IDEAS home Printed from https://ideas.repec.org/a/eee/quaeco/v76y2020icp292-309.html
   My bibliography  Save this article

Exploring economic anomalies in the S&P500 index

Author

Listed:
  • Parnes, Dror

Abstract

We examine anomalies in the S&P500 index, an equity-based proxy for the U.S. economy, from January 1957 until December 2018. We use the LOcally wEighted Scatterplot Smoothing (LOESS) nonlinear regression model with various smoothing degrees and identify high and low extreme values in the S&P500 index upon contrasting it with nine U.S. macroeconomic indicators. We find that high and low anomalies occur with cyclicality patterns with respect to the production rate, the inflation rate, the U.S. workforce, and the private consumption rate. A sharp distinction between earlier low anomalies and later high anomalies arises with respect to the interest rate and the U.S. trade price balance. Unusual recent high anomalies appear, however, with respect to the U.S. currency, the market sentiment, and the unemployment rate. We detect robust concentration of high economic anomalies in the S&P500 index (42 in the year of 2017 and 74 in the year of 2018) along eight (out of the nine) macroeconomic indicators. This realization can serve as a warning sign for market participants.

Suggested Citation

  • Parnes, Dror, 2020. "Exploring economic anomalies in the S&P500 index," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 292-309.
  • Handle: RePEc:eee:quaeco:v:76:y:2020:i:c:p:292-309
    DOI: 10.1016/j.qref.2019.09.012
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062976919300158
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.qref.2019.09.012?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. Eugene F. Fama & Kenneth R. French, 2008. "Dissecting Anomalies," Journal of Finance, American Finance Association, vol. 63(4), pages 1653-1678, August.
    2. Schwert, G. William, 2003. "Anomalies and market efficiency," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 15, pages 939-974, Elsevier.
    3. Olson, Dennis & Mossman, Charles & Chou, Nan-Ting, 2015. "The evolution of the weekend effect in US markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 58(C), pages 56-63.
    4. Harris, Lawrence E & Gurel, Eitan, 1986. "Price and Volume Effects Associated with Changes in the S&P 500 List: New Evidence for the Existence of Price Pressures," Journal of Finance, American Finance Association, vol. 41(4), pages 815-829, September.
    5. Mark J. Kamstra & Lisa A. Kramer & Maurice D. Levi, 2003. "Winter Blues: A SAD Stock Market Cycle," American Economic Review, American Economic Association, vol. 93(1), pages 324-343, March.
    6. Kelly, Patrick J. & Meschke, Felix, 2010. "Sentiment and stock returns: The SAD anomaly revisited," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1308-1326, June.
    7. Seyed Mehdian & Mark J. Perry, 2001. "The Reversal of the Monday Effect: New Evidence from US Equity Markets," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 28(7‐8), pages 1043-1065, September.
    8. Stambaugh, Robert F. & Yu, Jianfeng & Yuan, Yu, 2012. "The short of it: Investor sentiment and anomalies," Journal of Financial Economics, Elsevier, vol. 104(2), pages 288-302.
    9. Black, Angela & Fraser, Patricia & Groenewold, Nicolaas, 2003. "U.S. stock prices and macroeconomic fundamentals," International Review of Economics & Finance, Elsevier, vol. 12(3), pages 345-367.
    10. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    11. Grossman, Sanford J & Shiller, Robert J, 1981. "The Determinants of the Variability of Stock Market Prices," American Economic Review, American Economic Association, vol. 71(2), pages 222-227, May.
    12. Nicolaas Groenewold, 1997. "Share Prices and Macroeconomic Factors," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 24(9&10), pages 1367-1383.
    13. Joseph Engelberg & R. David Mclean & Jeffrey Pontiff, 2018. "Anomalies and News," Journal of Finance, American Finance Association, vol. 73(5), pages 1971-2001, October.
    14. Orawan Ratanapakorn & Subhash Sharma, 2007. "Dynamic analysis between the US stock returns and the macroeconomic variables," Applied Financial Economics, Taylor & Francis Journals, vol. 17(5), pages 369-377.
    15. French, Kenneth R., 1980. "Stock returns and the weekend effect," Journal of Financial Economics, Elsevier, vol. 8(1), pages 55-69, March.
    16. Chen, Nai-Fu & Roll, Richard & Ross, Stephen A, 1986. "Economic Forces and the Stock Market," The Journal of Business, University of Chicago Press, vol. 59(3), pages 383-403, July.
    17. Sven Bouman & Ben Jacobsen, 2002. "The Halloween Indicator, "Sell in May and Go Away": Another Puzzle," American Economic Review, American Economic Association, vol. 92(5), pages 1618-1635, December.
    18. Bali, Turan G. & Brown, Stephen J. & Murray, Scott & Tang, Yi, 2017. "A Lottery-Demand-Based Explanation of the Beta Anomaly," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(6), pages 2369-2397, December.
    19. Nicolaas, Patricia Groenewold Fraser, 1997. "Share Prices and Macroeconomic Factors," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 24(9‐10), pages 1367-1383, October.
    20. Ariel, Robert A., 1987. "A monthly effect in stock returns," Journal of Financial Economics, Elsevier, vol. 18(1), pages 161-174, March.
    21. Seyed Mehdian & Mark J. Perry, 2001. "The Reversal of the Monday Effect: New Evidence from US Equity Markets," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 28(7&8), pages 1043-1065.
    22. Sensoy, Berk A., 2009. "Performance evaluation and self-designated benchmark indexes in the mutual fund industry," Journal of Financial Economics, Elsevier, vol. 92(1), pages 25-39, April.
    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. Shanaev, Savva & Ghimire, Binam, 2022. "A generalised seasonality test and applications for cryptocurrency and stock market seasonality," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 172-185.
    2. Chen, Kexin & Pun, Chi Seng & Wong, Hoi Ying, 2023. "Efficient social distancing during the COVID-19 pandemic: Integrating economic and public health considerations," European Journal of Operational Research, Elsevier, vol. 304(1), pages 84-98.

    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. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, November.
    2. Qadan, Mahmoud & Nisani, Doron & Eichel, Ron, 2022. "Irregularities in forward-looking volatility," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 489-501.
    3. Urquhart, Andrew & McGroarty, Frank, 2014. "Calendar effects, market conditions and the Adaptive Market Hypothesis: Evidence from long-run U.S. data," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 154-166.
    4. Degenhardt, Thomas & Auer, Benjamin R., 2018. "The “Sell in May” effect: A review and new empirical evidence," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 169-205.
    5. Kaustia, Markku & Rantapuska, Elias, 2016. "Does mood affect trading behavior?," Journal of Financial Markets, Elsevier, vol. 29(C), pages 1-26.
    6. Shafiqur Rahman & Matthew J. Schneider, 2019. "Tests of Alternative Asset Pricing Models Using Individual Security Returns and a New Multivariate F-Test," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 22(01), pages 1-34, March.
    7. Benjamin R. Auer, 2019. "Does the strength of capital market anomalies exhibit seasonal patterns?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(1), pages 91-103, January.
    8. Mostafa Saidur Rahim Khan & Naheed Rabbani, 2019. "Market Conditions and Calendar Anomalies in Japanese Stock Returns," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 26(2), pages 187-209, June.
    9. Plastun, Alex & Sibande, Xolani & Gupta, Rangan & Wohar, Mark E., 2020. "Halloween Effect in developed stock markets: A historical perspective," International Economics, Elsevier, vol. 161(C), pages 130-138.
    10. Qadan, Mahmoud & Aharon, David Y. & Eichel, Ron, 2022. "Seasonal and Calendar Effects and the Price Efficiency of Cryptocurrencies," Finance Research Letters, Elsevier, vol. 46(PA).
    11. Sebastien Valeyre, 2020. "Refined model of the covariance/correlation matrix between securities," Papers 2001.08911, arXiv.org.
    12. Cochrane, John H., 2005. "Financial Markets and the Real Economy," Foundations and Trends(R) in Finance, now publishers, vol. 1(1), pages 1-101, July.
    13. Kaustia, Markku & Rantapuska, Elias, 2013. "Does mood affect trading behavior?," SAFE Working Paper Series 4, Leibniz Institute for Financial Research SAFE.
    14. Sebastien Valeyre & Denis Grebenkov & Sofiane Aboura & Francois Bonnin, 2016. "Should employers pay their employees better? An asset pricing approach," Papers 1602.00931, arXiv.org, revised Oct 2016.
    15. Levy, Tamir & Yagil, Joseph, 2012. "The week-of-the-year effect: Evidence from around the globe," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1963-1974.
    16. N. Groenewold, 2000. "Financial Deregulation and the Relationship Between the Economy and the Share Market in Australia," Economics Discussion / Working Papers 00-10, The University of Western Australia, Department of Economics.
    17. Wessel Marquering & Johan Nisser & Toni Valla, 2006. "Disappearing anomalies: a dynamic analysis of the persistence of anomalies," Applied Financial Economics, Taylor & Francis Journals, vol. 16(4), pages 291-302.
    18. Watson, John & Wickramanayake, J., 2012. "The relationship between aggregate managed fund flows and share market returns in Australia," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(3), pages 451-472.
    19. Richardson, Scott & Tuna, Irem & Wysocki, Peter, 2010. "Accounting anomalies and fundamental analysis: A review of recent research advances," Journal of Accounting and Economics, Elsevier, vol. 50(2-3), pages 410-454, December.
    20. N. Groenewold, 2000. "Fundamental Share Prices and Aggregate Real Output," Economics Discussion / Working Papers 00-05, The University of Western Australia, Department of Economics.

    More about this item

    Keywords

    S&P500 Index; Anomalies; U.S. macroeconomic indicators; LOESS;
    All these keywords.

    JEL classification:

    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    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:quaeco:v:76:y:2020:i:c:p:292-309. 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/620167 .

    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.