Advanced Search
MyIDEAS: Login

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

Contents:

Author Info

  • 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.

Download Info

To our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.

Bibliographic Info

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

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

Contact details of provider:
Postal: New Jersey Hall - 75 Hamilton Street, New Brunswick, NJ 08901-1248
Phone: (732) 932-7482
Fax: (732) 932-7416
Web page: http://snde.rutgers.edu/Rutgers/wp/rutgers-wplist.html
More information through EDIRC

Related research

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

Other versions of this item:

Find related papers by JEL classification:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. de Fontnouvelle, Patrick, 2000. "Information Dynamics In Financial Markets," Macroeconomic Dynamics, Cambridge University Press, vol. 4(02), pages 139-169, June.
  2. Peter Boswijk & Cars H. Hommes & Sebastiano Manzan, 2005. "Behavioral Heterogeneity in Stock Prices," Tinbergen Institute Discussion Papers 05-052/1, Tinbergen Institute.
  3. 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.
  4. 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.
  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. 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.
  7. William A. Brock & Blake D. LeBaron, 1995. "A Dynamic Structural Model for Stock Return Volatility and Trading Volume," NBER Working Papers 4988, National Bureau of Economic Research, Inc.
  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, W.A. & Hommes, C.H., 1996. "A Rational Route to Randomness," Working papers 9530r, Wisconsin Madison - Social Systems.
  10. 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.
  11. 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.
  12. David Goldbaum, 2003. "Profitable technical trading rules as a source of price instability," Quantitative Finance, Taylor & Francis Journals, vol. 3(3), pages 220-229.
  13. Carhart, Mark M, 1997. " On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
  14. 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.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. 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.
  2. 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.
  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. Sacht, Stephen & Jang, Tae-Seok, 2012. "Identification of Animal Spirits in a Bounded Rationality Model: An Application to the Euro Area," Annual Conference 2012 (Goettingen): New Approaches and Challenges for the Labor Market of the 21st Century 62071, Verein für Socialpolitik / German Economic Association.
  5. 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.
  6. 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.
  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, C.H., 2010. "The Heterogeneous Expectations Hypothesis: Some Evidence from the Lab," CeNDEF Working Papers 10-06, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  9. Blake LeBaron, 2011. "Active and Passive Learning in Agent-based Financial Markets," Eastern Economic Journal, Palgrave Macmillan, vol. 37(1), pages 35-43.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:rut:rutres:200414. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ().

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.