Hostname: page-component-7dd5485656-pnlb5 Total loading time: 0.001 Render date: 2025-10-31T16:53:22.720Z Has data issue: false hasContentIssue false
  • English
  • Français

Mimicking Portfolios with Conditioning Information

Published online by Cambridge University Press:  06 April 2009

Wayne Ferson ,
Andrew F. Siegel  and
Pisun (Tracy) Xu
Wayne Ferson
Affiliation:
ferson@bc.edu, Carroll School of Management, Boston College, Chestnut Hill, MA 02467
Andrew F. Siegel
Affiliation:
asiegal@u.Washington.edu, University of Washington Business School, Box 353200, Seattle, WA 98195.
Pisun (Tracy) Xu
Affiliation:
psxu@u.washington.edu, University of Washington Business School, Box 353200, Seattle, WA 98195.
Get access Rights & Permissions [Opens in a new window]

Abstract

Mimicking portfolios have long been useful in asset pricing research. In most empirical applications, the portfolio weights are assumed to be fixed over time, while in theory they may be functions of the economic state. This paper derives and characterizes mimicking portfolios in the presence of predetermined state variables, or conditioning information. The results generalize and integrate multifactor minimum variance efficiency (Fama (1996)) with conditional and unconditional mean-variance efficiency (Hansen and Richard (1987), Ferson and Siegel (2001)). Empirical examples illustrate the potential importance of time-varying mimicking portfolio weights and highlight challenges in their application.

Information

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 41 , Issue 3 , September 2006 , pp. 607 - 635
Copyright
Copyright © School of Business Administration, University of Washington 2006

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Breeden, D. “An Intertemporal Asset Pricing Model with Stochastic Consumption and Investment Opportunities.” Journal of Financial Economics, 7 (1979), 265–296.Google Scholar
Breeden, D.; Gibbons, M.; and Litzenberger, R.. “Empirical Tests of the Consumption-Oriented CAPM.” Journal of Finance, 44 (1989), 231–262.Google Scholar
Brown, S.;Gallagher, D.Steenbeck, O.; and Swan, P.. “Double or Nothing: Patterns fo Equity Fund Holdings and Transactions.” Working page, New york Univ. (2004).Google Scholar
Brown, S., and Warner, J.. “Measuring security Price Performance.” Journal of Financial Economics, 9 (1980), 205–258.Google Scholar
Chen, N.Roll, R.; and Ross, S. “Economic Forces andthe Stock Market.“ Journal of Business, 59 (1986), 383–403.CrossRefGoogle Scholar
Cochrane, J. Asser PricingPrinceton, NJ: Princeton Univ. Press (2001).Google Scholar
Dybvig, P., and Ross, S.. “Differential Information and Performation and Performance Measurement Using a Security Market Line.” Journal of Finance, 40 (1985), 383–399.Google Scholar
Eckbo, E.; Masulis, R.; and Norli, O.. “Seasoned Public offerings: Resolution of the New Issues Puzzle.” Jounal of Financial Economics, 56 (2000), 251–291.Google Scholar
Fama, E. “Stock Returns, Expected Returns and Real Activity.” Journal of Finance, 45 (1990), 1089–1109.CrossRefGoogle Scholar
Fama, E. “Multifactor Portfolio Efficiency and Multifactor Asset Pricing.” Journal of Financial and Quantitative Analysis, 31 (1996), 441–465.Google Scholar
Fama, E. “Determining the Number of Priced State Variables in the ICAPM.” Journal of Financial and Quantitative Analysis, 33 (1998), 217–231.Google Scholar
Fama, E., and French, K.. “Common Risk Factors in the Returns on Stocks and Bonds.” Journal of Finance, 33 (1993), 3–56.Google Scholar
Fama, E., and French, K.. “Multifactor Explantions of Asset Pricing Anomalies”. Journal of Finance, 51 (1996), 55–87.Google Scholar
Fama, E., and French, K.. “Industry Costs of Equity.” Journal of Financial Economics, 43 (1997), 153–193.Google Scholar
Fama, E., and Schwert, G.. “Asset Returns and Inflantion.” Journal of Financial Economics, 5 (1997), 115–146.Google Scholar
Ferson, W., and Harvey, C.. “The Variation of Economic Risk Premiums.” Journal of Political Economy, 99 (1991), 385–415.Google Scholar
Ferson, W., and Siegel, A.. “The Efficient Use of Conditioning Information in Portfolios.” Journal of Finance, 56 (2001), 967–982.Google Scholar
Ferson, W., and Siegel, A.. “Stochastic Discount Factor Bounds with Conditioning Information.” Review of Financial Studies, 16 (2003), 567–595.Google Scholar
Hansen, L. “Large Sample Properties of Generalized Method of Moment Estimators.” Econoetrica 50 (1982), 1029–1054.Google Scholar
Hansen, L., and Jagannathan, R.. “Implications of Security Market Data for Dynamic Economics.” Journal of Political of Economy, 99 (1991), 225–262.CrossRefGoogle Scholar
Hansen, L., and Richard, S. “The Role of Conditioning Information in Deducing Testable Restrictions implied by Dynamic Asset Pricing Models.” Econometrica, 55 (1987), 587–613.Google Scholar
Huberman, G., Kandel, S., and Stambaugh, R.. “predicting Returns in Stock and Bond Markets.” Journal of Financial Economics, 42 (1987), 1–9.Google Scholar
Keim, D., and Stambaugh, R.. “Predicting Returns in Stock and Bond Markets.” Journal of Financial Economics, 17 (1986), 357–390.Google Scholar
Lamont, O. “Economic Tracking Portfolios.” Journal of Econometrica, 105 (2001), 161–184.Google Scholar
Merton, R. “An intertemporal Capital Asset Pricing Model.” Econometrica, 41 (1973), 867–887.Google Scholar
Newey, W., and West, K.. “A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix.” Econometrica, 55 (1987), 703–708.Google Scholar
Stein, C. “Estimation of the Mean of a Multivariate Normal Distribution.” Proceedings of the Prague Symposium on Asymptotic Statistics (1973), 345–381.Google Scholar