Drift Estimation of Generalized Security Price Processes from High Frequency Derivative Prices |
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Authors: | Pandher Gurupdesh S |
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Institution: | (1) Department of Finance, DePaul University, 1 East Jackson Blvd., Chicago, Illinois, 60604 |
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Abstract: | This paper presents a framework for using high frequency derivative prices to estimate the drift of generalized security price processes. This work may be seen more generally as a quasi-likelihood approach to estimating
continuous-time parameters of derivative pricing models using discrete option data. We develop a generalized derivative-based
estimator for the drift where the underlying security price process follows any arbitrary state-time separable diffusion process
(including arithmetic and geometric Brownian motion as special cases). The framework provides a method to measure premia in
derivative prices, test for risk-neutral pricing and leads to a new empirical approach to pricing derivative contingent claims.
A sufficient condition for the asymptotic consistency of the generalized estimator is also obtained. A study based on generating
the S&P500 index and calls shows that the estimator can correctly estimate the drift parameter.
This revised version was published online in November 2006 with corrections to the Cover Date. |
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Keywords: | excess return market price of risk risk-neutral pricing quasi-likelihood estimation Feynman-Kac asymptotic consistency |
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