This paper applies a non- and a semiparametric copula-based approach to analyze the first-order autocorrelation of returns in high frequency financial time series. Using the EUREX D3047 tick data from the German stock index, it can be shown that the temporal dependence structure of price...

<heading id="h1" level="1" implicit="yes" format="display">Abstract</heading>I analyze the dynamic trading behavior of market participants by developing a bivariate modeling framework for describing the arrival process of buy and sell orders in a limit order book. The model contains an extended autoregressive conditional duration model with a flexible generalized...

This paper introduces a new bivariate autoregressive conditional framework (ACD×ACL) for modelling the arrival process of buy and sell orders in a limit order book. The model contains two dynamic components to describe the observed clustering of durations and order types: a duration process to...

This paper applies a non- and a semiparametric copula-based approach to analyze the first-order autocorrelation of returns in high frequency financial time series. Using the EUREX D3047 tick data from the German stock index, it can be shown that the temporal dependence structure of price...

This paper focuses on the liquidity of electronic stock markets applying a sequential estimation approach of models for volume duration with increasing threshold values. A modified ACD model with a Box-Tukey transformation and a flexible generalized beta distribution is proposed to capture the...

This paper introduces a new bivariate autoregressive conditional framework (ACD×ACL) for modelling the arrival process of buy and sell orders in a limit order book. The model contains two dynamic components to describe the observed clustering of durations and order types: a duration process to...

Purpose – Algorithmic trading attempts to reduce trading costs by selecting optimal trade execution and scheduling algorithms. Whilst many common approaches only consider the bid-ask spread when measuring market impact, the authors aim to analyse the detailed limit order book data, which has...

This paper suggests a dynamic copula approach that allows more flexibility in capturing duration clusters of ultra-high frequent order book data. The proposed framework involves a time-varying mixing parameter and does not only model (a) the degree of dependence of consecutive durations, but...