Using Recurrent Neural Networks To Forecasting of Forex

This paper reports empirical evidence that a neural networks model is applicable to the statistically reliable prediction of foreign exchange rates. Time series data and technical indicators such as moving average, are fed to neural nets to capture the underlying "rules" of the movement in currency exchange rates. The trained recurrent neural networks forecast the exchange rates between American Dollar and four other major currencies, Japanese Yen, Swiss Frank, British Pound and EURO. Various statistical estimates of forecast quality have been carried out. Obtained results show, that neural networks are able to give forecast with coefficient of multiple determination not worse then 0.65. Linear and nonlinear statistical data preprocessing, such as Kolmogorov-Smirnov test and Hurst exponents for each currency were calculated and analyzed.Comment: 23 pages, 13 figure

Benchmark calculation for proton-deuteron elastic scattering observables including Coulomb

Two independent calculations of proton-deuteron elastic scattering observables including Coulomb repulsion between the two protons are compared in the proton lab energy region between 3 MeV and 65 MeV. The hadron dynamics is based on the purely nucleonic charge-dependent AV18 potential. Calculations are done both in coordinate space and momentum space. The coordinate-space calculations are based on a variational solution of the three-body Schr\"odinger equation using a correlated hyperspherical expansion for the wave function. The momentum-space calculations proceed via the solution of the Alt-Grassberger-Sandhas equation using the screened Coulomb potential and the renormalization approach. Both methods agree within 1% on all observables, showing the reliability of both numerical techniques in that energy domain. At energies below three-body breakup threshold the coordinate-space method remains favored whereas at energies higher than 65 MeV the momentum-space approach seems to be more efficient.Comment: Submitted to Phys. Rev.