IDEAS home Printed from https://ideas.repec.org/a/eee/reveco/v98y2025ics1059056025000036.html
   My bibliography  Save this article

Analyzing and forecasting P/E ratios using investor sentiment in panel data regression and LSTM models

Author

Listed:
  • Dolaeva, Aishat
  • Beliaeva, Uliana
  • Grigoriev, Dmitry
  • Semenov, Alexander
  • Rysz, Maciej

Abstract

This study investigates several factors influencing the well-known price/earnings ratio (P/E), with particular emphasis on investor sentiment scores obtained from textual data using natural language processing models. Data consisting of various economic indicators and user-generated text messages from the social network Twitter were collected for several established firms that were categorized into two sectors. Sentiment scores from the textual data were obtained using the BERT and FinBERT language models and shown to exhibit a high level of accuracy. Fixed and random effect regression models considering panel data comprising the economics indicators and sentiment scores were constructed and revealed statistically significant influences of sentiment on the P/E ratio in one sector. A Long Short-Term Memory recurrent neural network model was then used to forecast the P/E ratio over a one year interval, which produced highly accurate results. Our analysis demonstrates the significance of investor sentiment as a factor in P/E ratio forecasting, emphasizing its contribution alongside other fundamental factors.

Suggested Citation

  • Dolaeva, Aishat & Beliaeva, Uliana & Grigoriev, Dmitry & Semenov, Alexander & Rysz, Maciej, 2025. "Analyzing and forecasting P/E ratios using investor sentiment in panel data regression and LSTM models," International Review of Economics & Finance, Elsevier, vol. 98(C).
  • Handle: RePEc:eee:reveco:v:98:y:2025:i:c:s1059056025000036
    DOI: 10.1016/j.iref.2025.103840
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1059056025000036
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.iref.2025.103840?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Malcolm Baker & Jeffrey Wurgler, 2007. "Investor Sentiment in the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 129-152, Spring.
    2. Mohamed Zouaoui & Geneviève Nouyrigat & Francisca Beer, 2011. "How does investor sentiment affect stock market crises?Evidence from panel data," Working Papers CREGO 1110304, Université de Bourgogne - CREGO EA7317 Centre de recherches en gestion des organisations.
    3. Bell, Andrew & Jones, Kelvyn, 2015. "Explaining Fixed Effects: Random Effects Modeling of Time-Series Cross-Sectional and Panel Data," Political Science Research and Methods, Cambridge University Press, vol. 3(1), pages 133-153, January.
    4. Shen, Dehua & Urquhart, Andrew & Wang, Pengfei, 2019. "Does twitter predict Bitcoin?," Economics Letters, Elsevier, vol. 174(C), pages 118-122.
    5. Rahman, Md Lutfur & Shamsuddin, Abul, 2019. "Investor sentiment and the price-earnings ratio in the G7 stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 55(C), pages 46-62.
    6. Mohamed Zouaoui & Geneviève Nouyrigat & Francisca Beer, 2011. "How Does Investor Sentiment Affect Stock Market Crises? Evidence from Panel Data," The Financial Review, Eastern Finance Association, vol. 46(4), pages 723-747, November.
    7. Yanzhao Zou & Dorien Herremans, 2022. "PreBit -- A multimodal model with Twitter FinBERT embeddings for extreme price movement prediction of Bitcoin," Papers 2206.00648, arXiv.org, revised Oct 2023.
    8. Itemgenova, Aigerim & Sikveland, Marius, 2020. "The determinants of the price-earnings ratio in the Norwegian aquaculture industry," Journal of Commodity Markets, Elsevier, vol. 17(C).
    9. Boonlert Jitmaneeroj, 2017. "Does investor sentiment affect price-earnings ratios?," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 34(2), pages 183-193, June.
    10. repec:eme:sef000:sef-09-2015-0229 is not listed on IDEAS
    11. Gan, Baoqing & Alexeev, Vitali & Bird, Ron & Yeung, Danny, 2020. "Sensitivity to sentiment: News vs social media," International Review of Financial Analysis, Elsevier, vol. 67(C).
    12. Pekka Malo & Ankur Sinha & Pekka Korhonen & Jyrki Wallenius & Pyry Takala, 2014. "Good debt or bad debt: Detecting semantic orientations in economic texts," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(4), pages 782-796, April.
    13. Mohamed Zouaoui & G. Nouyrigat & F. Beer, 2011. "How Does Investor Sentiment Affect StockMarket Crises? Evidence from Panel Data," Post-Print halshs-00785809, HAL.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Reis, Pedro Manuel Nogueira & Pinho, Carlos, 2020. "A new European investor sentiment index (EURsent) and its return and volatility predictability," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    2. Pedro Manuel Nogueira Reis & Carlos Pinho, 2021. "A Reappraisal of the Causal Relationship between Sentiment Proxies and Stock Returns," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 22(4), pages 420-442, October.
    3. Betül Kalaycı & Ayşe Özmen & Gerhard-Wilhelm Weber, 2020. "Mutual relevance of investor sentiment and finance by modeling coupled stochastic systems with MARS," Annals of Operations Research, Springer, vol. 295(1), pages 183-206, December.
    4. Bildirici, Melike E. & Badur, Mesut M., 2019. "The effects of oil and gasoline prices on confidence and stock return of the energy companies for Turkey and the US," Energy, Elsevier, vol. 173(C), pages 1234-1241.
    5. Deven Bathia & Don Bredin & Dirk Nitzsche, 2016. "International Sentiment Spillovers in Equity Returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 21(4), pages 332-359, October.
    6. Betül Kalaycı & Vilda Purutçuoğlu & Gerhard Wilhelm Weber, 2025. "Optimal model description of finance and human factor indices," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 33(1), pages 1-26, March.
    7. Deven Bathia & Don Bredin, 2013. "An examination of investor sentiment effect on G7 stock market returns," The European Journal of Finance, Taylor & Francis Journals, vol. 19(9), pages 909-937, October.
    8. Wu, Qinqin & Hao, Ying & Lu, Jing, 2017. "Investor sentiment, idiosyncratic risk, and mispricing of American Depository Receipt," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 1-14.
    9. Phan, Thi Nha Truc & Bertrand, Philippe & Phan, Hong Hai & Vo, Xuan Vinh, 2023. "The role of investor behavior in emerging stock markets: Evidence from Vietnam," The Quarterly Review of Economics and Finance, Elsevier, vol. 87(C), pages 367-376.
    10. Loann David Denis Desboulets, 2017. "Co-movements in Market Prices and Fundamentals: A Semiparametric Multivariate GARCH Approach," Working Papers halshs-02059302, HAL.
    11. Xiao Han & Nikolaos Sakkas & Jo Danbolt & Arman Eshraghi, 2022. "Persistence of investor sentiment and market mispricing," The Financial Review, Eastern Finance Association, vol. 57(3), pages 617-640, August.
    12. Wang, Wenzhao & Su, Chen & Duxbury, Darren, 2021. "Investor sentiment and stock returns: Global evidence," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 365-391.
    13. Kamini Solanki & Yudhvir Seetharam, 2014. "Is consumer confidence an indicator of JSE performance?," Contemporary Economics, Vizja University, vol. 8(3), September.
    14. Cervantes, Paula & Díaz, Antonio & Esparcia, Carlos & Huélamo, Diego, 2022. "The impact of COVID-19 induced panic on stock market returns: A two-year experience," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 1075-1097.
    15. Loang Ooi Kok, 2025. "From Tweets to Trades: The Dynamic Dance of Investor Sentiment, Attention, and News Sentiment in ESG Stocks," China Finance and Economic Review, De Gruyter, vol. 14(1), pages 70-91.
    16. Mariano González-Sánchez & M. Encina Morales de Vega, 2021. "Influence of Bloomberg’s Investor Sentiment Index: Evidence from European Union Financial Sector," Mathematics, MDPI, vol. 9(4), pages 1-21, February.
    17. Nawaf Almaskati & Ron Bird & Yue Lu & Danny Leung, 2019. "Corporate Governance, Information Uncertainty and Market Reaction to Information Signals," Working Papers in Economics 19/15, University of Waikato.
    18. Wang, Wenzhao & Duxbury, Darren, 2021. "Institutional investor sentiment and the mean-variance relationship: Global evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 415-441.
    19. Tingqiang Chen & Binqing Xiao & Haifei Liu, 2018. "Credit Risk Contagion in an Evolving Network Model Integrating Spillover Effects and Behavioral Interventions," Complexity, Hindawi, vol. 2018, pages 1-16, March.
    20. Economou, Fotini & Panagopoulos, Yannis & Tsouma, Ekaterini, 2018. "Uncovering asymmetries in the relationship between fear and the stock market using a hidden co-integration approach," Research in International Business and Finance, Elsevier, vol. 44(C), pages 459-470.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reveco:v:98:y:2025:i:c:s1059056025000036. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620165 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.