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

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  • David Goldbaum

    ()
    (Economics Rutgers University)

  • Bruce Mizrach

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 Society for Computational Economics in its series Computing in Economics and Finance 2005 with number 295.

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Date of creation: 11 Nov 2005
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Handle: RePEc:sce:scecf5:295

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

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References

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  1. David Goldbaum, 2003. "Profitable technical trading rules as a source of price instability," Quantitative Finance, Taylor & Francis Journals, vol. 3(3), pages 220-229.
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  5. Xue-Zhong He & Carl Chiarella, 1999. "Heterogeneous Beliefs, Risk and Learning in a Simple Asset-Pricing Model," Computing in Economics and Finance 1999 223, Society for Computational Economics.
  6. de Fontnouvelle, Patrick, 2000. "Information Dynamics In Financial Markets," Macroeconomic Dynamics, Cambridge University Press, vol. 4(02), pages 139-169, June.
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  8. Carl Chiarella & Alexander Khomin, . "Adaptive Rational Expectations in Models of Monetary Dynamics," Computing in Economics and Finance 1997 97, Society for Computational Economics.
  9. 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.
  10. 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.
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  13. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
  14. 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.
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  16. Carhart, Mark M, 1997. " On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
  17. 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.
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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. Carl Chiarella & Xue-Zhong He & Weihong Huang & Huanhuan Zheng, 2011. "Estimating Behavioural Heterogeneity Under Regime Switching," Research Paper Series 290, Quantitative Finance Research Centre, University of Technology, Sydney.
  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. Blake LeBaron, 2011. "Active and Passive Learning in Agent-based Financial Markets," Eastern Economic Journal, Palgrave Macmillan, vol. 37(1), pages 35-43.
  5. Jang, Tae-Seok & Sacht, Stephen, 2012. "Identification of animal spirits in a bounded rationality model: An application to the euro area," Economics Working Papers 2012-12, Christian-Albrechts-University of Kiel, Department of Economics.
  6. 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.
  7. 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.
  8. 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.
  9. 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.

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