Business & Information Systems Engineering

, Volume 57, Issue 6, pp 349–361 | Cite as

Beware of Performance Indicators

How Visual Cues Increase the Disposition Effect
  • Tobias T. Kranz
  • Florian Teschner
  • Christof Weinhardt
Research Paper

Abstract

Online trading interfaces are important instruments for retail investors. For sound reasons, regulators obligate online brokers to inform customers about certain trade related risks. Research has shown that different behavioral biases can decrease traders’ performance and hence lead to pecuniary losses. The disposition to hold losing stocks too long and sell winning stocks too early (‘disposition effect’) is such a deviation from rational behavior. The disposition effect is analyzed for the prediction market ‘Kurspiloten’ which predicts selected stock prices and counts nearly 2000 active traders and more than 200,000 orders. We show that the disposition effect can be aggravated by visual feedback on a trader’s performance via colored trend direction arrows and percentages. However, we find no evidence that such an interface modification leads to higher activity. Furthermore, we can not confirm that creating awareness of the disposition effect with textual information is suited to decreasing its strength.

Keywords

Retail investor behavior Human computer interaction Disposition effect Electronic markets Market interface design 

Notes

Acknowledgments

We are very grateful to the anonymous reviewers for their valuable comments as well as to the proof-reader. Furthermore, we thank the author and contributors of the texreg package (Leifeld 2013).

Supplementary material

12599_2015_399_MOESM1_ESM.pdf (1.2 mb)
(pdf 1278 kB)

References

  1. Andreassen PB (1988) Explaining the price-volume relationship: the difference betweeen price changes and changing prices. Organ Behav Hum Decis Process 41(3):371–389CrossRefGoogle Scholar
  2. Bakos Y, Lucas HC Jr., Oh W (2005) The impact of E-commerce on competition in the retail brokerage industry. Inf Syst Res 16(4):352–371CrossRefGoogle Scholar
  3. Barber BM, Lee Y-T, Liu Y-J, Odean T (2007) Is the aggregate investor reluctant to realise losses? Evidence from Taiwan. Europ Financ Manag 13(3):423–447CrossRefGoogle Scholar
  4. Bhandari G, Hassanein K (2010) An agent-based debiasing framework for investment decision-support systems. Behav Inf Technol 31(5):495–507CrossRefGoogle Scholar
  5. Bhandari G, Hassanein K, Deaves R (2008) Debiasing investors with decision support systems: an experimental investigation. Decis Support Syst 46(1):399–410CrossRefGoogle Scholar
  6. Boer H, Ter Huurne E, Taal E (2006) Effects of pictures and textual arguments in sun protection public service announcements. Cancer Detect Prevent 30(5):432–438CrossRefPubMedGoogle Scholar
  7. Borghesi R (2013) The impact of the disposition effect on asset prices: insight from the NBA. J Econ Financ, Forthcoming, pp 1–14Google Scholar
  8. Camargo A, Isabella F (2013) The race for self-directed investors: developments in online trading among brokers and banks. Technical report 1, Celent, 499 Washington Blvd, 11th Floor Jersey City, NJ 07310Google Scholar
  9. Chen K-Y, Plott CR (2002) Information aggregation mechanisms: concept, design and implementation for a sales forecasting problem. California Institute of Technology Social Science Working Paper, 1131Google Scholar
  10. Christiansen JD (2007) Prediction markets: practical experiments in small markets and behaviour observed. J Predict Mark 1(1):17–41Google Scholar
  11. Dhar R, Zhu N (2006) Up close and personal: an individual level analysis of the disposition effect. Manag Sci 52(5):726–740CrossRefGoogle Scholar
  12. Feng L, Seasholes MS (2005) Do investor sophistication and trading experience eliminate behavioral biases in financial markets. Rev Financ 9:305–351CrossRefMATHGoogle Scholar
  13. Fenton-O’Creevy M, Gareth D, Ben H, Adam MTP, Astor PJ, Mark von Overveld AS, Jeffrey TL (2012) In-depth studies: results (Year 3) (D9–2.3.3). Report 1, xDELIAGoogle Scholar
  14. Forsythe R, Nelson F, Neumann GR, Wright J (1992) Anatomy of an experimental political stock market. Am Econ Rev 82(5):1142–1161Google Scholar
  15. Garvey R, Murphy A (2004) Are professional traders too slow to realize their losses? Financ Anal J 60(4):35–43CrossRefGoogle Scholar
  16. Gjerstad S (2005) Risk aversion, beliefs, and prediction market equilibrium. Microeconomics, EconWPAGoogle Scholar
  17. Hammond D (2011) Cigarette package health warnings and interest in quit smoking – 14 countries. Morb Mortal Wkly Rep 60(20):645–651Google Scholar
  18. Hanson R (2002) Logarithmic market scoring rules for modular combinatorial information aggregation. J Predict Mark 1(1):2–15Google Scholar
  19. Hartzmark SM, Solomon DH (2012) Efficiency and the disposition effect in NFL prediction markets. Q J Econ, 2(3):1250013–1–1250013–42Google Scholar
  20. Hedtrich F, Loy J-P, Müller RAE (2011) Supply chain management-new perspectives, chapter prediction markets – a new tool for managing supply chainsGoogle Scholar
  21. Kahneman D, Tversky A (1979) Prospect theory: an analysis of decision under risk. Econometrica 47(2):263–292CrossRefMATHGoogle Scholar
  22. Lakonishok J, Smidt S (1986) Volume for winners and losers: taxation and other motives for stock trading. J Financ 41(4):951–974CrossRefGoogle Scholar
  23. Leifeld P (2013) Texreg: conversion of statistical model output in R to LaTeX and HTML tables. J Stat Softw 55(8):1–24CrossRefGoogle Scholar
  24. Lim L-H, Benbasat I (1996) A framework for addressing group judgment biases with group technology. J Manag Inf Syst 13(3):7–24CrossRefGoogle Scholar
  25. Machina MJ (1982) Expected utility analysis without the independence axiom. Econometrica 50(2):277–323MathSciNetCrossRefMATHGoogle Scholar
  26. Odean T (1998) Are investors reluctant to realize their losses? J Financ 53(5):1775–1798CrossRefGoogle Scholar
  27. Seru A, Shumway T, Stoffman N (2010) Learning by trading. Rev Financ Stud 23(2):705–739CrossRefGoogle Scholar
  28. Servan-Schreiber E, Wolfers J, Pennock DM, Galebach B (2004) Prediction markets: does money matter? Electron Mark 14(3):243–251CrossRefGoogle Scholar
  29. Shapira Z, Venezia I (2001) Patterns of behavior of professionally managed and independent investors. J Bank Financ 25(8):1573–1587CrossRefGoogle Scholar
  30. Shefrin H, Statman M (1985) The disposition to sell winners too early and ride losers too long: theory and evidence. J Financ 40(3):777–790CrossRefGoogle Scholar
  31. Slamka C, Soukhoroukova A, Spann M (2008) Event studies in real- and play-money prediction markets. J Predict Mark 2(2):53–70Google Scholar
  32. Speier C, Morris MG (2003) The influence of query interface design on decision-making performance. MIS Q 27(3):397–423Google Scholar
  33. Stathel S, Florian T, Tobias K, Tobias K, Clemens van Dinther, Christof W (2010) Innovation assessment via enterprise information markets. In: Proceedings of the 1st International conference on IT-enabled innovation in enterprise, pp 206–218Google Scholar
  34. Teschner F, Stephan S, Christof W (2011) A prediction market for macro-economic variables. In: 44th Hawaii international conference on system sciences (HICSS), 2011, pp 1–9Google Scholar
  35. Teschner F, Wagenschwanz F, Weinhardt C (2012) Analysis of the disposition effect: asymetry and prediction accuracy. J Predict Mark 7(1):27–42Google Scholar
  36. Thaler R (1985) Mental accounting and consumer choice. Market Sci 4(3):199–214CrossRefGoogle Scholar
  37. Thaler RH, Shefrin HM (1981) An economic theory of self-control. J Polit Econ 89(2):392–406CrossRefGoogle Scholar
  38. Weber M, Camerer CF (1998) The disposition effect in securities trading: an experimental analysis. J Econ Behav Organiz 33(2):167–184CrossRefGoogle Scholar
  39. Weber M, Frank W (2007) An individual level analysis of the disposition effect: empirical and experimental evidence. Technical report 07–45, DFG SFB 504, University of MannheimGoogle Scholar
  40. Wolfers J, Eric Z (2004) Prediction markets. J Econ Perspect, 18(2):107–126. http://www.nber.org/papers/w10504

Copyright information

© Springer Fachmedien Wiesbaden 2015

Authors and Affiliations

  • Tobias T. Kranz
    • 1
  • Florian Teschner
    • 1
  • Christof Weinhardt
    • 1
  1. 1.Institut für Informationswirtschaft und Marketing (IISM), Karlsruher Institut für TechnologieKarlsruheGermany

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