Optimization and statistical methods for high frequency finance

Optimization Methods in Finance

Spectral Analysis of High-Frequency Finance

Popular across a wide range of fields, spectral analysis is a powerful technique for studying the behavior of complex systems. It decomposes a signal into many different periodic components, each associated with a specific cycle length. We argue that the application of spectral analysis to finance leads to natural interpretations in terms of horizon-specific behaviors. A spectral framework prov...

The Event Calculus on High-frequency Finance

Edward Tsang has a first degree in Business Administration (Major in Finance) and a PhD in Computer Science. He has broad interest in applied artificial intelligence, in particularly computational finance, heuristic search, constraint satisfaction and scheduling. He is currently a professor in computer science at the University of Essex where he leads the Computational Finance Group and Constra...

Special Issue on Statistical and Computational Methods in Finance

In recent decades major developments in computational methods allowed revolutionary changes to take place in the statistical and econometric analysis of financial processes. Evaluating various forecasts and policy scenarios with their implied risk using advanced computational techniques and modern financial models is becoming more and more standard practice. The contents of this special issue r...

Dependence Structures for Multivariate High–Frequency Data in Finance

Stylised facts for univariate high–frequency data in finance are well–known. They include scaling behaviour, volatility clustering, heavy tails, and seasonalities. The multivariate problem, however, has scarcely been addressed up to now. In this paper, bivariate series of high–frequency FX spot data for major FX markets are investigated. First, as an indispensable prerequisite for further analy...