In this paper, we have investigated artificial neural networks based prediction modeling of foreign currency rates using three learning algorithms, namely, Standard Backpropagation (SBP), Scaled Conjugate Gradient (SCG) and Backpropagation with Bayesian Regularization (BPR). The models were trained from historical data using five technical indicators to predict six currency rates against Austra...

For foreign currency exchange rates, multi-affine analysis can put quantitatively into evidence the differences between correlated (daily closing market) values and random walks in time dependent data. The H(q) spectrum is presented and discussed here for the USD/DEM and JPY/USD exchange rates. The time-evolution of these ratios is found to be multi-affine. The h(γ)-curve describing the hierarc...

This paper uses Reuters high-frequency exchange rate data to investigate the contributions to the price discovery process by individual banks in the foreign exchange market. We propose multivariate time series models in calendar time as well as in tick time to study the dynamic relations between the quotes of individual banks. We investigate the hypothesis that German banks are price leaders in...