IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v38y2021ics1544612319313674.html
   My bibliography  Save this article

Measuring Trump: The Volfefe Index and its impact on European financial markets

Author

Listed:
  • Klaus, Jürgen
  • Koser, Christoph

Abstract

In this study, we examine the predictive power of the recently constructed Volfefe Index, the quantification of the tweeting activity of U.S. president Donald J. Trump, on the dynamics of European stock markets. After controlling for a set of macroeconomic and financial factors, we show that the Trump Tweet factor contributes to the prediction of European stock market returns. The results obtained from a rolling-window regression model indicate that the relationship between the Volfefe Index and European stock market returns is heterogeneous and time-varying. These dynamics coincide surprisingly well with a series of presidential tweets, identifying the directional effect of the Trump Twitter factor.

Suggested Citation

  • Klaus, Jürgen & Koser, Christoph, 2021. "Measuring Trump: The Volfefe Index and its impact on European financial markets," Finance Research Letters, Elsevier, vol. 38(C).
    • Handle: RePEc:eee:finlet:v:38:y:2021:i:c:s1544612319313674
    DOI: 10.1016/j.frl.2020.101447
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612319313674
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2020.101447?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Lieven Baele & Geert Bekaert & Koen Inghelbrecht & Min Wei, 2020. "Flights to Safety," The Review of Financial Studies, Society for Financial Studies, vol. 33(2), pages 689-746.
    2. De Long, J Bradford, et al, 1990. "Positive Feedback Investment Strategies and Destabilizing Rational Speculation," Journal of Finance, American Finance Association, vol. 45(2), pages 379-395, June.
    3. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    4. Elie Bouri & Donald Lien & David Roubaud & Syed Jawad Hussain Shahzad, 2018. "Fear Linkages Between the US and BRICS Stock Markets: A Frequency-Domain Causality," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 25(3), pages 441-454, September.
    5. Schmeling, Maik, 2009. "Investor sentiment and stock returns: Some international evidence," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 394-408, June.
    6. Newey, Whitney K & West, Kenneth D, 1987. "Hypothesis Testing with Efficient Method of Moments Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 28(3), pages 777-787, October.
    7. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
    8. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    9. Gabriele Ranco & Darko Aleksovski & Guido Caldarelli & Miha Grčar & Igor Mozetič, 2015. "The Effects of Twitter Sentiment on Stock Price Returns," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-21, September.
    10. Sadorsky, Perry, 1999. "Oil price shocks and stock market activity," Energy Economics, Elsevier, vol. 21(5), pages 449-469, October.
    11. Barberis, Nicholas & Shleifer, Andrei & Vishny, Robert, 1998. "A model of investor sentiment," Journal of Financial Economics, Elsevier, vol. 49(3), pages 307-343, September.
    12. Vayanos, Dimitri, 2004. "Flight to quality, flight to liquidity, and the pricing of risk," LSE Research Online Documents on Economics 456, London School of Economics and Political Science, LSE Library.
    13. Richard A. Ajayi & Mbodja Mougouė, 1996. "On The Dynamic Relation Between Stock Prices And Exchange Rates," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 19(2), pages 193-207, June.
    14. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    15. Lily Fang & Joel Peress, 2009. "Media Coverage and the Cross‐section of Stock Returns," Journal of Finance, American Finance Association, vol. 64(5), pages 2023-2052, October.
    16. Bouri, Elie & Gupta, Rangan & Hosseini, Seyedmehdi & Lau, Chi Keung Marco, 2018. "Does global fear predict fear in BRICS stock markets? Evidence from a Bayesian Graphical Structural VAR model," Emerging Markets Review, Elsevier, vol. 34(C), pages 124-142.
    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. Bales, Stephan & Burghartz, Kaspar & Burghof, Hans-Peter & Hitz, Lukas, 2023. "Does the source of uncertainty matter? The impact of financial, newspaper and Twitter-based measures on U.S. banks," Research in International Business and Finance, Elsevier, vol. 65(C).
    2. Yusaku Nishimura & Xuyi Dong & Bianxia Sun, 2021. "Trump's tweets: Sentiment, stock market volatility, and jumps," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 44(3), pages 497-512, September.
    3. Shahzad, Syed Jawad Hussain & Anas, Muhammad & Bouri, Elie, 2022. "Price explosiveness in cryptocurrencies and Elon Musk's tweets," Finance Research Letters, Elsevier, vol. 47(PB).
    4. Dragomirescu-Gaina, Catalin & Philippas, Dionisis & Goutte, Stéphane, 2023. "How to ‘Trump’ the energy market: Evidence from the WTI-Brent spread," Energy Policy, Elsevier, vol. 179(C).
    5. Agrrawal, Pankaj & Agarwal, Rajat, 2023. "A Longer-Term evaluation of Information releases by Influential market Agents and the Semi-strong market Efficiency," EconStor Preprints 273555, ZBW - Leibniz Information Centre for Economics.
    6. Abdi, Farshid & Kormanyos, Emily & Pelizzon, Loriana & Getmansky, Mila & Simon, Zorka, 2021. "Market impact of government communication: The case of presidential tweets," SAFE Working Paper Series 314, Leibniz Institute for Financial Research SAFE, revised 2021.
    7. Machus, Tobias & Mestel, Roland & Theissen, Erik, 2022. "Heroes, just for one day: The impact of Donald Trump’s tweets on stock prices," Journal of Behavioral and Experimental Finance, Elsevier, vol. 33(C).

    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. Mariem Talbi & Amel Ben Halima, 2019. "Global Contagion of Investor Sentiment during the US Subprime Crisis: The Case of the USA and the Region of Latin America," International Journal of Economics and Financial Issues, Econjournals, vol. 9(3), pages 163-174.
    2. Keunbae Ahn, 2021. "Predictable Fluctuations in the Cross-Section and Time-Series of Asset Prices," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2021.
    3. Huynh, Toan Luu Duc & Foglia, Matteo & Nasir, Muhammad Ali & Angelini, Eliana, 2021. "Feverish sentiment and global equity markets during the COVID-19 pandemic," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 1088-1108.
    4. Enwei Zhu & Jing Wu & Hongyu Liu & Keyang Li, 2023. "A Sentiment Index of the Housing Market in China: Text Mining of Narratives on Social Media," The Journal of Real Estate Finance and Economics, Springer, vol. 66(1), pages 77-118, January.
    5. Guo, Kun & Sun, Yi & Qian, Xin, 2017. "Can investor sentiment be used to predict the stock price? Dynamic analysis based on China stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 390-396.
    6. Zhi Da & Borja Larrain & Clemens Sialm & José Tessada, 2016. "Coordinated Noise Trading: Evidence from Pension Fund Reallocations," NBER Working Papers 22161, National Bureau of Economic Research, Inc.
    7. Szymon Lis, 2022. "Investor Sentiment in Asset Pricing Models: A Review," Working Papers 2022-14, Faculty of Economic Sciences, University of Warsaw.
    8. Han, Xing & Li, Youwei, 2017. "Can investor sentiment be a momentum time-series predictor? Evidence from China," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 212-239.
    9. Wenjie Ding & Khelifa Mazouz & Qingwei Wang, 2019. "Investor sentiment and the cross-section of stock returns: new theory and evidence," Review of Quantitative Finance and Accounting, Springer, vol. 53(2), pages 493-525, August.
    10. 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.
    11. 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.
    12. Di, Li & Shaiban, Mohammed Sharaf & Hasanov, Akram Shavkatovich, 2021. "The power of investor sentiment in explaining bank stock performance: Listed conventional vs. Islamic banks," Pacific-Basin Finance Journal, Elsevier, vol. 66(C).
    13. Li, Xiao & Shen, Dehua & Xue, Mei & Zhang, Wei, 2017. "Daily happiness and stock returns: The case of Chinese company listed in the United States," Economic Modelling, Elsevier, vol. 64(C), pages 496-501.
    14. Lin, Chu-Bin & Chou, Robin K. & Wang, George H.K., 2018. "Investor sentiment and price discovery: Evidence from the pricing dynamics between the futures and spot markets," Journal of Banking & Finance, Elsevier, vol. 90(C), pages 17-31.
    15. Rakovská, Zuzana, 2021. "Composite survey sentiment as a predictor of future market returns: Evidence for German equity indices," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 473-495.
    16. Hanna, Alan J. & Turner, John D. & Walker, Clive B., 2017. "News media and investor sentiment over the long run," QUCEH Working Paper Series 2017-06, Queen's University Belfast, Queen's University Centre for Economic History.
    17. Wang, Wenzhao & Su, Chen & Duxbury, Darren, 2022. "The conditional impact of investor sentiment in global stock markets: A two-channel examination," Journal of Banking & Finance, Elsevier, vol. 138(C).
    18. Virk, Nader Shahzad & Butt, Hilal Anwar, 2022. "Asset pricing anomalies: Liquidity risk hedgers or liquidity risk spreaders?," International Review of Financial Analysis, Elsevier, vol. 81(C).
    19. Wang, Wenzhao, 2018. "Investor sentiment and the mean-variance relationship: European evidence," Research in International Business and Finance, Elsevier, vol. 46(C), pages 227-239.
    20. Hou, Yang & Meng, Jiayin, 2018. "The momentum effect in the Chinese market and its relationship with the simultaneous and the lagged investor sentiment," MPRA Paper 94838, University Library of Munich, Germany.

    More about this item

    Keywords

    European Financial Markets; Twitter; Sentiment; Donald Trump; Volfefe Index;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G40 - Financial Economics - - Behavioral Finance - - - General

    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:finlet:v:38:y:2021:i:c:s1544612319313674. 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/frl .

    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.