A NOTE ON BAYESIAN INFERENCE IN ASSET PRICING

2001 ◽  
Vol 17 (2) ◽  
pp. 475-482
Author(s):  
J.L. Knight ◽  
S.E. Satchell

In this paper the authors extend results by Harvey and Zhou (1990, Journal of Financial Econometrics 26, 221–254) and Kandel, McCulloch, and Stambaugh (1995, Review of Financial Studies 8(1), 1–53) to derive the posterior distribution of a key parameter in a Bayesian analysis of asset pricing models. It is shown that this distribution depends upon the same terms that constitute the standard asset pricing test of Jobson and Korkie (1985, Canadian Journal of Administrative Science 12, 114–138). Contrary to the view held by other authors, we find straightforward expressions for the posterior distribution that can be calculated without resorting to Monte Carlo methods.

Author(s):  
MARCO AVELLANEDA ◽  
ROBERT BUFF ◽  
CRAIG FRIEDMAN ◽  
NICOLAS GRANDECHAMP ◽  
LUKASZ KRUK ◽  
...  

2002 ◽  
Vol 17 (2) ◽  
pp. 149-174 ◽  
Author(s):  
Christopher Otrok ◽  
B. Ravikumar ◽  
Charles H. Whiteman

Author(s):  
Marco Avellaneda ◽  
Robert Buff ◽  
Craig Friedman ◽  
Nicolas Grandchamp ◽  
Lukasz Kruk ◽  
...  

Mathematics ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 739
Author(s):  
Hilmar Gudmundsson ◽  
David Vyncke

The weighted Monte Carlo method is an elegant technique to calibrate asset pricing models to market prices. Unfortunately, the accuracy can drop quite quickly for out-of-sample options as one moves away from the strike range and maturity range of the benchmark options. To improve the accuracy, we propose a generalized version of the weighted Monte Carlo calibration method with two distinguishing features. First, we use a probability distortion scheme to produce a non-uniform prior distribution for the simulated paths. Second, we assign multiple weights per path to fit with the different maturities present in the set of benchmark options. Our tests on S&P500 options data show that the new calibration method proposed here produces a significantly better out-of-sample fit than the original method for two commonly used asset pricing models.


Author(s):  
Carlo A. Favero ◽  
Fulvio Ortu ◽  
Andrea Tamoni ◽  
Haoxi Yang

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