Is a sentiment-based trading strategy profitable?

被引:13
|
作者
Kim, Karam [1 ]
Ryu, Doojin [1 ]
Yu, Jinyoung [1 ]
机构
[1] Sungkyunkwan Univ, Coll Econ, 25-2 Sungkyunkwan Ro, Seoul 03063, South Korea
关键词
cross-sectional stock returns; investor sentiment; portfolio management; return predictability; trading strategy; INVESTOR SENTIMENT; STOCK RETURNS; OVERNIGHT RETURNS; MARKET EVIDENCE; INFORMATION; TRADES; PREDICTABILITY; PERFORMANCE; IMPACTS;
D O I
10.1080/10293523.2022.2076373
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
We examine whether sentiment indices predict individual firms' stock returns and evaluate the performances of sentiment-based trading strategies in the Korean equity market. We find that the sentiment indices (constructed using the principal component analysis (PCA) and overnight stock returns) positively predict stock price movements, whereas news sentiment does not significantly determine future stock returns. A comparison of portfolio performances among sentiment indices reveals that the long-short equity strategy based on PCA sentiment changes yields the highest return - a result that is not explained by well-known risk factors. Moreover, investors may earn even greater returns by employing multiple sentiment measures when constructing portfolios, suggesting that each measure reflects different aspects of investor sentiment.
引用
收藏
页码:94 / 107
页数:14
相关论文
共 50 条
  • [21] Generative adversarial network for sentiment-based stock prediction
    Asgarian, Sepehr
    Ghasemi, Rouzbeh
    Momtazi, Saeedeh
    [J]. CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2023, 35 (02):
  • [22] A Sentiment-Based Multimodal Method to Detect Fake News
    Libonati Maia, Igor Maffei
    de Souza, Marcelo Pereira
    Matias da Silva, Flavio Roberto
    Souza Freire, Paulo Marcio
    Goldschmidt, Ronaldo Ribeiro
    [J]. PROCEEDINGS OF THE 27TH BRAZILIAN SYMPOSIUM ON MULTIMEDIA AND THE WEB (WEBMEDIA '21), 2021, : 212 - 215
  • [23] A Comparative Study of Sentiment-Based Graphs of Text Summaries
    Chua, Stephanie
    Kulathuramaiyer, Narayanan
    Ranaivo-Malancon, Bali
    Iboi, Hazimah
    [J]. 2018 5TH IEEE INTERNATIONAL CONFERENCE ON ENGINEERING TECHNOLOGIES AND APPLIED SCIENCES (IEEE ICETAS), 2018,
  • [24] TRANSITIVITY IN WORK-RELEVANT AND SENTIMENT-BASED SOCIOGRAMS
    BISHOP, JM
    [J]. PACIFIC SOCIOLOGICAL REVIEW, 1979, 22 (02): : 185 - 200
  • [25] Genetic programming optimization for a sentiment feedback strength based trading strategy
    Yang, Steve Y.
    Mo, Sheung Yin Kevin
    Liu, Anqi
    Kirilenko, Andrei A.
    [J]. NEUROCOMPUTING, 2017, 264 : 29 - 41
  • [26] A Sentiment-Based Item Description Approach for kNN Collaborative Filtering
    D'Addio, Rafael M.
    Manzato, Marcelo G.
    [J]. 30TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING, VOLS I AND II, 2015, : 1060 - 1065
  • [27] What is Your Influence on Social Media? A Sentiment-Based Model
    Chang, Wei-Lun
    [J]. PROCEEDINGS OF THE 15TH EUROPEAN CONFERENCE ON RESEARCH METHODOLOGY FOR BUSINESS AND MANAGEMENT STUDIES (ECRM2016), 2016, : 405 - 407
  • [28] A profitable trading and risk management strategy despite transaction costs
    Duran, Ahmet
    Bommarito, Michael J.
    [J]. QUANTITATIVE FINANCE, 2011, 11 (06) : 829 - 848
  • [29] Exploiting New Sentiment-Based Meta-level Features for Effective Sentiment Analysis
    Canuto, Sergio
    Goncalves, Marcos Andre
    Benevenuto, Fabricio
    [J]. PROCEEDINGS OF THE NINTH ACM INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING (WSDM'16), 2016, : 53 - 62
  • [30] A SENTIMENT-BASED FILTERATION AND DATA ANALYSIS FRAMEWORK FOR SOCIAL MEDIA
    Abd Ghani, Norjihan
    Kamal, Siti Syahidah Mohamad
    [J]. PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON COMPUTING & INFORMATICS, 2015, : 632 - 637