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...

We propose a nonlinear filter to estimate the time-varying default risk from the term structure of credit default swap (CDS) spreads. Based on the numerical solution of the Fokker–Planck equation (FPE) using a meshfree interpolation method, the filter performs a joint estimation of the...

SUMMARY We model the financial market using a class of agent‐based models in which agents’ expectations are driven by heuristic forecasting rules (in contrast to the rational expectations models used in traditional theories of financial markets). We show that, within this framework, we can...

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 applies a new methodology for modeling order durations of ultra-high-frequency data using copulas. While the class of common Autoregressive Conditional Duration models are characterized by strict parameterizations and high computational burden, the semiparametric copula approach...

This paper presents a novel application of advanced methods from Fourier analysis to the study of ultra-high-frequency financial data. The use of Lomb-Scargle Fourier transform, provides a robust framework to take into account the irregular spacing in time, minimising the computational effort....

This paper discusses the possibility of recovering normality of asset returns through a stochastic time change, where the appropriate economic time is determined through a simple parametric function of the cumulative number of trades and/or the cumulative volume. The existing literature argues...

In this paper, we apply the meshfree radial basis function (RBF) interpolation to numerically approximate zero-coupon bond prices and survival probabilities in order to price credit default swap (CDS) contracts. We assume that the interest rate follows a Cox-Ingersoll-Ross process while the...

This paper introduces an adaptive neuro-fuzzy inference system (ANFIS) for financial trading, which learns to predict price movements from training data consisting of intraday tick data sampled at high frequency. The empirical data used in our investigation are five-minute mid-price time series...