Linear approximations and tests of conditional pricing models
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Linear approximations and tests of conditional pricing models by Michael W. Brandt

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Published by National Bureau of Economic Research in Cambridge, Mass .
Written in English

Subjects:

  • Prices -- Econometric models

Book details:

Edition Notes

StatementMichael W. Brandt, David A. Chapman.
SeriesNBER working paper series -- no. 12513., Working paper series (National Bureau of Economic Research) -- working paper no. 12513.
ContributionsChapman, David A., 1960-, National Bureau of Economic Research.
The Physical Object
Pagination49 p. :
Number of Pages49
ID Numbers
Open LibraryOL17631276M
OCLC/WorldCa71340103

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Linear Approximations and Tests of Conditional Pricing Models. Michael W. Brandt & David A Issue Date September We construct a simple reduced-form example of a conditional pricing model with modest intrinsic nonlinearity. The theoretical magnitude of the pricing errors (alphas) induced by the application of standard linear Cited by: 2. Download Citation | Linear Approximations and Tests of Conditional Pricing Models* | If a nonlinear risk premium in a conditional asset pricing model is approximated with a linear function, as is. Linear Approximations and Tests of Conditional Pricing Models. Linear Approximations and Tests of Conditional Pricing Models * Michael W Brandt, Michael W Brandt Linear Approximations and Tests of Conditional Pricing Models, Review of Finance, Vol Issue 2, March , We calibrate the model to size- and book-to-market (B/M)-sorted portfolio returns, a short-term Treasury yield, and estimates.

  Brandt, Michael W. and Chapman, David A., Linear Approximations and Tests of Conditional Pricing Models (September ). NBER Working Paper No. w Downloadable! We construct a simple reduced-form example of a conditional pricing model with modest intrinsic nonlinearity. The theoretical magnitude of the pricing errors (alphas) induced by the application of standard linear conditioning are derived as a direct consequence of an omitted variables bias. When the model is calibrated to either characteristics sorted or industry portfolios, we. Empirical tests of conditional asset pricing models frequently approximate conditioning information using linear functions of observable variables. We explore the effects of these approximations in a simple economy in which the level of the short rate and the Sharpe ratio on a well-diversified portfolio serve as the two (latent) state variables. CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Empirical tests of conditional asset pricing models frequently approximate conditioning information using linear functions of observable variables. We explore the effects of these approximations in a simple economy in which the level of the short rate and the Sharpe ratio on a well-diversified portfolio serve as the.

Request PDF | Linear Approximations and Tests of Conditional Pricing Models | We construct a simple reduced-form example of a conditional pricing model with modest intrinsic nonlinearity. The. Get this from a library! Linear approximations and tests of conditional pricing models. [Michael W Brandt; D A Chapman; National Bureau of Economic Research.] -- We construct a simple reduced-form example of a conditional pricing model with modest intrinsic nonlinearity. The theoretical magnitude of the pricing errors (alphas) induced by the application of.   As explained in the previous section, the choice of the appropriate model for conditional portfolio evaluation depends on the statistical properties of the state variables z 1t, z 2t, , z 8t, considering that z 9t is a dummy variable. The results from ADF and Phillips-Peron unit root tests, reported in Table 2A, unambiguously indicate that the first five series are I(1), while z 6t, z 7t, z. Michael W. Brandt & David A. Chapman, "Linear Approximations and Tests of Conditional Pricing Models," NBER Working Papers , National Bureau of Economic Research, Inc. Full references (including those not matched with items on IDEAS).