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Testing mean-variance efficiency in CAPM with possibly non-gaussian errors: an exact simulation-based approach

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  • Dufour, Jean-Marie
  • Beaulieu, Marie-Claude
  • Khalaf, Lynda

Abstract

In this paper we propose exact likelihood-based mean-variance efficiency tests of the market portfolio in the context of Capital Asset Pricing Model (CAPM), allowing for a wide class of error distributions which include normality as a special case. These tests are developed in the framework of multivariate linear regressions (MLR). It is well known however that despite their simple statistical structure, standard asymptotically justified MLR-based tests are unreliable. In financial econometrics, exact tests have been proposed for a few specific hypotheses [Jobson and Korkie (Journal of Financial Economics, 1982), MacKinlay (Journal of Financial Economics, 1987), Gibbons, Ross and Shanken (Econometrica, 1989), Zhou (Journal of Finance 1993)] most of which depend on normality. For the gaussian model, our tests correspond to Gibbons, Ross and Shanken's mean-variance efficiency tests. In non-gaussian contexts, we reconsider mean-variance efficiency tests allowing for multivariate Student-t and gaussian mixture errors. Our framework allows to cast more evidence on whether the normality assumption is too restrictive when testing the CAPM. We also propose exact multivariate diagnostic checks (including tests for multivariate GARCH and multivariate generalization of the well known variance ratio tests) and goodness of fit tests as well as a set estimate for the intervening nuisance parameters. Our results [over five-year subperiods] show the following: (i) multivariate normality is rejected in most subperiods, (ii) residual checks reveal no significant departures from the multivariate i.i.d. assumption, and (iii) mean-variance efficiency tests of the market portfolio is not rejected as frequently once it is allowed for the possibility of non-normal errors. -- In diesem Papier schlagen wir exakte likelihood-basierte Tests auf Mittelwert-Varianz- Effizienz im Rahmen des CAPM vor. Dabei wird eine breite Klasse von Verteilungen für den stochastischen Term zugelassen. Normalverteilung ist ein Spezialfall. Die Tests werden im Rahmen von multivariablen linearen Regressionen (MLR) entwickelt. Bekanntlich sind Standardtests, die auf MLR basieren und asymptotisch gerechtfertigt werden, nicht zuverlässig. In der Finanzökonometrie sind exakte Tests für einige wenige Hypothesen vorgeschlagen worden. Die meisten hängen von der Annahme der Normalverteilung ab (Jobson und Korkie (1982), Mac Kinley (1987), Gibbons, Ross und Shanken (1989), Zhou (1993)). Für das gaussianische Modell entsprechen unsere Tests denen von Gibbons, Ross und Shanken. Im nichtgaussianischen Modell betrachten wir Mittelwert-Varianz-Effizienz-Tests, wobei multivariate-Student-t und ?gemischte? Normalverteilungen zugelassen werden. Unser Ansatz gibt mehr Aufschluß darüber, ob die Annahme der Normalverteilung zu restriktiv ist, wenn das CAPM gestestet wird. Wir schlagen auch exakte multivariate Diagnosen (einschließlich Tests für multivariate GARCH-Modelle und multivariate Verallgemeinerungen der bekannten Varianz- Relationen-Tests) sowie Tests auf die Anpassungsgüte und eine Schätzung für die störenden Verschmutzungsparameter vor. Unsere Ergebnisse (für 5-Jahres-Perioden) zeigen das Folgende: (i) multivariate Normalität wird für die meisten Perioden verworfen (ii) die Überprüfung der Residuen zeigt keine signifikante Abweichung von der Annahme einer multivariaten i.i.d. Verteilung (iii), wenn man nichtnormalverteilte Fehler zulässt, werden Mittelwert-Varianz-Effizienz Tests des Marktportfolios seltener verworfen.

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Bibliographic Info

Paper provided by Deutsche Bundesbank, Research Centre in its series Discussion Paper Series 1: Economic Studies with number 2003,01.

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Date of creation: 2003
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Handle: RePEc:zbw:bubdp1:4196

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Keywords: capital assed pricing model; CAPM; mean-variance efficiency; nonnormality; multivariate linear regression; uniform linear hypothesis; exact test;

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  1. Dufour, Jean-Marie & Kiviet, Jan F., 1996. "Exact tests for structural change in first-order dynamic models," Journal of Econometrics, Elsevier, vol. 70(1), pages 39-68, January.
  2. DUFOUR, Jean-Marie & KHALAF, Lynda, 2000. "Exact Tests for Contemporaneous Correlation of Disturbances in Seemingly Unrelated Regressions," Cahiers de recherche 2000-11, Universite de Montreal, Departement de sciences economiques.
  3. Shanken, Jay, 1990. "Intertemporal asset pricing : An Empirical Investigation," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 99-120.
  4. Andrew W. Lo & A. Craig MacKinlay, 1989. "Stock Market Prices Do Not Follow Random Walks: Evidence From a Simple Specification Test," NBER Working Papers 2168, National Bureau of Economic Research, Inc.
  5. Dufour, Jean-Marie & Khalaf, Lynda & Bernard, Jean-Thomas & Genest, Ian, 2004. "Simulation-based finite-sample tests for heteroskedasticity and ARCH effects," Journal of Econometrics, Elsevier, vol. 122(2), pages 317-347, October.
  6. Gibbons, Michael R. & Shanken, Jay, 1987. "Subperiod aggregation and the power of multivariate tests of portfolio efficiency," Journal of Financial Economics, Elsevier, vol. 19(2), pages 389-394, December.
  7. Stewart, Kenneth G., 1995. "The functional equivalence of the W, LR, and LM statistics," Economics Letters, Elsevier, vol. 49(2), pages 109-112, August.
  8. Lee, John H. H., 1991. "A Lagrange multiplier test for GARCH models," Economics Letters, Elsevier, vol. 37(3), pages 265-271, November.
  9. Raymond Kan & Guofu Zhou, 2012. "Tests of Mean-Variance Spanning," Annals of Economics and Finance, Society for AEF, vol. 13(1), pages 139-187, May.
  10. Kenneth Stewart, 1997. "Exact testing in multivariate regression," Econometric Reviews, Taylor and Francis Journals, vol. 16(3), pages 321-352.
  11. Fiorentini, G. & Sentana, E. & Calzolari, G., 2000. "The Score of Condionally Heteroskedastic Dynamic Regression Models with Student T Innovations, and an LM Test for Multivariate Normality," Papers 0007, Centro de Estudios Monetarios Y Financieros-.
  12. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
  13. Berndt, Ernst R & Savin, N Eugene, 1977. "Conflict among Criteria for Testing Hypotheses in the Multivariate Linear Regression Model," Econometrica, Econometric Society, vol. 45(5), pages 1263-77, July.
  14. Berk, Jonathan B., 1997. "Necessary Conditions for the CAPM," Journal of Economic Theory, Elsevier, vol. 73(1), pages 245-257, March.
  15. Beaulieu, Marie-Claude, 1998. "Time to maturity in the basis of stock market indices: Evidence from the S&P 500 and the MMI," Journal of Empirical Finance, Elsevier, vol. 5(3), pages 177-195, September.
  16. Allingham, Michael, 1991. "Existence Theorems in the Capital Asset Pricing Model," Econometrica, Econometric Society, vol. 59(4), pages 1169-74, July.
  17. Jean-Marie Dufour, 1997. "Some Impossibility Theorems in Econometrics with Applications to Structural and Dynamic Models," Econometrica, Econometric Society, vol. 65(6), pages 1365-1388, November.
  18. Dufour, J.M. & Khalaf, L., 2000. "Simulation-Based Finite and Large Sample Tests in Multivariate Regressions," Cahiers de recherche 2000-10, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  19. Richardson, Matthew & Smith, Tom, 1993. "A Test for Multivariate Normality in Stock Returns," The Journal of Business, University of Chicago Press, vol. 66(2), pages 295-321, April.
  20. Gibbons, Michael R & Ross, Stephen A & Shanken, Jay, 1989. "A Test of the Efficiency of a Given Portfolio," Econometrica, Econometric Society, vol. 57(5), pages 1121-52, September.
  21. Gibbons, Michael R., 1982. "Multivariate tests of financial models : A new approach," Journal of Financial Economics, Elsevier, vol. 10(1), pages 3-27, March.
  22. Jean-Marie Dufour, 2005. "Monte Carlo tests with nuisance parameters: a general approach to finite-sample inference and non-standard asymptotics," CIRANO Working Papers 2005s-02, CIRANO.
  23. Jiahui Wang & Eric Zivot, 1998. "Inference on Structural Parameters in Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 66(6), pages 1389-1404, November.
  24. Shanken, Jay, 1986. " Testing Portfolio Efficiency When the Zero-Beta Rate Is Unknown: A Note," Journal of Finance, American Finance Association, vol. 41(1), pages 269-76, March.
  25. Affleck-Graves, John & McDonald, Bill, 1989. " Nonnormalities and Tests of Asset Pricing Theories," Journal of Finance, American Finance Association, vol. 44(4), pages 889-908, September.
  26. Nielsen, Lars Tyge, 1990. "Existence of equilibrium in CAPM," Journal of Economic Theory, Elsevier, vol. 52(1), pages 223-231, October.
  27. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
  28. Zhou, Guofu, 1995. "Small sample rank tests with applications to asset pricing," Journal of Empirical Finance, Elsevier, vol. 2(1), pages 71-93, March.
  29. Zhou, Guofu, 1991. "Small sample tests of portfolio efficiency," Journal of Financial Economics, Elsevier, vol. 30(1), pages 165-191, November.
  30. Jobson, J. D. & Korkie, Bob, 1989. "A Performance Interpretation of Multivariate Tests of Asset Set Intersection, Spanning, and Mean-Variance Efficiency," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 24(02), pages 185-204, June.
  31. Jean-Marie Dufour & Abdeljelil Farhat & Lucien Gardiol & Lynda Khalaf, 1998. "Simulation-based finite sample normality tests in linear regressions," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages C154-C173.
  32. Dufour, Jean-Marie, 1990. "Exact Tests and Confidence Sets in Linear Regressions with Autocorrelated Errors," Econometrica, Econometric Society, vol. 58(2), pages 475-94, March.
  33. Owen, Joel & Rabinovitch, Ramon, 1983. " On the Class of Elliptical Distributions and Their Applications to the Theory of Portfolio Choice," Journal of Finance, American Finance Association, vol. 38(3), pages 745-52, June.
  34. MacKinlay, A Craig & Richardson, Matthew P, 1991. " Using Generalized Method of Moments to Test Mean-Variance Efficiency," Journal of Finance, American Finance Association, vol. 46(2), pages 511-27, June.
  35. Groenewold, Nicolaas & Fraser, Patricia, 2001. "Tests of asset-pricing models: how important is the iid-normal assumption?," Journal of Empirical Finance, Elsevier, vol. 8(4), pages 427-449, September.
  36. Jobson, J. D. & Korkie, Bob, 1982. "Potential performance and tests of portfolio efficiency," Journal of Financial Economics, Elsevier, vol. 10(4), pages 433-466, December.
  37. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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Cited by:
  1. Hooi Hooi Lean & Michael McAleer & Wing-Keung Wong, 2010. "Market Efficiency of Oil Spot and Futures: A Mean-Variance and Stochastic Dominance Approach," Working Papers in Economics 10/18, University of Canterbury, Department of Economics and Finance.
  2. Amengual, Dante & Sentana, Enrique, 2010. "A comparison of mean-variance efficiency tests," Journal of Econometrics, Elsevier, vol. 154(1), pages 16-34, January.
  3. Kaïs Dachraoui & Georges Dionne, 2004. "Conditions Ensuring the Separability of Asset Demand for All Risk-Averse Investors," Cahiers de recherche 0411, CIRPEE.
  4. Enrique Sentana, 2008. "The Econometrics Of Mean-Variance Efficiency Tests: A Survey," Working Papers wp2008_0807, CEMFI.

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