Filtering on a partially observed ultra-high-frequency data model (Q2501130)
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| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Filtering on a partially observed ultra-high-frequency data model |
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Filtering on a partially observed ultra-high-frequency data model (English)
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4 September 2006
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A model for intraday stock price movements is considered. The jump-intensity of the logreturn process is a function of the whole history of a hidden marked point process. The aim is to find the conditional law of such intensity given the history of the logreturn process. Under a Markovianity assumption, related with the weak form of market efficiency, classical filtering techniques are used. The law of the jump-intensity, given the history of the logreturn price, is evaluated and a discussion on a particular case is performed.
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financial markets
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ultra-high-frequency data
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stochastic model
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nonlinear filtering
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Markov jumping processes
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