IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2309.05560.html

New News is Bad News

Author

Listed:
  • Paul Glasserman
  • Harry Mamaysky
  • Jimmy Qin

Abstract

An increase in the novelty of news predicts negative stock market returns and negative macroeconomic outcomes over the next year. We quantify news novelty - changes in the distribution of news text - through an entropy measure, calculated using a recurrent neural network applied to a large news corpus. Entropy is a better out-of-sample predictor of market returns than a collection of standard measures. Cross-sectional entropy exposure carries a negative risk premium, suggesting that assets that positively covary with entropy hedge the aggregate risk associated with shifting news language. Entropy risk cannot be explained by existing long-short factors.

Suggested Citation

  • Paul Glasserman & Harry Mamaysky & Jimmy Qin, 2023. "New News is Bad News," Papers 2309.05560, arXiv.org.
    • Handle: RePEc:arx:papers:2309.05560
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2309.05560
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    2. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    3. Geert Bekaert & Eric C. Engstrom & Nancy R. Xu, 2022. "The Time Variation in Risk Appetite and Uncertainty," Management Science, INFORMS, vol. 68(6), pages 3975-4004, June.
    4. Azzimonti, Marina, 2018. "Partisan conflict and private investment," Journal of Monetary Economics, Elsevier, vol. 93(C), pages 114-131.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Iania, Leonardo & Nguyen, P. Thao & Smedts, Kristien, 2025. "Stock returns and macroeconomic uncertainty," International Review of Financial Analysis, Elsevier, vol. 104(PA).
    2. Wo Long & Wenxin Zeng & Xiaoyu Zhang & Ziyao Zhou, 2025. "Integrating Large Language Models and Reinforcement Learning for Sentiment-Driven Quantitative Trading," Papers 2510.10526, arXiv.org.

    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. Peress, Joël & Dong, Xi & KANG, NAMHO, 2020. "Fast and Slow Arbitrage: Fund Flows and Mispricing in the Frequency Domain," CEPR Discussion Papers 15235, C.E.P.R. Discussion Papers.
    2. Chan, Kam Fong & Gray, Philip & Gray, Stephen & Zhong, Angel, 2020. "Political uncertainty, market anomalies and Presidential honeymoons," Journal of Banking & Finance, Elsevier, vol. 113(C).
    3. Hacıoğlu-Hoke, Sinem, 2024. "Macroeconomic effects of political risk shocks," Economics Letters, Elsevier, vol. 242(C).
    4. Yuan, Jun & Yang, Liuyong & Xu, Qi, 2025. "The real side of black swans: Tail risk and corporate investment," Journal of Banking & Finance, Elsevier, vol. 176(C).
    5. González-Sánchez, Mariano & Nave, Juan & Rubio, Gonzalo, 2020. "Effects of uncertainty and risk aversion on the exposure of investment-style factor returns to real activity," Research in International Business and Finance, Elsevier, vol. 53(C).
    6. Bianchi, Robert J. & Fan, John Hua & Miffre, Joëlle & Zhang, Tingxi, 2023. "Exploiting the dynamics of commodity futures curves," Journal of Banking & Finance, Elsevier, vol. 154(C).
    7. Chen, Xi & Wang, Junbo & Wu, Chunchi & Wu, Di, 2024. "Extreme illiquidity and cross-sectional corporate bond returns," Journal of Financial Markets, Elsevier, vol. 68(C).
    8. Pham, Anh Viet, 2019. "Political risk and cost of equity: The mediating role of political connections," Journal of Corporate Finance, Elsevier, vol. 56(C), pages 64-87.
    9. Deschamps, Bruno & Fei, Tianlun & Jiang, Ying & Liu, Xiaoquan, 2025. "Uncertainty and cross-sectional stock returns: Evidence from China," Journal of Banking & Finance, Elsevier, vol. 171(C).
    10. Goodness C. Aye & Rangan Gupta, 2019. "Macroeconomic Uncertainty And The Comovement In Buying Versus Renting In The Usa," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(3), pages 93-121, September.
    11. Juan M. Londono & Mehrdad Samadi, 2023. "The Price of Macroeconomic Uncertainty: Evidence from Daily Options," International Finance Discussion Papers 1376, Board of Governors of the Federal Reserve System (U.S.).
    12. Liu, Yunting & Zhu, Yandi, 2025. "Good idiosyncratic volatility, bad idiosyncratic volatility, and the cross-section of stock returns," Journal of Banking & Finance, Elsevier, vol. 170(C).
    13. Matousek, Roman & Panopoulou, Ekaterini & Papachristopoulou, Andromachi, 2020. "Policy uncertainty and the capital shortfall of global financial firms," Journal of Corporate Finance, Elsevier, vol. 62(C).
    14. Glebocki, Helena & Saha, Sujata, 2024. "Global uncertainty and exchange rate conditions: Assessing the impact of uncertainty shocks in emerging markets and advanced economies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 96(C).
    15. Faiza Siddiqui & Yusheng Kong & Hyder Ali & Salma Naz, 2024. "Energy-Related Uncertainty and Idiosyncratic Return Volatility: Implications for Sustainable Investment Strategies in Chinese Firms," Sustainability, MDPI, vol. 16(17), pages 1-39, August.
    16. Jeffrey Ng & Walid Saffar & Janus Jian Zhang, 2020. "Policy uncertainty and loan loss provisions in the banking industry," Review of Accounting Studies, Springer, vol. 25(2), pages 726-777, June.
    17. Gurdip Bakshi & Xiaohui Gao & George Panayotov, 2021. "A Theory of Dissimilarity Between Stochastic Discount Factors," Management Science, INFORMS, vol. 67(7), pages 4602-4622, July.
    18. Murad, S.M. Woahid & Pathan, Shams & Durand, Robert B. & Zheng, Chen, 2025. "Understanding Bank-Level Uncertainty: New insights into banking activity and its macroeconomic impacts," International Review of Economics & Finance, Elsevier, vol. 102(C).
    19. Guillaume Coqueret & Thomas Giroux & Olivier David Zerbib, 2024. "The biodiversity premium," Post-Print hal-05415060, HAL.
    20. Guo, Junjie & Li, Youshu & Shao, Qinglong, 2022. "Cross-category spillover effects of economic policy uncertainty between China and the US: Time and frequency evidence," Journal of Asian Economics, Elsevier, vol. 80(C).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:2309.05560. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.