Result: Testing the Markov property with high frequency data

Title:
Testing the Markov property with high frequency data
Authors:
AMARO DE MATOS, Joao, FERNANDES, Marcelo
Source:
Semiparametric methods in econometricsJournal of econometrics. 141(1):44-64
Publisher Information:
Amsterdam: Elsevier, 2007.
Publication Year:
2007
Physical Description:
print, 1 p.1/2
Original Material:
INIST-CNRS
Subject Terms:
Control theory, operational research, Automatique, recherche opérationnelle, Mathematics, Mathématiques, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Topologie. Variétés et complexes cellulaires. Analyse globale et analyse sur variétés, Topology. Manifolds and cell complexes. Global analysis and analysis on manifolds, Analyse globale, analyse sur des variétés, Global analysis, analysis on manifolds, Probabilités et statistiques, Probability and statistics, Théorie des probabilités et processus stochastiques, Probability theory and stochastic processes, Processus de markov, Markov processes, Statistiques, Statistics, Inférence à partir de processus stochastiques; analyse des séries temporelles, Inference from stochastic processes; time series analysis, Applications, Assurances, économie, finance, Insurance, economics, finance, Analyse donnée, Data analysis, Análisis datos, Analyse numérique, Numerical analysis, Análisis numérico, Bootstrap, Bourse valeurs, Stock exchange, Bolsa valores, Comportement asymptotique, Asymptotic behavior, Comportamiento asintótico, Distribution statistique, Statistical distribution, Distribución estadística, Donnée financière, Financial data, Datos financieros, Donnée économique, Economic data, Dato económico, Echantillonnage, Sampling, Muestreo, Econométrie, Econometrics, Econometría, Estimation non paramétrique, Non parametric estimation, Estimación no paramétrica, Estimation statistique, Statistical estimation, Estimación estadística, Finance, Finanzas, Loi conditionnelle, Conditional distribution, Ley condicional, Mesure information, Information measure, Medida información, Méthode Monte Carlo, Monte Carlo method, Método Monte Carlo, Méthode jackknife, Jackknife method, Método jackknife, Méthode rééchantillonnage, Resampling method, Méthode statistique, Statistical method, Método estadístico, Méthode stochastique, Stochastic method, Método estocástico, Prix, Price, Precio, Processus Markov, Markov process, Proceso Markov, Processus stochastique, Stochastic process, Proceso estocástico, Simulation, Simulación, Temps continu, Continuous time, Tiempo continuo, Test hypothèse, Hypothesis test, Test hipótesis, Test non paramétrique, Non parametric test, Prueba no paramétrica, Test statistique, Statistical test, Test estadístico, Théorie approximation, Approximation theory, Théorie information, Information theory, Teoría información, Théorie statistique, Statistical theory, Teoría estadística, 58A25, 60J05, 60J99, 62B10, 62E17, 62F05, 62F40, 62M02, 62M05, 62P05, 65C05, Echantillon fini, Finite sample, Estimation paramétrique, Indépendance conditionnelle, Conditional independence, Sciences actuarielles, Bid-ask spread; Conditional independence; Duration; Nonparametric testing; U-statistic, C14; C52; G10; G19
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Faculdade de Economia, Universidade Nova de Lisboa, Rua Marqués de Fronteira, 20, 1099-038 Lisbon, Portugal
Economics Department, Queen Mary, University of London, Mile End Road, E1 4NS, London, United Kingdom
ISSN:
0304-4076
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=19153134
Rights:
Copyright 2007 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Mathematics
Accession Number:
edscal.19153134
Database:
PASCAL Archive

Further Information

This paper develops a framework to nonparametrically test whether discrete-valued irregularly spaced financial transactions data follow a 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 the irregular spacing that characterizes transactions data. Under such an observation rule, the current price duration is independent of a previous price duration given the previous price realization. A simple nonparametric test then follows by examining whether this conditional independence property holds. Monte Carlo simulations suggest that the asymptotic test has huge size distortions, though a bootstrap-based variant entails reasonable size and power properties in finite samples. As for an empirical illustration, we investigate whether 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. We robustly reject the Markov assumption for two out of the five stocks under scrutiny. Finally, it is reassuring that our results are consistent with two alternative measures of asymmetric information.