AbstractThose empirical properties exhibited by high frequency financial data, such as time-varying intensities and self-exciting features, make it a challenge to model appropriately the dynamics associated with, for instance, order arrival. To capture the microscopic structures pertaining to limit order books, this paper focuses on modeling high frequency financial data using Hawkes processes. Specifically, the model with power-law kernels is compared with the counterpart with exponential kernels, on the goodness of fit to the empirical data, based on a number of proposed quantities for statistical tests. Based on one-trading-day data of one representative stock, it is shown that Hawkes processes with power-law kernels are able to reproduc...
none3siWe show that multivariate Hawkes processes coupled with the nonparametric estimation procedur...
This thesis focuses on the statistical modeling of the dynamics of limit order books in electronic e...
The vast amount of information characterizing nowadays’s high-frequency financial datasets poses bot...
Those empirical properties exhibited by high frequency financial data, such as time-varying intensit...
AbstractThose empirical properties exhibited by high frequency financial data, such as time-varying ...
Compared with low frequency data, high frequency data exhibit distinct empirical properties, includi...
We study statistical aspects of state-dependent Hawkes processes, which are an extension of Hawkes p...
In this paper, we focus on the high frequency dynamics of limit order flow and market order flow. We...
International audienceHigh-dimensional Hawkes processes with exponential kernels are used to describ...
The quality of various Hawkes-process-based order book models are assessed using some objectivecrite...
International audienceHawkes processes provide a natural framework to model dependenciesbetween the ...
Because of their tractability and their natural interpretations in term of market quantities, Hawkes...
We test three common information criteria (IC) for selecting the order of a Hawkes process with an i...
International audience<p>In this work, we adopt Spread constrained Limit Order Book Hawkes Process (...
International audienceIt has been suggested that marked point processes might be good candidates for...
none3siWe show that multivariate Hawkes processes coupled with the nonparametric estimation procedur...
This thesis focuses on the statistical modeling of the dynamics of limit order books in electronic e...
The vast amount of information characterizing nowadays’s high-frequency financial datasets poses bot...
Those empirical properties exhibited by high frequency financial data, such as time-varying intensit...
AbstractThose empirical properties exhibited by high frequency financial data, such as time-varying ...
Compared with low frequency data, high frequency data exhibit distinct empirical properties, includi...
We study statistical aspects of state-dependent Hawkes processes, which are an extension of Hawkes p...
In this paper, we focus on the high frequency dynamics of limit order flow and market order flow. We...
International audienceHigh-dimensional Hawkes processes with exponential kernels are used to describ...
The quality of various Hawkes-process-based order book models are assessed using some objectivecrite...
International audienceHawkes processes provide a natural framework to model dependenciesbetween the ...
Because of their tractability and their natural interpretations in term of market quantities, Hawkes...
We test three common information criteria (IC) for selecting the order of a Hawkes process with an i...
International audience<p>In this work, we adopt Spread constrained Limit Order Book Hawkes Process (...
International audienceIt has been suggested that marked point processes might be good candidates for...
none3siWe show that multivariate Hawkes processes coupled with the nonparametric estimation procedur...
This thesis focuses on the statistical modeling of the dynamics of limit order books in electronic e...
The vast amount of information characterizing nowadays’s high-frequency financial datasets poses bot...