Testing the Markov Property With Ultra-High Frequency Financial Data

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 level. This framework is convenient for it accommodates not only the irregular spacing of transactio...

Testing the Markov property with high frequency data

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 characterize...

Financial econometric analysis at ultra-high frequency: Data handling concerns

Data collection at ultra high-frequency on financial markets requires the manipulation of complex databases, and possibly the correction of errors present in the data. The New York Stock Exchange is chosen to provide evidence of problems affecting ultra high-frequency data sets. Standard filters can be applied to remove bad records from the trades and quotes data.A method for outlier detection ...

Spectral Densities of Ultra - high Frequency Data

This paper suggests the application of advanced methods from Fourier Analysis in order to describe ultra-high frequent data in limit order books. Using Lomb’s normalized periodogram and Scargle’s Discrete Fourier Transforms to take account of the irregularity in spacing, the power spectra of different time series processes can be easily estimated, without immense computational effort caused by ...

Analysis of High Frequency Financial Data