Expected Shortfall (ES) is a risk measure that quantifies the expected loss of an investment in the worst-case scenario, given a confidence interval.
It is often used as a more conservative alternative to Value-at-Risk (VaR) because it accounts for the possibility of extreme losses and provides a more accurate estimate of the expected loss in the worst-case scenario.
To calculate the expected shortfall, follow these two steps:
Estimate the VaR at a given confidence level. VaR is the maximum possible loss that is expected to occur on investment under normal circumstances at a certain confidence level in a given time frame. This can be done using a variety of methods, such as the historical simulation method, variance co-variance method, hybrid method, or monte-carlo simulation method.
Determine ES by calculating the expected loss in the worst-case scenario within the VaR significance level (i.e. 1 - confidence level). The ES is the average loss in the worst-case scenarios, which can be calculated by sorting the losses and taking the average of the worst losses within the significance level.
ES is a useful risk measure because it provides a more accurate estimate of the expected loss in the worst-case scenario and can help financial institutions ensure that they have sufficient capital to cover potential losses. However, it is important to understand that the accuracy of the ES estimate depends on the accuracy of the VaR estimate, the selection of the lookback period, the assumptions involved, and the method used to calculate the same.