ABSTRACTThe CBOE VIX index is a widely recognised benchmark measure of expected stock market volatility. As shown in the literature, probability distributions other than Gaussian are key features required to describe the dynamics of the S&P 500, the variable that ultimately determines the VIX index level. As such, it is important to assess if deviations from the Gaussian distribution have important impacts on the VIX index level. We examine herein how a model articulated over a time‐varying non‐Gaussian distribution with conditional skewness and kurtosis can contribute to the overall explanation of the VIX dynamics.