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Expected Shortfall (ES) is a parameter that indicates the potential loss that can be expected on a particular asset in a situation where an event occurs beyond the standard probability measure (Value at Risk).

The Expected Shortfall indicator shows the potential loss that will be generated on a particular asset in a specified time period if the VaR (Value at Risk) level is exceeded.

A VaR 95% indicator within a 15% range means that there is a 95% chance that the potential loss will not exceed the 15% level. Therefore, most of the time, the VaR indicator is sufficient to estimate the level of risk in a given asset or portfolio.

However, what happens when those 5% of cases occur where the loss exceeds the 15% level? How much loss can be expected then? Will it be 16%, 26%, or maybe 56%? This is where the Expected Shortfall indicator comes in handy.

Therefore, ES should be understood as information about the potential loss that can be expected if it already exceeds the standard level defined by 95% probability.

A monthly Expected Shortfall 95% parameter at a 20% level will mean that if those 5% of cases occur where the loss exceeds the VaR level, there is a 95% chance that the loss will not exceed the 20% level.

**Example:**

The ES indicator should be used in conjunction with the VaR parameter and should be treated as information about what an investor can expect in the worst-case scenario when VaR levels have already been breached.

For example, let's assume that Company XYZ has a monthly VaR 95% indicator at a 15% level and the same ES indicator at a 20% level.

This situation should be interpreted as follows: there is a 95% chance that the monthly loss on XYZ stocks will not exceed 15%, but if something unpredictable happens and the loss exceeds the assumed level, then in those 5% of cases, there is a further 95% chance that the following loss will not exceed 20%.

Therefore, the Expected Shortfall indicator is often used by investors when conducting stress tests on their portfolio. By combining ES and VaR, it is possible to determine with reasonable accuracy what losses an investor can expect within a specified time frame with a specific probability.

This knowledge provides a basis for reacting in advance and adjusting those risk levels according to one's preferences.

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