是股票收益的幕后推手吗[J]. 金融经济学研究, 2017, 32(6): 95-103.
|
| [36] |
(Yu Qin, Zhang Bing, Yu Wenwei. Are the Emotions of News a Wire-Puller of Stock Returns?[J]. Financial Economics Research, 2017, 32(6): 95-103.)
|
| [37] |
Li J, Chen Y, Shen Y, et al. Measuring China’s Stock Market Sentiment[J]. Social Science Research Network, DOI:10.2139/ssrn.3377684.
|
| [38] |
Mishev K, Gjorgjevikj A, Vodenska I, et al. Evaluation of Sentiment Analysis in Finance: From Lexicons to Transformers[J]. IEEE Access, 2020, 8: 131662-131682.
doi: 10.1109/Access.6287639
|
| [39] |
Zhao L Y, Li L, Zheng X H, et al. A BERT Based Sentiment Analysis and Key Entity Detection Approach for Online Financial Texts[C]// Proceedings of the 24th International Conference on Computer Supported Cooperative Work in Design. 2021: 1233-1238.
|
| [40] |
Johnman M, Vanstone B J, Gepp A. Predicting FTSE 100 Returns and Volatility Using Sentiment Analysis[J]. Accounting & Finance, 2018, 58(S1): 253-274.
doi: 10.1111/acfi.2018.58.issue-S1
|
| [41] |
Singh N K, Tomar D S, Sangaiah A K. Sentiment Analysis: A Review and Comparative Analysis over Social Media[J]. Journal of Ambient Intelligence and Humanized Computing, 2020, 11(1): 97-117.
doi: 10.1007/s12652-018-0862-8
|
| [42] |
Zucco C, Calabrese B, Agapito G, et al. Sentiment Analysis for Mining Texts and Social Networks Data: Methods and Tools[J]. WIREs: Data Mining and Knowledge Discovery, 2020, 10(1): e1333.
doi: 10.1002/widm.v10.1
|
| [43] |
Yadav A, Vishwakarma D K. Sentiment Analysis Using Deep Learning Architectures: A Review[J]. Artificial Intelligence Review, 2020, 53(6): 4335-4385.
doi: 10.1007/s10462-019-09794-5
|
| [44] |
Jegadeesh N, Wu D. Word Power: A New Approach for Content Analysis[J]. Journal of Financial Economics, 2013, 110(3): 712-729.
doi: 10.1016/j.jfineco.2013.08.018
|
| [45] |
Li X D, Xie H R, Chen L, et al. News Impact on Stock Price Return via Sentiment Analysis[J]. Knowledge-Based Systems, 2014, 69(1): 14-23.
doi: 10.1016/j.knosys.2014.04.022
|
| [46] |
Pröllochs N, Feuerriegel S, Neumann D. Negation Scope Detection in Sentiment Analysis: Decision Support for News-Driven Trading[J]. Decision Support Systems, 2016, 88: 67-75.
doi: 10.1016/j.dss.2016.05.009
|
| [47] |
Rekabsaz N, Lupu M H, Baklanov A, et al. Volatility Prediction Using Financial Disclosures Sentiments with Word Embedding-Based IR Models[C]// Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1:Long Papers). 2017: 1712-1721.
|
| [48] |
Fraiberger S P, Lee D, Puy D, et al. Media Sentiment and International Asset Prices[J]. Journal of International Economics, 2021, 133: 103526.
doi: 10.1016/j.jinteco.2021.103526
|
| [49] |
Khan F H, Qamar U, Bashir S. A Semi-Supervised Approach to Sentiment Analysis Using Revised Sentiment Strength Based on SentiWordNet[J]. Knowledge and Information Systems, 2017, 51(3): 851-872.
doi: 10.1007/s10115-016-0993-1
|
| [50] |
Pandarachalil R, Sendhilkumar S, Mahalakshmi G S. Twitter Sentiment Analysis for Large-Scale Data: An Unsupervised Approach[J]. Cognitive Computation, 2015, 7(2): 254-262.
doi: 10.1007/s12559-014-9310-z
|
| [51] |
Ren R, Wu D D, Liu T. X Forecasting Stock Market Movement Direction Using Sentiment Analysis and Support Vector Machine[J]. IEEE Systems Journal, 2019, 13(1): 760-770.
doi: 10.1109/JSYST.2018.2794462
|
| [52] |
Liu S M, Chen J H. A Multi-Label Classification Based Approach for Sentiment Classification[J]. Expert Systems with Applications, 2015, 42(3): 1083-1093.
doi: 10.1016/j.eswa.2014.08.036
|
| [53] |
乐国安, 董颖红, 陈浩, 等. 在线文本情感分析技术及应用[J]. 心理科学进展, 2013, 21(10): 1711-1719.
doi: 10.3724/SP.J.1042.2013.01711
|
| [53] |
(Yue Guoan, Dong Yinghong, Chen Hao, et al. Online Textual Sentiment Analysis Technology and It’s Applications[J]. Advances in Psychological Science, 2013, 21(10): 1711-1719.)
doi: 10.3724/SP.J.1042.2013.01711
|
| [54] |
朱梦珺, 蒋洪迅, 许伟. 基于金融微博情感与传播效果的股票价格预测[J]. 山东大学学报(理学版), 2016, 51(11): 13-25.
|
| [54] |
(Zhu Mengjun, Jiang Hongxun, Xu Wei. Weibo Moods and Propagation Factors Based Stock Prices Prediction[J]. Journal of Shandong University(Natural Science), 2016, 51(11): 13-25.)
|
| [55] |
Price S M, Doran J S, Peterson D R, et al. Earnings Conference Calls and Stock Returns: The Incremental Informativeness of Textual Tone[J]. Journal of Banking & Finance, 2012, 36(4): 992-1011.
doi: 10.1016/j.jbankfin.2011.10.013
|
| [56] |
Caporin M, Poli F. Building News Measures from Textual Data and an Application to Volatility Forecasting[J]. Econometrics, 2017, 5(3): 35.
doi: 10.3390/econometrics5030035
|
| [57] |
姚加权, 冯绪, 王赞钧, 等. 语调、情绪及市场影响:基于金融情绪词典[J]. 管理科学学报, 2021, 24(5): 26-46.
|
| [57] |
(Yao Jiaquan, Feng Xu, Wang Zanjun, et al. Tone, Sentiment and Market Impacts: The Construction of Chinese Sentiment Dictionary in Finance[J]. Journal of Management Sciences in China, 2021, 24(5): 26-46.)
|
| [58] |
Renault T. Intraday Online Investor Sentiment and Return Patterns in the U.S. Stock Market[J]. Journal of Banking & Finance, 2017, 84: 25-40.
doi: 10.1016/j.jbankfin.2017.07.002
|
| [59] |
Liang H, Sun X, Sun Y, et al. Text Feature Extraction Based on Deep Learning: A Review[J]. Eurasip Journal on Wireless Communications and Networking, 2017(1): 211.
doi: 10.1186/s13638-017-0993-1
pmid: 29263717
|
| [60] |
Habimana O, Li Y H, Li R X, et al. Sentiment Analysis Using Deep Learning Approaches: An Overview[J]. Science China Information Sciences, 2019, 63(1): 111102.
doi: 10.1007/s11432-018-9941-6
|
| [61] |
Iwasaki H, Chen Y. Topic Sentiment Asset Pricing with DNN Supervised Learning[J]. SSRN Electronic Journal. DOI:10.2139/ssrn.3228485.
|
| [62] |
Devlin J, Chang M W, Lee K, et al. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding[C]// Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics:Human Language Technologies, Volume 1, 2019: 4171-4186.
|
| [63] |
Teti E, Dallocchio M, Aniasi A. The Relationship Between Twitter and Stock Prices. Evidence from the US Technology Industry[J]. Technological Forecasting & Social Change, 2019, 149(C): 119747.
|
| [64] |
Affuso E, Lahtinen K D. Social Media Sentiment and Market Behavior[J]. Empirical Economics, 2019, 57(1): 105-127.
doi: 10.1007/s00181-018-1430-y
|
| [65] |
Xing F Z, Cambria E, Welsch R E. Intelligent Asset Allocation via Market Sentiment Views[J]. IEEE Computational Intelligence Magazine, 2018, 13(4): 25-34.
|
| [66] |
Checkley M S, Higón D A, Alles H. The Hasty Wisdom of the Mob: How Market Sentiment Predicts Stock Market Behavior[J]. Expert Systems with Applications, 2017, 77: 256-263.
doi: 10.1016/j.eswa.2017.01.029
|
| [67] |
Weng B, Lu L, Wang X, et al. Predicting Short-Term Stock Prices Using Ensemble Methods and Online Data Sources[J]. Expert Systems with Applications, 2018, 112: 258-273.
doi: 10.1016/j.eswa.2018.06.016
|
| [68] |
石善冲, 康凯立, 赵志刚. 机构与个体投资者情绪对IPO抑价影响研究——基于微信文本挖掘[J]. 经济与管理, 2019, 33(1): 51-58.
|
| [68] |
(Shi Shanchong, Kang Kaili, Zhao Zhigang. Research on the Influence of Institutional and Individual Investor Sentiment on IPO Underpricing[J]. Economy and Management, 2019, 33(1): 51-58.)
|
| [69] |
黄润鹏, 左文明, 毕凌燕. 基于微博情绪信息的股票市场预测[J]. 管理工程学报, 2015, 29(1): 47-52,215.
|
| [69] |
(Huang Runpeng, Zuo Wenming, Bi Lingyan. Predicting the Stock Market Based on Microblog Mood[J]. Journal of Industrial Engineering and Engineering Management, 2015, 29(1): 47-52, 215.)
|
| [70] |
Liu Y F, Qin Z C, Li P Y, et al. Stock Volatility Prediction Using Recurrent Neural Networks with Sentiment Analysis[C]// Proceedings of International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems. 2017: 192-201.
|
| [71] |
段江娇, 刘红忠, 曾剑平. 投资者情绪指数、分析师推荐指数与股指收益率的影响研究——基于我国东方财富网股吧论坛、新浪网分析师个股评级数据[J]. 上海金融, 2014(11): 60-64.
|
| [71] |
(Duan Jiangjiao, Liu Hongzhong, Zeng Jianping. Research on the Influence of Investor Sentiment Index, Analyst Recommendation Index and Stock Index Return—Based on the Data of Analysts’ Individual Stock Rating of China Oriental Fortune Network and Sina.com[J]. Shanghai Finance, 2014(11): 60-64.)
|
| [72] |
姚潇, 吴冬晓, 庞守林. 基于文本挖掘的管理层语调对公司债券信用利差的影响[J]. 经济理论与经济管理, 2020(3): 99-112.
|
| [72] |
(Yao Xiao, Wu Dongxiao, Pang Shoulin. The Influence of Management Tone on Corporate Bond Credit Spread Based on Text Mining[J]. Economic Theory and Business Management, 2020(3): 99-112.)
|
| [73] |
Piñeiro-Chousa J, López-Cabarcos M Á, Caby J, et al. The Influence of Investor Sentiment on the Green Bond Market[J]. Technological Forecasting and Social Change, 2021, 162: 120351.
doi: 10.1016/j.techfore.2020.120351
|
| [74] |
Erlwein-Sayer C. Macroeconomic News Sentiment: Enhanced Risk Assessment for Sovereign Bonds[J]. Risks, 2018, 6(4): 141.
doi: 10.3390/risks6040141
|
| [75] |
Gotthelf N, Uhl M W. News Sentiment: A New Yield Curve Factor[J]. Journal of Behavioral Finance, 2019, 20(1): 31-41.
doi: 10.1080/15427560.2018.1432620
|
| [76] |
Consoli S, Pezzoli L T, Tosetti E. Emotions in Macroeconomic News and Their Impact on the European Bond Market[J]. Journal of International Money and Finance, 2021, 118: 102472.
doi: 10.1016/j.jimonfin.2021.102472
|
| [77] |
庞有明, 蒋洪迅. 基于新闻舆情的信用债估值修正模型及其应用[J]. 山西大学学报(自然科学版), 2017, 40(1): 1-13.
|
| [77] |
(Pang Youming, Jiang Hongxun. Media-Adjusted Credit Bond Valuation and Its Applications[J]. Journal of Shanxi University(Natural Science Edition), 2017, 40(1): 1-13.)
|
| [78] |
林杰, 江晨曦. 基于BERT模型的投资者情绪指数建模及与价格关系分析[J]. 上海管理科学, 2020, 42(4): 75-80.
|
| [78] |
(Lin Jie, Jiang Chenxi. Modeling of Investors’ Sentiment Index Based on BERT Model and Analysis of Its Relationship with Price[J]. Shanghai Management Science, 2020, 42(4): 75-80.)
|
| [79] |
刘桂芳, 徐维军, 黄静龙, 等. 考虑公司信息披露情绪的欧式脆弱期权定价[J]. 运筹与管理, 2021, 30(9): 164-171.
doi: 10.12005/orms.2021.0295
|
| [79] |
(Liu Guifang, Xu Weijun, Huang Jinglong, et al. European Vulnerable Option Pricing Considering Corporate Information Disclosure Emotion[J]. Operations Research and Management Science, 2021, 30(9): 164-171.)
doi: 10.12005/orms.2021.0295
|
| [80] |
Tsai M F, Wang C J. On the Risk Prediction and Analysis of Soft Information in Finance Reports[J]. European Journal of Operational Research, 2017, 257(1): 243-250.
doi: 10.1016/j.ejor.2016.06.069
|
| [81] |
徐高彦, 高歌. 分析师预测分歧是市场情绪洪流的“漫水桥”吗——基于股价崩盘风险的视角[J]. 现代经济探讨, 2022(2): 52-67.
|
| [81] |
(Xu Gaoyan, Gao Ge. Is the Dispersion of Analysts’ Forecast a “Water-Overflowing Bridge” in the Flood of Market Sentiment?: From the Perspective of Stock Price Crash Risk[J]. Modern Economic Research, 2022(2): 52-67.)
|
| [82] |
尹海员. 新闻媒体报道对投资者情绪影响效应研究——来自我国股票市场的经验证据[J]. 厦门大学学报(哲学社会科学版), 2016(2): 92-101.
|
| [82] |
(Yin Haiyuan. A Study on Effect of Media Reports on Investor Sentiment: Evidence from China’s Stock Market[J]. Journal of Xiamen University (Arts & Social Sciences), 2016(2): 92-101.)
|
| [83] |
吕华揆, 刘政昊, 钱宇星, 等. 异质性财经新闻与股市关系研究[J]. 数据分析与知识发现, 2021, 5(1): 99-111.
|
| [83] |
(Lv Huakui, Liu Zhenghao, Qian Yuxing, et al. Relationship Between Financial News and Stock Market Fluctuations[J]. Data Analysis and Knowledge Discovery, 2021, 5(1): 99-111.)
|
| [84] |
张天骄, 孙谦. 网络媒体过度乐观情绪与上市公司股价崩盘风险[J]. 管理现代化, 2022, 42(1): 34-39.
|
| [84] |
(Zhang Tianjiao, Sun Qian. Sun Qian. Over-Optimistic Sentiment of Internet Media and Stock Price Crash Risk[J]. Modernization of Management, 2022, 42(1): 34-39.)
|
| [85] |
王昶, 王敏, 龚铖. 媒体报道降低了股价崩盘风险吗?——来自创业板的证据[J]. 金融与经济, 2017(4): 74-80.
|
| [85] |
(Wang Chang, Wang Min, Gong Cheng. Does Media Coverage Reduce the Risk of Stock Price Collapse? -Evidence from the Growth Enterprise Market[J]. Journal of Finance and Economics, 2017(4): 74-80.)
|
| [86] |
Liu Q K, Cheng X, Su S, et al. Hierarchical Complementary Attention Network for Predicting Stock Price Movements with News[C]// Proceedings of the 27th ACM International Conference on Information and Knowledge Management. 2018: 1603-1606.
|
| [87] |
Shi L, Teng Z Y, Wang L, et al. DeepClue: Visual Interpretation of Text-Based Deep Stock Prediction[J]. IEEE Transactions on Knowledge and Data Engineering, 2019, 31(6): 1094-1108.
doi: 10.1109/TKDE.69
|
| [88] |
张宁, 尹乐民, 何立峰. 网络股评“发布者-关注者”BSI与股票市场关联性研究[J]. 数据分析与知识发现, 2018, 2(6): 1-12.
|
| [88] |
(Zhang Ning, Yin Lemin, He Lifeng. Impacts of “Poster-Follower” Sentiment on Stock Market Performance[J]. Data Analysis and Knowledge Discovery, 2018, 2(6): 1-12.)
|
| [89] |
黄创霞, 温石刚, 杨鑫, 等. 个体投资者情绪与股票价格行为的互动关系研究[J]. 中国管理科学, 2020, 28(3): 191-200.
|
| [89] |
(Huang Chuangxia, Wen Shigang, Yang Xin, et al. The Interactive Relationship Between Individual Investor Sentiment and Stock Price Behaviors[J]. Chinese Journal of Management Science, 2020, 28(3): 191-200.)
|
| [90] |
Siganos A, Vagenas-Nanos E, Verwijmeren P. Divergence of Sentiment and Stock Market Trading[J]. Journal of Banking & Finance, 2017, 78: 130-141.
doi: 10.1016/j.jbankfin.2017.02.005
|
| [91] |
杨七中, 章贵桥, 马蓓丽. 管理层语意与未来股价崩盘风险——基于投资者情绪的中介效分析[J]. 中南财经政法大学学报, 2020(1): 26-36, 159.
|
| [91] |
(Yang Qizhong, Zhang Guiqiao, Ma Beili. Management Meanings and Stock Price Crash Risk: The Mediating Role of Investors Sentiments[J]. Journal of Zhongnan University of Economics and Law, 2020(1): 26-36, 159.)
|
| [92] |
Barber B M, Odean T. All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors[J]. The Review of Financial Studies, 2008, 21(2): 785-818.
doi: 10.1093/rfs/hhm079
|
| [93] |
Seng J L, Yang H F. The Association Between Stock Price Volatility and Financial News-A Sentiment Analysis Approach[J]. Kybernetes, 2017, 46(8): 1341-1365.
doi: 10.1108/K-11-2016-0307
|
| [94] |
You J X, Zhang B H, Zhang L. Who Captures the Power of the Pen?[J]. The Review of Financial Studies, 2018, 31(1): 43-96.
doi: 10.1093/rfs/hhx055
|
| [95] |
南晓莉. 新媒体时代网络投资者意见分歧对IPO溢价影响——基于股票论坛数据挖掘方法[J]. 中国软科学, 2015(10): 155-165.
|
| [95] |
(Nan Xiaoli. Effect of Internet Investors’ Opinion Divergence on IPO Premiums in the New Media Age: Analysis Based on Data Mining of Stock BBS[J]. China Soft Science, 2015(10): 155-165.)
|
| [96] |
Bhattacharya U, Galpin N, Ray R, et al. The Role of the Media in the Internet IPO Bubble[J]. Journal of Financial and Quantitative Analysis, 2009, 44(3): 657-682.
doi: 10.1017/S0022109009990056
|
| [97] |
Li S Y, Kong J H. News Sentiment and the Risk of a Stock Price Crash Risk: Based on Financial Dictionary Combined BERT-DCA[J]. Discrete Dynamics in Nature and Society, 2022, 2022: 8305947.
|
| [98] |
Campbell G, Turner J D, Walker C B. The Role of the Media in a Bubble[J]. Explorations in Economic History, 2012, 49(4): 461-481.
doi: 10.1016/j.eeh.2012.07.002
|
| [99] |
易洪波, 赖娟娟, 董大勇. 网络论坛不同投资者情绪对交易市场的影响——基于VAR模型的实证分析[J]. 财经论丛, 2015(1): 46-54.
|
| [99] |
(Yi Hongbo, Lai Juanjuan, Dong Dayong. A Study of the Influence of BBS Investor Sentiments on the Trading Market——An Empirical Analysis Based on VAR Model[J]. Collected Essays on Finance and Economics, 2015(1): 46-54.)
|
| [100] |
Banerjee S, Kremer I. Disagreement and Learning: Dynamic Patterns of Trade[J]. The Journal of Finance, 2010, 65(4): 1269-1302.
doi: 10.1111/jofi.2010.65.issue-4
|
| [101] |
孙鲲鹏, 肖星. 互联网社交媒体对投资者情绪传染与股价崩盘风险的影响机制[J]. 技术经济, 2018, 37(6): 93-102.
|
| [101] |
(Sun Kunpeng, Xiao Xing. Influence of Social Media in Internet on Sentiment Contagion and Stock Price Crash[J]. Technology Economics, 2018, 37(6): 93-102.)
|
| [102] |
唐斯圆, 李丹. 普通投资者关注度与股价崩盘风险——基于自媒体的研究[J]. 投资研究, 2018, 37(4): 38-56.
|
| [102] |
(Tang Siyuan, Li Dan. Ordinary Investors’ Attention and Stock Price Crash Risk—Empirical Analysis Based on “We Media”[J]. Review of Investment Studies, 2018, 37(4): 38-56.)
|
| [103] |
邓学斌, 胡凡. 融资融券制度、投资者情绪与股票市场系统性风险[J]. 暨南学报(哲学社会科学版), 2021, 43(9): 54-67.
|
| [103] |
(Deng Xuebin, Hu Fan. Margin and Short-Selling System, Investor Sentiment and Systemic Risks of Stock Market[J]. Jinan Journal(Philosophy & Social Sciences), 2021, 43(9): 54-67.)
|
| [104] |
欧阳资生, 李虹宣, 杨希特. 网络舆情对中国上市金融机构系统性风险影响研究[J]. 系统科学与数学, 2021, 41(5): 1339-1354.
doi: 10.12341/jssms20216
|
| [104] |
(Ouyang Zisheng, Li Hongxuan, Yang Xite. Research on the Influence of Network Public Opinion on the Systematic Risk of Listed Financial Institutions in China[J]. Journal of Systems Science and Mathematical Sciences, 2021, 41(5): 1339-1354.)
doi: 10.12341/jssms20216
|
| [105] |
王白雪, 郭琨, 孙毅, 等. 基于投资者情绪的股市系统性风险监测新方法[J]. 山西财经大学学报, 2018, 40(S2): 30-34.
|
| [105] |
(Wang Baixue, Guo Kun, Sun Yi, et al. A New Method of Systematic Risk Monitoring in Stock Market Based on Investor Sentiment[J]. Journal of Shanxi University of Finance and Economics, 2018, 40(S2): 30-34.)
|
| [106] |
丁肖丽. 网络讨论、情绪分化与股票市场表现[J]. 湘潭大学学报(哲学社会科学版), 2019, 43(2): 75-81.
|
| [106] |
(Ding Xiaoli. Internet Discussions, Sentiment Divergence and Stock Market Performance[J]. Journal of Xiangtan University(Philosophy and Social Sciences), 2019, 43(2): 75-81.)
|
| [107] |
Wang Q L, Xu W, Zheng H. Combining the Wisdom of Crowds and Technical Analysis for Financial Market Prediction Using Deep Random Subspace Ensembles[J]. Neurocomputing, 2018, 299: 51-61.
doi: 10.1016/j.neucom.2018.02.095
|
| [108] |
Gupta R, Chen M. Sentiment Analysis for Stock Price Prediction[C]// Proceedings of the 2020 IEEE Conference on Multimedia Information Processing and Retrieval. 2020: 213-218.
|
| [109] |
乔智, 耿志民. 股吧对个人投资者情绪的影响研究[J]. 金融理论与实践, 2013(11): 77-81.
|
| [109] |
(Qiao Zhi, Geng Zhimin. An Empirical Research on Individual Investor Emotional Effect from Stock BBS[J]. Financial Theory & Practice, 2013(11): 77-81.)
|
| [110] |
Guo T, Finke M, Mulholland B. Investor Attention and Advisor Social Media Interaction[J]. Applied Economics Letters, 2015, 22(4): 261-265.
doi: 10.1080/13504851.2014.937030
|
| [111] |
孙书娜, 孙谦. 投资者关注和股市表现——基于雪球关注度的研究[J]. 管理科学学报, 2018, 21(6): 60-71.
|
| [111] |
(Sun Shuna, Sun Qian. Investor Attention and Market Performance: Evidence Based on “Xueqiu Attention”[J]. Journal of Management Sciences in China, 2018, 21(6): 60-71.)
|
| [112] |
Fang J C, Gozgor G, Lau C K M, et al. The Impact of Baidu Index Sentiment on the Volatility of China’s Stock Markets[J]. Finance Research Letters, 2020, 32: 101099.
doi: 10.1016/j.frl.2019.01.011
|
| [113] |
Guo K, Sun Y, Qian X. Can Investor Sentiment be Used to Predict the Stock Price? Dynamic Analysis Based on China Stock Market[J]. Physica A: Statistical Mechanics and Its Applications, 2017, 469: 390-396.
doi: 10.1016/j.physa.2016.11.114
|
| [114] |
陈卫华, 徐国祥. 基于深度学习和股票论坛数据的股市波动率预测精度研究[J]. 管理世界, 2018, 34(1): 180-181.
|
| [114] |
(Chen Weihua, Xu Guoxiang. Research on Prediction Accuracy of Stock Market Volatility Based on Deep Learning and Stock Forum Data[J]. Management World, 2018, 34(1): 180-181.)
|
| [115] |
Gao Y, Wang Y J, Wang C, et al. Internet Attention and Information Asymmetry: Evidence from Qihoo 360 Search Data on the Chinese Stock Market[J]. Physica A: Statistical Mechanics and Its Applications, 2018, 510: 802-811.
doi: 10.1016/j.physa.2018.07.016
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