Value at Risk (VaR) and Expected Shortfall are quantitative risk metrics that estimate how much a portfolio could lose over a given period under normal market conditions, and how severe that loss could get if things go worse than expected. Both are widely used to stress test crypto portfolios, which behave very differently from traditional assets during periods of stress.
Why standard deviation falls short
Traditional risk models often assume returns follow a normal bell curve, but crypto returns have fat tails and a pronounced negative skew, meaning extreme moves happen far more often than a normal distribution would predict. Standard deviation alone smooths over that reality and understates how bad a flash crash or a cascading liquidation event can actually get.
VaR versus expected shortfall
VaR gives you a threshold: the loss level you'd expect to see exceeded only 5% of the time, for example. What it doesn't tell you is how bad things get once that threshold is actually breached. Expected Shortfall, also called Conditional VaR, fills that gap by averaging the losses across only the worst 5% (or 1%) of scenarios, giving a clearer picture of tail risk. Because of this, many risk managers treat CVaR as the more meaningful number when sizing how much capital to hold in reserve against a genuinely bad outcome.
Running a practical stress test
A useful starting point is running historical simulations against real data from past market panics, such as the March 2020 crash, the May 2021 liquidation event, or the November 2022 collapse following FTX. It's also worth calculating correlation coefficients between the assets in a portfolio, since correlations that look manageable in calm markets tend to converge toward 1.0 during a genuine panic, which erases the diversification benefit right when it's needed most. Holding cash or short-term Treasury reserves sized to cover the calculated Expected Shortfall gives a portfolio a buffer against exactly the kind of drawdown the model is built to anticipate.