# Tools for Cryptocurrency Portfolio Risk Management - Part 2

Dec 20225 mins
|
Knowledge Bank

## Review

In our previous portfolio risk management article (read here) we reviewed several VaR (Value-at-Risk) models & their applicability in the crypto trading space. While our view is that VaR is a useful tool in a crypto portfolio risk management toolbox, it is by no means the only tool. In this article, we will examine several other complementary risk tools the author has used in practice, namely Expected Shortfall, Stressed VaR & Bespoke Stress Scenarios.

## Expected Shortfall (ES)

One of VaR’s weaknesses is the inability to capture “tail risk”. An alternative metric (ES) has therefore emerged, which measures the riskiness of a position by considering both the size & the likelihood of losses beyond a certain confidence level. In a nutshell, think of ES as the expected value of these losses beyond a given confidence level. So while we understand that VaR is the loss that is expected to be exceeded (100 - X) % of the time in N days for specified parameter values (X & N), ES is the expected loss conditional that the loss exceeds VaR. For example, if X = 99% & N = 1 day, ES is the average amount that the portfolio loses over a 1-day period when the loss is (already) in the 1% tail of the distribution.

## Stressed VaR (SVaR)

In practice, both volatilities & correlations of the cryptocurrencies in the portfolio need to be stressed, taking into account historical moves as a sanity check. Increasing the assumed volatilities is the easy part and has the effect of lengthening the tails of the gaussian (normal) loss distributions underlying the VCV VaR calculation. The 2nd step – stressing the correlation matrix – is trickier. In volatile periods correlations typically approach 1.0 (ex. 1987, 1998, 2008), which is known as “tail contagion”. Note when stressing the correlation matrix, the VaR calculator requires the matrix to satisfy the mathematical property of positive definiteness which simply means that the correlations need to be internally consistent with each other.

The photo above is from (GARP)