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Estimating the Intensity of Choice in a Dynamic Mutual Fund Allocation Decision

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  • David Goldbaum

    ()
    (Rutgers University - Newark)

  • Bruce Mizrach

    ()
    (Rutgers University)

Abstract

We estimate the intensity of choice parameter in heterogenous agent models in both a static and dynamic setting. Mean-variance optimizing agents choose among mutual funds of similar styles but varying performance. Actively managed funds have a lower Sharpe ratio than passive index funds, yet they attract a majority share of asset allocation. By estimating the relative growth of passive funds, we obtain a dynamic estimate of the intensity of choice calibrated to 10 years of mutual fund flows.

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Bibliographic Info

Paper provided by Rutgers University, Department of Economics in its series Departmental Working Papers with number 200414.

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Length: 20 pages
Date of creation: 06 Jun 2004
Date of revision:
Handle: RePEc:rut:rutres:200414

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Keywords: heterogenous agents; intensity of choice; mutual funds;

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References

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  1. Peter Boswijk & Cars H. Hommes & Sebastiano Manzan, 2005. "Behavioral Heterogeneity in Stock Prices," Tinbergen Institute Discussion Papers 05-052/1, Tinbergen Institute.
  2. Edwin J. Elton & Martin J. Gruber & Jeffrey A. Busse, 2004. "Are Investors Rational? Choices among Index Funds," Journal of Finance, American Finance Association, vol. 59(1), pages 261-288, 02.
  3. Carhart, Mark M, 1997. " On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
  4. Carl Chiarella & Xue-Zhong He, 1999. "Heterogeneous Beliefs, Risks and Learning in a Simple Asset Pricing Model," Research Paper Series 18, Quantitative Finance Research Centre, University of Technology, Sydney.
  5. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
  6. repec:att:wimass:9624 is not listed on IDEAS
  7. LeBaron, Blake & Arthur, W. Brian & Palmer, Richard, 1999. "Time series properties of an artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 23(9-10), pages 1487-1516, September.
  8. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
  9. Brock, William A & LeBaron, Blake D, 1996. "A Dynamic Structural Model for Stock Return Volatility and Trading Volume," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 94-110, February.
  10. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
  11. Brock, William A. & de Fontnouvelle, Patrick, 2000. "Expectational diversity in monetary economies," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 725-759, June.
  12. de Fontnouvelle, Patrick, 2000. "Information Dynamics In Financial Markets," Macroeconomic Dynamics, Cambridge University Press, vol. 4(02), pages 139-169, June.
  13. William A. Branch, 2004. "The Theory of Rationally Heterogeneous Expectations: Evidence from Survey Data on Inflation Expectations," Economic Journal, Royal Economic Society, vol. 114(497), pages 592-621, 07.
  14. David Goldbaum, 2003. "Profitable technical trading rules as a source of price instability," Quantitative Finance, Taylor & Francis Journals, vol. 3(3), pages 220-229.
  15. Gaunersdorfer, Andrea, 2000. "Endogenous fluctuations in a simple asset pricing model with heterogeneous agents," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 799-831, June.
  16. De Grauwe, Paul & Grimaldi, Marianna, 2006. "Exchange rate puzzles: A tale of switching attractors," European Economic Review, Elsevier, vol. 50(1), pages 1-33, January.
  17. Carl Chiarella & Alexander Khomin, . "Adaptive Rational Expectations in Models of Monetary Dynamics," Computing in Economics and Finance 1997 97, Society for Computational Economics.
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Citations

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Cited by:
  1. Lines, Marji & Westerhoff, Frank, 2009. "Effects of inflation expectations on macroeconomic dynamics: Extrapolative versus regressive expectations," BERG Working Paper Series 68, Bamberg University, Bamberg Economic Research Group.
  2. Jang, Tae-Seok & Sacht, Stephen, 2012. "Identification of Animal Spirits in a Bounded Rationality Model: An Application to the Euro Area," MPRA Paper 37399, University Library of Munich, Germany.
  3. Michael Wegener & Frank Westerhoff, 2012. "Evolutionary competition between prediction rules and the emergence of business cycles within Metzler’s inventory model," Journal of Evolutionary Economics, Springer, vol. 22(2), pages 251-273, April.
  4. Lux, Thomas, 2012. "Estimation of an agent-based model of investor sentiment formation in financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1284-1302.
  5. Hommes, Cars, 2011. "The heterogeneous expectations hypothesis: Some evidence from the lab," Journal of Economic Dynamics and Control, Elsevier, vol. 35(1), pages 1-24, January.
  6. Blake LeBaron, 2011. "Active and Passive Learning in Agent-based Financial Markets," Eastern Economic Journal, Palgrave Macmillan, vol. 37(1), pages 35-43.
  7. Chiarella, Carl & He, Xue-Zhong & Huang, Weihong & Zheng, Huanhuan, 2012. "Estimating behavioural heterogeneity under regime switching," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 446-460.
  8. Mahayni, Antje & Schoenmakers, John G.M., 2011. "Minimum return guarantees with fund switching rights—An optimal stopping problem," Journal of Economic Dynamics and Control, Elsevier, vol. 35(11), pages 1880-1897.
  9. Anufriev, M. & Tuinstra, J. & Bao, T., 2013. "Fund Choice Behavior and Estimation of Switching Models: An Experiment," CeNDEF Working Papers 13-04, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

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