A type or method of value at risk (VaR) that assumes the data (used in calculation) follows a normal or Gaussian distribution. This measure of risk is used to quantify the risk of potential losses for a firm/ an investment/ a fund, etc., using normally distributed (Gaussian- distributed) data (of returns). By nature, the Gaussian assumption tends to underestimate the likelihood of large returns and and as such extreme risks (fat tail risks).

Such shortcomings may be reduced or eliminated by another risk measure, known as the Cornish-Fisher VaR (Cornish and Fisher [1938], as it takes into account the third and fourth moments of the return distribution.