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On the negative value of information in informationally inefficient markets: Calculations for large number of traders

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  • Pfeifer, Christian
  • Schredelseker, Klaus
  • Seeber, Gilg U.H.

Abstract

In informationally inefficient markets, classical decision theory assumes the value of information to be positive. Recent developments, however, contradict this paradigm. Schredelseker [Schredelseker, K., 2001. Is the usefulness approach useful? Some reflections on the utility of public information. In: McLeay, S., Riccaboni, A. (Eds.), Contemporary Issues in Accounting Regulation, Kluwer Academic Publishers, Boston, pp. 135-153] proposed a simulation model wherein a single security is traded among non-cooperating and asymetrically informed traders. One of the main results was the fact that badly informed traders could expect higher returns than traders with more information. But Schredelseker was able to give exact results for a small number of traders only. The aim of this paper is to give reliable results for a sufficiently large number of traders for both the expected gain and the probability of gain larger than zero. We are using combinatorial methods in order to get exact results for badly informed traders and simulation techniques for results of traders with higher level of information. The exact results are used (error between exact results and simulation results for the first traders) to determine the number of samples which have to be drawn with the simulation algorithm. As a result it was possible to verify the negative value of information on gain for a sufficient large number of traders. Furthermore a partition of expected gain is given. Traders with less information seem to be in advantage because of that part of information which is unknown to them.

Suggested Citation

  • Pfeifer, Christian & Schredelseker, Klaus & Seeber, Gilg U.H., 2009. "On the negative value of information in informationally inefficient markets: Calculations for large number of traders," European Journal of Operational Research, Elsevier, vol. 195(1), pages 117-126, May.
    • Handle: RePEc:eee:ejores:v:195:y:2009:i:1:p:117-126
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    References listed on IDEAS

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    1. Hakansson, Nils H & Kunkel, J Gregory & Ohlson, James A, 1982. "Sufficient and Necessary Conditions for Information to Have Social Value in Pure Exchange," Journal of Finance, American Finance Association, vol. 37(5), pages 1169-1181, December.
    2. Hirshleifer, Jack, 1971. "The Private and Social Value of Information and the Reward to Inventive Activity," American Economic Review, American Economic Association, vol. 61(4), pages 561-574, September.
    3. Kunkel, J Gregory, 1982. "Sufficient Conditions for Public Information to Have Social Value in a Production and Exchange Economy," Journal of Finance, American Finance Association, vol. 37(4), pages 1005-1013, September.
    4. Baiman, S, 1975. "Evaluation And Choice Of Internal Information-Systems Within A Multiperson World," Journal of Accounting Research, Wiley Blackwell, vol. 13(1), pages 1-15.
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    Cited by:

    1. Choi, Hyung Sik & Schneider, Uwe A. & Rasche, Livia & Cui, Junbo & Schmid, Erwin & Held, Hermann, 2015. "Potential effects of perfect seasonal climate forecasting on agricultural markets, welfare and land use: A case study of Spain," Agricultural Systems, Elsevier, vol. 133(C), pages 177-189.
    2. Borgonovo, Emanuele & Hazen, Gordon B. & Jose, Victor Richmond R. & Plischke, Elmar, 2021. "Probabilistic sensitivity measures as information value," European Journal of Operational Research, Elsevier, vol. 289(2), pages 595-610.
    3. Klaus Schredelseker, 2012. "Finanzkrise — Mitschuld der Theorie?," Schmalenbach Journal of Business Research, Springer, vol. 64(8), pages 833-845, December.
    4. Weissensteiner, Alex, 2019. "Correlated noise: Why passive investment might improve market efficiency," Journal of Economic Behavior & Organization, Elsevier, vol. 158(C), pages 158-172.
    5. Florian Hauser & Jürgen Huber & Bob Kaempff, 2015. "Costly Information in Markets with Heterogeneous Agents: A Model with Genetic Programming," Computational Economics, Springer;Society for Computational Economics, vol. 46(2), pages 205-229, August.
    6. Florian Hauser & Bob Kaempff, 2013. "Evolution of trading strategies in a market with heterogeneously informed agents," Journal of Evolutionary Economics, Springer, vol. 23(3), pages 575-607, July.
    7. Wang, Zongrun & Chen, Songsheng, 2019. "Market efficiency, strategies and incomes of heterogeneously informed investors in a social network environment," Journal of Economic Behavior & Organization, Elsevier, vol. 158(C), pages 15-32.
    8. Carlo Marinelli & Alex Weissensteiner, 2013. "On the relation between forecast precision and trading profitability of financial analysts," Papers 1301.6638, arXiv.org.

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