Abstract
A model of O-U process with discrete noises is proposed for the price micro-movement, which refers to the transactional price behavior. The model can be viewed as a multivariate point process and framed as a filtering problem with counting process observations. Under this framework, the whole sample paths are observable and are used for parameter estimation. Based on the filtering equation, we construct a consistent recursive algorithm to compute the approximate posterior and the Bayes estimates. Finally, Bayes estimates for a two-month transaction prices of Microsoft are obtained.
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Zeng, Y. (2001) A partially-observed model for micro-movement of stock price with Bayes estimation via filtering equation, Working Paper. Department of Mathematics and Statistics, University of Missouri at Kansas City.
Zeng, Y. (2001) Bayesian estimation for a simple micro-movement stock price model with discrete noises, Working Paper. Department of Mathematics and Statistics, University of Missouri at Kansas City.
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© 2002 Springer-Verlag Berlin Heidelberg
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Zeng, Y., Scott, L.C. (2002). Bayes Estimation via Filtering Equation for O-U Process with Discrete Noises: Application to the Micro-Movement of Stock Prices. In: Pasik-Duncan, B. (eds) Stochastic Theory and Control. Lecture Notes in Control and Information Sciences, vol 280. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48022-6_36
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DOI: https://doi.org/10.1007/3-540-48022-6_36
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