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Asset returns, news topics, and media effects

Author

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  • Vegard H ghaug Larsen
  • Leif Anders Thorsrud
Abstract
We decompose the textual data in a daily Norwegian business newspaper into news topics and investigate their predictive and causal role for asset prices. Our three main findings are: (1) a one unit innovation in the news topics predict roughly a 1 percentage point increase in close-to-open returns and significant continuation patterns peaking at 4 percentage points after 15 business days, with little sign of reversal; (2) simple zero-cost news-based investment strategies yield significant annualized risk-adjusted returns of up to 20 percent; and (3) during a media shortage, due to an exogenous strike, returns for firms particularly exposed to our news measure experience a substantial fall. Our estimates suggest that between 20 to 40 percent of the news topics predictive power is due to the causal media effect. Together these findings lend strong support for a rational attention view where the media alleviate information frictions and disseminate fundamental information to a large population of investors.

Suggested Citation

  • Vegard H ghaug Larsen & Leif Anders Thorsrud, 2017. "Asset returns, news topics, and media effects," Working Papers No 5/2017, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Handle: RePEc:bny:wpaper:0054
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    Citations

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    Cited by:

    1. Lino Wehrheim, 2019. "Economic history goes digital: topic modeling the Journal of Economic History," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 13(1), pages 83-125, January.
    2. Vegard H ghaug Larsen & Leif Anders Thorsrud, 2018. "Business cycle narratives," Working Papers No 6/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    3. Larsen, Vegard H. & Thorsrud, Leif Anders & Zhulanova, Julia, 2021. "News-driven inflation expectations and information rigidities," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 507-520.
    4. Saskia Ter Ellen & Vegard H. Larsen & Leif Anders Thorsrud, 2022. "Narrative Monetary Policy Surprises and the Media," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(5), pages 1525-1549, August.
    5. Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News Media vs. FRED-MD for Macroeconomic Forecasting," CESifo Working Paper Series 8639, CESifo.
    6. Mosi Rosenboim & Yossi Saadon & Ben Z. Schreiber, 2018. "“Much Ado about Nothing”? The Effect of Print Media Tone on Stock Indices," Bank of Israel Working Papers 2018.10, Bank of Israel.
    7. Daniel Borup & Jorge Wolfgang Hansen & Benjamin Dybro Liengaard & Erik Christian Montes Schütte, 2023. "Quantifying investor narratives and their role during COVID‐19," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 512-532, June.
    8. Ristolainen, Kim & Roukka, Tomi & Nyberg, Henri, 2024. "A thousand words tell more than just numbers: Financial crises and historical headlines," Journal of Financial Stability, Elsevier, vol. 70(C).
    9. Dorine Boumans & Henrik Müller & Stefan Sauer, 2022. "How Media Content Influences Economic Expectations: Evidence from a Global Expert Survey," ifo Working Paper Series 380, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    10. David Ardia & Keven Bluteau & Kris Boudt & Koen Inghelbrecht, 2020. "Climate change concerns and the performance of green versus brown stocks," Working Paper Research 395, National Bank of Belgium.
    11. Axel Groß-Klußmann, 2024. "Learning deep news sentiment representations for macro-finance," Digital Finance, Springer, vol. 6(3), pages 341-377, September.
    12. Lino Wehrheim, 2017. "Economic History Goes Digital: Topic Modeling the Journal of Economic History," Working Papers 177, Bavarian Graduate Program in Economics (BGPE).
    13. Lin Chen & Stephanie Houle, 2023. "Turning Words into Numbers: Measuring News Media Coverage of Shortages," Discussion Papers 2023-8, Bank of Canada.
    14. Saadon, Yossi & Schreiber, Ben Z., 2023. "Newspapers tone and the overnight-intraday stock return anomaly," Journal of Financial Markets, Elsevier, vol. 65(C).
    15. Leif Anders Thorsrud, 2016. "Nowcasting using news topics Big Data versus big bank," Working Papers No 6/2016, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    16. Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2022. "News media versus FRED‐MD for macroeconomic forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 63-81, January.
    17. Ashwin, Julian, 2024. "Financial news media and volatility: Is there more to newspapers than news?," Journal of Financial Markets, Elsevier, vol. 69(C).

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    More about this item

    Keywords

    Stock returns; News; Machine learning; Latent Dirichlet Allocation (LDA);
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • G4 - Financial Economics - - Behavioral Finance
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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