Testing the Markov property with ultra high frequency financial data

This paper develops a framework to test whether discrete-valued irregularly-spaced financial transactions data follow a subordinated Markov process. For that purpose, we consider a specific optional sampling in which a continuous-time Markov process is observed only when it crosses some discrete lev...

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Detalles Bibliográficos
Autores: Matos, João Manuel Gonçalves Amaro de, Fernandes, Marcelo
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2001
País:Brasil
Institución:Fundação Getulio Vargas (FGV)
Repositorio:Repositório Institucional do FGV (FGV Repositório Digital)
Idioma:inglés
OAI Identifier:oai:repositorio.fgv.br:10438/780
Acceso en línea:http://hdl.handle.net/10438/780
Access Level:acceso abierto
Palabra clave:Bid-ask spread
Nonparametric tests
Price durations
Subordinated Markov process
Ultra-high frequency data
Economia
Markov, Processos de
Processo estocástico
Descripción
Sumario:This paper develops a framework to test whether discrete-valued irregularly-spaced financial transactions data follow a subordinated Markov process. For that purpose, we consider a specific optional sampling in which a continuous-time Markov process is observed only when it crosses some discrete level. This framework is convenient for it accommodates not only the irregular spacing of transactions data, but also price discreteness. Further, it turns out that, under such an observation rule, the current price duration is independent of previous price durations given the current price realization. A simple nonparametric test then follows by examining whether this conditional independence property holds. Finally, we investigate whether or not bid-ask spreads follow Markov processes using transactions data from the New York Stock Exchange. The motivation lies on the fact that asymmetric information models of market microstructures predict that the Markov property does not hold for the bid-ask spread. The results are mixed in the sense that the Markov assumption is rejected for three out of the five stocks we have analyzed.