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.
Titolo: | Filtering on a Partially Observed Ultra-high-frequency Data Model |
Autori: | |
Data di pubblicazione: | 2006 |
Rivista: | |
Abstract: | 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. |
Handle: | http://hdl.handle.net/11697/13123 |
Appare nelle tipologie: | 1.1 Articolo in rivista |
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