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Thus based on the data in the sample an sich (as calculated by a test for normality), it is unlikely that the sample is part of a normal distribution, but we already know it is part of a normal distribution, because it's part of population that is normally distributed.
We show that when returns are approximately log-normally distributed, this measure. forecasts future volatility consistently better than the historical standard deviation. In the markets. we examine, it also forecasts as well or better than the GARCH model.