From the table 1, we can see that various measures for forecast accuracy, (RMSE - root mean square error), (MAE - mean square error), (MAPE - mean absolute percentage error), (SMAPE - symmetric mean absolute percentage error) for the financial series in the UK from 2017Q2 to 2019Q1. The scores from table 1 show that the (MSSA) forecasts (including financial big data) are superior to the (SSA) forecasts (not including financial big data). We can observe that forecasts we obtain using (MSSA) for the period 2017Q2 - 2019Q1 (out of the sample forecasts since we use a sample for the forecasting accuracy comparison from 2004Q1 to 2017Q1) for the residential property prices, credit to private non-financial sector, credit share in the GDP in the UK are far superior to the one we obtain using (SSA). Taking into account financial big data improves forecasting accuracy for financial series in the UK. Similar results we observe in the case of the USA (see table 2).