Experimental investigation of the efficiency of universal measures based forecasting methods

We describe and experimentally investigate a method to construct forecasting algorithms for stationary and ergodic processes based on universal measures (or so-called universal data compressors). Using the time series of solar activity indices as a research target, we show that the quality of the predictions is higher than that of known methods forecasts.