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The role of additional information in option pricing: estimation issues for the state space model
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Wang, Ren-Her, Aston, John A. D. and Fuh, Cheng-Der. (2010) The role of additional information in option pricing: estimation issues for the state space model. Computational Economics, Vol.36 (No.4). pp. 283-307. ISSN 0927-7099
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Official URL: http://dx.doi.org/10.1007/s10614-010-9240-0
Abstract
We consider two competing financial state space models and investigate whether additional information in the form of option price data is helpful to the estimation of either the unobservable state variable (volatility) or the unknown parameters in the model. The complete discussion of the estimation problem in the presence of additional information involves decisions about filtering methods, the quality of the new information, the correlation between state variables and out-of-sample forecast performance. It is found that the state variable estimation is more sensitive than the parameter estimation to the correlation, information quality and the assumed linearity or non-linearity of the underlying model. As a result of the investigation of these factors, the particle filter is shown to be an attractive method for computing posterior distributions for these models.
| Item Type: | Journal Article |
|---|---|
| Subjects: | H Social Sciences > HC Economic History and Conditions H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management Q Science > QA Mathematics |
| Divisions: | Faculty of Science > Statistics |
| Journal or Publication Title: | Computational Economics |
| Publisher: | Springer New York LLC |
| ISSN: | 0927-7099 |
| Date: | December 2010 |
| Volume: | Vol.36 |
| Number: | No.4 |
| Number of Pages: | 25 |
| Page Range: | pp. 283-307 |
| Identification Number: | 10.1007/s10614-010-9240-0 |
| Status: | Peer Reviewed |
| Publication Status: | Published |
| Access rights to Published version: | Restricted or Subscription Access |
| URI: | http://wrap.warwick.ac.uk/id/eprint/4940 |
Data sourced from Thomson Reuters' Web of Knowledge
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