Crash Metrics: Measuring Risk When Markets Break

Financial markets behave nicely—until they don’t.

Most risk models are built on a dangerous assumption: 

Returns are assumed to be well-behaved, correlations are stable, and diversification works.

But during crashes, all of this collapses.

risk measures designed specifically for extreme market regimes

what happens during stress, panic, and liquidation events

In this blog, we’ll build crash metrics from first principles and see 

how to measure crash exposure using real examples

Why Traditional Risk Metrics Fail in Crashes

“What is the maximum loss over a given time horizon at X% confidence?”

VaR assumes return distributions and correlations remain stable.

Two assets can have the same volatility but 

So diversification disappears exactly when you need it most.

Crash metrics measure how an asset or portfolio behaves during extreme downside market events.

“How bad does this get when markets crash?”

given that the market is already crashing

Before measuring crash exposure, we need a 

Crash = market return in the worst 5% of days

“How much does this asset lose when the market crashes?”

how strongly an asset moves during market crashes

“If the market loses 1%, how much does my asset lose 

When the market crashes, the stock loses 

, even if its volatility looks reasonable in normal times.