This study models and forecasts the evolution of intraday implied volatility on an underlying EUR–USD exchange rate for a number of maturities. To our knowledge we are the first to employ high frequency data in this context. This allows the construction of forecasting models that can attempt...

Purpose – The purpose of this paper is to focus on the empirical dimension of financial integration among the five newest members of the European Monetary Union (Cyprus, Estonia, Malta, Slovakia and Slovenia) and the euro area. The main objective is to study the level and the speed of...

The motivation for this paper is to introduce a hybrid neural network architecture of Particle Swarm Optimization and Adaptive Radial Basis Function (ARBF–PSO), a time varying leverage trading strategy based on Glosten, Jagannathan and Runkle (GJR) volatility forecasts and a neural network...

Three government bond futures contracts and their respective 3-month interest rate futures contracts traded on LIFFE are examined. The data period covers three years of observations, January 1994-December 1996, sampled at half-hourly intervals. Borrowing from the calculation of minimum variance...

ABSTRACT Equity block trade transactions per se directly relate to the valuation of a company's equity capital. These transactions are executed outside the continuous trading system and single price system, and involve trading of large volumes of shares at an agreed price. This paper...

ABSTRACT Should we make financial forecasts? The usual answer looks like Pascal's wager: we don't know whether God exists; who erroneously believes loses nothing, who correctly believes wins everything; who correctly disbelieves, gains nothing, who erroneously disbelieves loses everything....

ABSTRACT A number of studies have explored the sources of the Monday effect, according to which returns are on average negative on Mondays. We contribute to the literature by exploring whether a direct measure of mood explains the Monday effect. In line with psychological literature, a greater...

ABSTRACT In this paper a hybrid genetic algorithm–support vector regression (GA‐SVR) model in economic forecasting and macroeconomic variable selection is introduced. The proposed algorithm is applied to the task of forecasting US inflation and unemployment. GA‐SVR genetically optimizes...

ABSTRACT The aim of this research was to analyse the different results that can be achieved using support vector machines (SVM) to forecast the weekly change movement of different simulated markets. The markets are developed by a GARCH model based on the S&P 500. These simulated markets are...