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Activity Number:
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514
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Type:
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Contributed
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Date/Time:
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Thursday, August 10, 2006 : 8:30 AM to 10:20 AM
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Sponsor:
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Business and Economics Statistics Section
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| Abstract - #306946 |
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Title:
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Nonlinear Properties of Conditional Returns under Scale Mixtures
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Author(s):
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Venkata Jandhyala*+ and Stergios B. Fotopoulos
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Companies:
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Washington State University and Washington State University
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Address:
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Department of Mathematics, Pullman, WA, 99164,
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Keywords:
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financial log returns ; APT model ; scale mixtures ; regression equation ; conditional variance ; GIG family of distributions
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Abstract:
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Analytical expressions are derived for the non-linear regression and its prediction error by modeling the log returns of financial assets as scale mixtures of the multivariate normal distribution. The expressions involve conditional moments of the mixing variable. These conditional moments are explicitly derived when the mixing variable belongs to the generalized inverse Gaussian family, of which gamma, inverse gamma and the inverse Gaussian distributions are members. The effectiveness of the nonlinear model over the usual linear model is captured through simulations for the above three families of distributions. The proposed scale mixture models extend the well-known arbitrage pricing theory (APT) in financial modeling to non-Gaussian cases. The methodology is applied to analyze the log returns intra-day data for DELL, COKE and S&P500 for the years 1998-2000.
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