On Identification of Continuous Time Stochastic Processes
| Autor: | Jeremy Berkowitz |
|---|---|
| Rok vydání: | 2000 |
| Předmět: |
Measurable function
Distribution (number theory) Stochastic process Generalization Function (mathematics) Parameter identification problem symbols.namesake Interest rates Asset pricing Econometric models Taylor series symbols Applied mathematics Linear combination Computer Science::Databases Mathematics |
| Zdroj: | Finance and Economics Discussion Series. 2000:1-16 |
| ISSN: | 1936-2854 |
| DOI: | 10.17016/feds.2000.07 |
| Popis: | In this note we delineate conditions under which continuous time stochastic processes can be identified from discrete data. The identification problem is approached in a novel way. The distribution of the observed stochastic process is expressed as the underlying true distribution, f, transformed by some operator, T. Using a generalization of the Taylor series expansion, the transformed function T f can often be expressed as a linear combination of the original function f. By combining the information across a large number of such transformations, the original measurable function of interest can be recovered. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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