This paper investigates whether the inclusion of the realized range as regressor in the (E)GARCH volatility equation would add information to the process improving out - of - sample forecasts performance and providing more accurate estimates of the volatility persistence. Sixteen range measures at eleven data frequencies are tested using Brazilian stock market data. Several measures for assessing the improvements in the fits were used including the likelihood ratio test, the persistence percentage de crease, and a formal statistical test for comparing forecasts errors from competing models. We found that for both the GARCH and EGARCH models there are always some realized range type at some frequencies bringing information to the volatility process with considerable persistence reduction.