Forex 24x7

As we are gearing up towards the launch of a real-time day scale forecasting service, I am using the newly developed forecasting figure of merit, Pearson correlation coefficient between the real and predicted logarithmic returns, to make a choice of the operating mode for the test mode of the service. I am taking another look at the dependence of the prediction quality on a day scale on the magnitude of a forecasting parameter nicknamed Fred for two distinct pattern recognition modes, namely that of completely independent analysis of the different exchange rates (so-called Step One), and the one in which the time series for the indvidivual exchange rates are considered jointly in order to utilize potential inter-market patterns (Step Three). Fig.1. Pearson correlation of predicted and actual day-scale logarithmic returns as a function of the forecasting parameter nicknamed Fred. The vertical bands indicate a measure of uncertainty, their boundaries are plus/minus one standard deviation to the points. Back-testing simulations give the forecasing engine no access to the future data, direct or indirect. Significantly positive (and ideally, large) values correspond to quality forecasting. Note that the quantities at different Fred are not quite statistically independent, therefore the error bands should be understood as having to do with the curve at large rather than with individual points.