IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v523y2019icp1150-1160.html
   My bibliography  Save this article

Statistical properties of volume and calendar effects in prediction markets

Author

Listed:
  • Restocchi, Valerio
  • McGroarty, Frank
  • Gerding, Enrico

Abstract

Prediction markets have proven to be an exceptional tool for harnessing the “wisdom of the crowd”, consequently making accurate forecasts about future events. Motivated by the lack of quantitative means of validations for models of prediction markets, in this paper we analyze the statistical properties of volume as well as the seasonal regularities (i.e., calendar effects) shown by volume and price. To accomplish this, we use a set of 3385 prediction market time series provided by PredictIt. We find that volume, with the exception of its seasonal regularities, possesses different properties than what is observed in financial markets. Moreover, price does not seem to exhibit any calendar effect. These findings suggest a significant difference between prediction and financial markets, and offer evidence for the need of studying prediction markets in more detail.

Suggested Citation

  • Restocchi, Valerio & McGroarty, Frank & Gerding, Enrico, 2019. "Statistical properties of volume and calendar effects in prediction markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1150-1160.
  • Handle: RePEc:eee:phsmap:v:523:y:2019:i:c:p:1150-1160
    DOI: 10.1016/j.physa.2019.03.096
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119303322
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2019.03.096?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. Tarun Chordia & Richard Roll & Avanidhar Subrahmanyam, 2001. "Market Liquidity and Trading Activity," Journal of Finance, American Finance Association, vol. 56(2), pages 501-530, April.
    2. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frederic Abergel, 2011. "Econophysics review: I. Empirical facts," Quantitative Finance, Taylor & Francis Journals, vol. 11(7), pages 991-1012.
    3. Rozeff, Michael S. & Kinney, William Jr., 1976. "Capital market seasonality: The case of stock returns," Journal of Financial Economics, Elsevier, vol. 3(4), pages 379-402, October.
    4. H. Bauke, 2007. "Parameter estimation for power-law distributions by maximum likelihood methods," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 58(2), pages 167-173, July.
    5. Mustafa Gultekin & Bulent Gultekin, "undated". "Stock Market Seasonality: Internal Evidence," Rodney L. White Center for Financial Research Working Papers 17-83, Wharton School Rodney L. White Center for Financial Research.
    6. Abergel,Frédéric & Anane,Marouane & Chakraborti,Anirban & Jedidi,Aymen & Muni Toke,Ioane, 2016. "Limit Order Books," Cambridge Books, Cambridge University Press, number 9781107163980.
    7. G.M. Constantinides & M. Harris & R. M. Stulz (ed.), 2003. "Handbook of the Economics of Finance," Handbook of the Economics of Finance, Elsevier, edition 1, volume 1, number 1.
    8. Frédéric Abergel & Anirban Chakraborti & Aymen Jedidi & Ioane Muni Toke & Marouane Anane, 2016. "Limit Order Books," Post-Print hal-02177394, HAL.
    9. Agrawal, Anup & Tandon, Kishore, 1994. "Anomalies or illusions? Evidence from stock markets in eighteen countries," Journal of International Money and Finance, Elsevier, vol. 13(1), pages 83-106, February.
    10. Gopikrishnan, P. & Plerou, V. & Gabaix, X. & Amaral, L.A.N. & Stanley, H.E., 2001. "Price fluctuations and market activity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 137-143.
    11. Gultekin, Mustafa N. & Gultekin, N. Bulent, 1983. "Stock market seasonality : International Evidence," Journal of Financial Economics, Elsevier, vol. 12(4), pages 469-481, December.
    12. Lakonishok, Josef & Maberly, Edwin, 1990. "The Weekend Effect: Trading Patterns of Individual and Institutional Investors," Journal of Finance, American Finance Association, vol. 45(1), pages 231-243, March.
    13. R. David Mclean & Jeffrey Pontiff, 2016. "Does Academic Research Destroy Stock Return Predictability?," Journal of Finance, American Finance Association, vol. 71(1), pages 5-32, February.
    14. Rama Cont & Marc Potters & Jean-Philippe Bouchaud, 1997. "Scaling in stock market data: stable laws and beyond," Science & Finance (CFM) working paper archive 9705087, Science & Finance, Capital Fund Management.
    15. Justin Wolfers & Eric Zitzewitz, 2006. "Prediction Markets in Theory and Practice," NBER Working Papers 12083, National Bureau of Economic Research, Inc.
    16. M. J. Fields, 1931. "Stock Prices: A Problem in Verification," The Journal of Business, University of Chicago Press, vol. 4, pages 415-415.
    17. Parameswaran Gopikrishnan & Vasiliki Plerou & Xavier Gabaix & H. Eugene Stanley, 2000. "Statistical Properties of Share Volume Traded in Financial Markets," Papers cond-mat/0008113, arXiv.org.
    18. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frédéric Abergel, 2011. "Econophysics review: II. Agent-based models," Post-Print hal-00621059, HAL.
    19. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034, Decembrie.
    20. G.M. Constantinides & M. Harris & R. M. Stulz (ed.), 2003. "Handbook of the Economics of Finance," Handbook of the Economics of Finance, Elsevier, edition 1, volume 1, number 2.
    21. V. Plerou & P. Gopikrishnan & X. Gabaix & L. A. N. Amaral & H. E. Stanley, 2001. "Price fluctuations, market activity and trading volume," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 262-269.
    22. James M. Poterba & Scott J. Weisbenner, 2001. "Capital Gains Tax Rules, Tax‐loss Trading, and Turn‐of‐the‐year Returns," Journal of Finance, American Finance Association, vol. 56(1), pages 353-368, February.
    23. Sias, Richard W & Starks, Laura T, 1997. "Institutions and Individuals at the Turn-of-the-Year," Journal of Finance, American Finance Association, vol. 52(4), pages 1543-1562, September.
    24. Reinganum, Marc R., 1983. "The anomalous stock market behavior of small firms in January : Empirical tests for tax-loss selling effects," Journal of Financial Economics, Elsevier, vol. 12(1), pages 89-104, June.
    25. Y. Malevergne & V. Pisarenko & D. Sornette, 2005. "Empirical distributions of stock returns: between the stretched exponential and the power law?," Quantitative Finance, Taylor & Francis Journals, vol. 5(4), pages 379-401.
    26. Goodell, John W. & McGroarty, Frank & Urquhart, Andrew, 2015. "Political uncertainty and the 2012 US presidential election: A cointegration study of prediction markets, polls and a stand-out expert," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 162-171.
    27. Officer, R. R., 1975. "Seasonality in Australian capital markets : Market efficiency and empirical issues," Journal of Financial Economics, Elsevier, vol. 2(1), pages 29-51, March.
    28. Qiu, T. & Zhong, L.X. & Chen, G. & Wu, X.R., 2009. "Statistical properties of trading volume of Chinese stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(12), pages 2427-2434.
    29. Vasiliki Plerou & Parameswaran Gopikrishnan & Xavier Gabaix & H. Eugene Stanley, 2004. "On the Origin of Power-Law Fluctuations in Stock Prices," Papers cond-mat/0403067, arXiv.org.
    30. Gabaix, Xavier & Gopikrishnan, Parameswaran & Plerou, Vasiliki & Stanley, Eugene, 2007. "A unified econophysics explanation for the power-law exponents of stock market activity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 81-88.
    31. French, Kenneth R., 1980. "Stock returns and the weekend effect," Journal of Financial Economics, Elsevier, vol. 8(1), pages 55-69, March.
    32. Praetz, Peter D, 1972. "The Distribution of Share Price Changes," The Journal of Business, University of Chicago Press, vol. 45(1), pages 49-55, January.
    33. Sidney B. Wachtel, 1942. "Certain Observations on Seasonal Movements in Stock Prices," The Journal of Business, University of Chicago Press, vol. 15, pages 184-184.
    34. Bhardwaj, Ravinder K & Brooks, LeRoy D, 1992. "The January Anomaly: Effects of Low Share Price, Transaction Costs, and Bid-Ask Bias," Journal of Finance, American Finance Association, vol. 47(2), pages 553-575, June.
    35. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frederic Abergel, 2011. "Econophysics review: II. Agent-based models," Quantitative Finance, Taylor & Francis Journals, vol. 11(7), pages 1013-1041.
    36. Franck Jovanovic & Christophe Schinckus, 2017. "Econophysics and Financial Economics," Post-Print hal-03541391, HAL.
    37. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    38. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frédéric Abergel, 2011. "Econophysics review: I. Empirical facts," Post-Print hal-00621058, HAL.
    39. Richmond, Peter & Mimkes, Jurgen & Hutzler, Stefan, 2013. "Econophysics and Physical Economics," OUP Catalogue, Oxford University Press, number 9780199674701, Decembrie.
    40. Berg, Joyce E. & Nelson, Forrest D. & Rietz, Thomas A., 2008. "Prediction market accuracy in the long run," International Journal of Forecasting, Elsevier, vol. 24(2), pages 285-300.
    Full references (including those not matched with items on IDEAS)

    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. Restocchi, Valerio & McGroarty, Frank & Gerding, Enrico, 2019. "The stylized facts of prediction markets: Analysis of price changes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 159-170.
    2. Matteo Rossi & Gabriella Marcarelli & Antonella Ferraro & Antonio Lucadamo, 2020. "How do Calendar Anomalies Affect an Investment Choice? A Proposal of an Analytic Hierarchy Process Model," International Journal of Economics and Financial Issues, Econjournals, vol. 10(1), pages 244-249.
    3. Suliman Zakaria Suliman Abdalla, 2015. "An Investigation of the Month-of-The-Year Effect for the Sudanese Stock Market," Working Papers 924, Economic Research Forum, revised Jun 2015.
    4. Rajesh Elangovan & Francis Gnanasekar Irudayasamy & Satyanarayana Parayitam, 2022. "Month-of-the-Year Effect: Empirical Evidence from Indian Stock Market," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 29(3), pages 449-476, September.
    5. Stefanescu, Răzvan & Dumitriu, Ramona, 2020. "Introducere în analiza anomaliilor calendaristice, Partea a doua [An Introduction to the Analysis of the Calendar Anomalies, Part 2]," MPRA Paper 97961, University Library of Munich, Germany.
    6. Cameron Truong, 2013. "The January effect, does options trading matter?," Australian Journal of Management, Australian School of Business, vol. 38(1), pages 31-48, April.
    7. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, November.
    8. Plastun, Alex & Sibande, Xolani & Gupta, Rangan & Wohar, Mark E., 2019. "Rise and fall of calendar anomalies over a century," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 181-205.
    9. Danny Yeung, 2012. "The Impact of Institutional Ownership: A Study of the Australian Equity Market," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 11, July-Dece.
    10. Fatta Bahadur K.C. Ph. D. & Nayan Krishna Joshi, 2005. "The Nepalese Stock Market: Efficient and Calendar Anomalies," NRB Economic Review, Nepal Rastra Bank, Research Department, vol. 17, pages 40-85, April.
    11. Irfan Ali & Waheed Akhter & Namrah Ashraf, 2017. "Impact of Muslim Holy Days on Asian stock markets: An empirical evidence," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1311096-131, January.
    12. Marco Bee & Debbie J. Dupuis & Luca Trapin, 2016. "US stock returns: are there seasons of excesses?," Quantitative Finance, Taylor & Francis Journals, vol. 16(9), pages 1453-1464, September.
    13. Lean, Hooi Hooi & Smyth, Russell & Wong, Wing-Keung, 2007. "Revisiting calendar anomalies in Asian stock markets using a stochastic dominance approach," Journal of Multinational Financial Management, Elsevier, vol. 17(2), pages 125-141, April.
    14. Khalil Jebran & Shihua Chen, 2017. "Examining anomalies in Islamic equity market of Pakistan," Journal of Sustainable Finance & Investment, Taylor & Francis Journals, vol. 7(3), pages 275-289, July.
    15. Michael E. Drew & Mirela Mallin & Tony Naughton & Madhu Veeraraghavan, 2004. "Equity Premium: - Does it exist? Evidence from Germany and United Kingdom," School of Economics and Finance Discussion Papers and Working Papers Series 170, School of Economics and Finance, Queensland University of Technology.
    16. Faheem Aslam & Ahmed Imran Hunjra & Tahar Tayachi & Peter Verhoeven & Yasir Tariq Mohmand, 2022. "Calendar Anomalies in Islamic Frontier Markets," SAGE Open, , vol. 12(2), pages 21582440221, May.
    17. 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.
    18. 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.
    19. Kononovicius, Aleksejus & Ruseckas, Julius, 2019. "Order book model with herd behavior exhibiting long-range memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 171-191.
    20. Stefanescu, Răzvan & Dumitriu, Ramona, 2016. "The impact of the Great Lent and of the Nativity Fast on the Bucharest Stock Exchange," MPRA Paper 89023, University Library of Munich, Germany, revised 22 Dec 2016.

    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:phsmap:v:523:y:2019:i:c:p:1150-1160. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.