We can see the statistical characteristics of UGAZF by looking at its beta, R-squared, and standard deviation. Its standard deviation is 227.3%, R-squared is 27%, and the beta is 6.23. These are pretty good values for an index. The next step is to look at the performance of UGAZF in terms of volatility.
UGAZF has an R-squared of 27%, a beta of 6.23, and a standard deviation of 227.3%
In a regression, an R-squared is the number of units that change the mean value of the dependent variable for one unit shift in the independent variable. A low R-squared value does not prevent you from drawing important conclusions about a relationship. In fact, small R-squared values can sometimes lead to problems when your prediction interval is narrow.
The R-squared is a measure of the fit between the independent and dependent variables, but does not necessarily mean that the model is good. It also does not tell whether the data and predictions are biased. A low R-squared means that the model is well-fitting, while a high R-squared means that the model is poorly fit.
The R-squared is a measure of the goodness of fit of a linear regression model. It indicates how much of the variation in the dependent variable can be explained by the independent variables, on a scale of 0 to 100%. An R-squared of 0.7 indicates a model can adequately explain the observed data.
R-Squared should be high if a fund is closely tracking an index. The higher the R-Squared, the higher the fund’s risk-adjusted returns will be. However, you should keep in mind that an R-Squared of 27% does not necessarily mean that the fund is better than the index.
R-squared is a measure of the extent to which the benchmark index is explaining the movement of a fund. An R-squared of 100% means that all movements of a fund are explained by the index. This value is also known as the “best fit line” coefficient.