why is multicollinearity a problem 
multicollinearity is a problem because it produces regression model results that are less reliable this is due to wider confidence intervals larger standard errors that can lower the statistical significance of regression coefficients in stock analysis it can lead to false impressions or assumptions about an investment the bottom linemulticollinearity exists whenever an independent variable is highly correlated with one or more of the other independent variables in a multiple regression equation multicollinearity is a problem because it will make the statistical inferences less reliable however the variance inflation factor vif can provide information about which variable or variables are redundant and thus the variables that have a high vif can be removed 