IDEAS home Printed from https://ideas.repec.org/a/kap/jbioec/v9y2007i1p1-18.html
   My bibliography  Save this article

Lunacy in the Stock Market—What is the Evidence?

Author

Listed:
  • Anthony Herbst

Abstract

Popular culture and folklore have long recognized the influence of the lunar cycle on plant, animal, and human behavior. Many of the effects have been validated in the physical and biological sciences. However, until recently such effects have been largely, if not completely ignored in the academic literature of financial economics. This study aims to contribute to answering whether there is, as some claim, a lunar influence on stock prices or volatility. The findings of this work support the Efficient Markets Hypothesis—no consistent, predictable lunar influence is found on either daily returns or daily price volatility in the Dow Jones Industrial Average, for either new or full moons. Some effects are found, but not consistent or predictable with lunar and calendar information alone. Copyright Springer Science+Business Media, LLC 2007

Suggested Citation

  • Anthony Herbst, 2007. "Lunacy in the Stock Market—What is the Evidence?," Journal of Bioeconomics, Springer, vol. 9(1), pages 1-18, April.
    • Handle: RePEc:kap:jbioec:v:9:y:2007:i:1:p:1-18
    DOI: 10.1007/s10818-007-9016-3
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10818-007-9016-3
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10818-007-9016-3?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. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
    2. Yuan, Kathy & Zheng, Lu & Zhu, Qiaoqiao, 2006. "Are investors moonstruck? Lunar phases and stock returns," Journal of Empirical Finance, Elsevier, vol. 13(1), pages 1-23, January.
    3. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    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. repec:but:manage:v:4:y:2014:i:1:p:51-65 is not listed on IDEAS
    2. Reschenhofer, Erhard & Lingler, Michaela, 2013. "Detecting synchronous cycles in financial time series of unequal length," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 1-9.
    3. Rayenda Khresna Brahmana & Chee-Wooi Hooy & Zamri Ahmad, 2014. "Moon Phase as the Cause of Monday Irrationality: Case of Asean Day of the Week Anomaly," The International Journal of Economic Behavior - IJEB, Faculty of Business and Administration, University of Bucharest, vol. 4(1), pages 51-65.

    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. Enrique Ter Horst & Abel Rodriguez & Henryk Gzyl & German Molina, 2012. "Stochastic volatility models including open, close, high and low prices," Quantitative Finance, Taylor & Francis Journals, vol. 12(2), pages 199-212, May.
    2. Gonzalo Cortazar & Alejandro Bernales & Diether Beuermann, 2005. "Methodology and Implementation of Value-at-Risk Measures in Emerging Fixed-Income Markets with Infrequent Trading," Finance 0512030, University Library of Munich, Germany.
    3. Sergey S. Stepanov, 2009. "Resilience of Volatility," Papers 0911.5048, arXiv.org.
    4. Claudeci Da Silva & Hugo Agudelo Murillo & Joaquim Miguel Couto, 2014. "Early Warning Systems: Análise De Ummodelo Probit De Contágio De Crise Dos Estados Unidos Para O Brasil(2000-2010)," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 110, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    5. Athanasios Tsagkanos & Konstantinos Gkillas & Christoforos Konstantatos & Christos Floros, 2021. "Does Trading Volume Drive Systemic Banks’ Stock Return Volatility? Lessons from the Greek Banking System," IJFS, MDPI, vol. 9(2), pages 1-13, April.
    6. Grobys, Klaus, 2023. "Correlation versus co-fractality: Evidence from foreign-exchange-rate variances," International Review of Financial Analysis, Elsevier, vol. 86(C).
    7. Xinyi Qian, 2020. "Gold market price spillover between COMEX, LBMA and SGE," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 44(4), pages 810-831, October.
    8. Parthajit Kayal & Sumanjay Dutta & Vipul Khandelwal & Rakesh Nigam, 2021. "Information Theoretic Ranking of Extreme Value Returns," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 1-21, March.
    9. Muneer Shaik & S. Maheswaran, 2019. "Robust Volatility Estimation with and Without the Drift Parameter," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(1), pages 57-91, March.
    10. Panda, Ajaya Kumar & Panda, Pradiptarathi & Nanda, Swagatika & Parad, Atul, 2021. "Information bias and its spillover effect on return volatility: A study on stock markets in the Asia-Pacific region," Pacific-Basin Finance Journal, Elsevier, vol. 69(C).
    11. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    12. Torben G. Andersen & Tim Bollerslev, 1997. "Answering the Critics: Yes, ARCH Models Do Provide Good Volatility Forecasts," NBER Working Papers 6023, National Bureau of Economic Research, Inc.
    13. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    14. Bayraci, Selcuk & Demiralay, Sercan, 2013. "Conditional Autoregregressive Range (CARR) Based Volatility Spillover Index For the Eurozone Markets," MPRA Paper 51909, University Library of Munich, Germany.
    15. Christensen, Kim & Podolski, Mark, 2005. "Asymptotic theory for range-based estimation of integrated variance of a continuous semi-martingale," Technical Reports 2005,18, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    16. Fabio Fornari, 1993. "Estimating variability in the Italian stock market: An ARCH approach," Open Economies Review, Springer, vol. 4(4), pages 403-423, December.
    17. Elie Bouri & Riza Demirer & David Gabauer & Rangan Gupta, 2020. "Sentiment and Financial Market Connectedness: The Role of Investor Happiness," Working Papers 202022, University of Pretoria, Department of Economics.
    18. Parthajit Kayal & Sumanjay Dutta & Vipul Khandelwal, "undated". "Information Theoretic Ranking of Extreme Value Returns," Working Papers 2020-195, Madras School of Economics,Chennai,India.
    19. W Jane Cheung & Andrew B Jackson, 2013. "Chief Executive Officer departures and market uncertainty," Australian Journal of Management, Australian School of Business, vol. 38(2), pages 279-310, August.
    20. Seiler, Volker, 2024. "The relationship between Chinese and FOB prices of rare earth elements – Evidence in the time and frequency domain," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 160-179.

    More about this item

    Keywords

    lunar cycles; moon phases; stock market; volatility; E44; G12; G14;
    All these keywords.

    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • 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

    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:kap:jbioec:v:9:y:2007:i:1:p:1-18. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.