Expected shortfall (CVaR)
Estimate expected shortfall (conditional VaR) — the average loss on the days your Value at Risk is breached — and see how much larger it is than the VaR at the same confidence.
Runs entirely in your browserRuns entirely on your device — nothing you type is sent anywhere. Educational only, and not investment advice.
How to use this calculator
Each step names a control you will find on screen above.
- Portfolio value
The total value at risk; both VaR and ES scale directly with it.
- Annual volatility
The annualised standard deviation of returns, scaled to the horizon by the square root of time.
- Horizon
The number of days over which the potential loss is measured.
- Confidence level
How far into the tail you measure. Higher confidence gives a larger VaR and a larger expected shortfall.
Worked example: A ₹10 lakh portfolio, one day
₹10,00,000 portfolio, 20% annual volatility, one-day horizon, 95% confidence.
What to enter
- Portfolio value
- ₹10,00,000
- Annual volatility
- 20%
- Horizon
- 1 day
- Confidence
- 95%
What it shows you
- 95% VaR
- ≈ ₹20,700
- 95% expected shortfall
- ≈ ₹26,000
- ES above VaR
- ≈ 25%
- 99% expected shortfall
- ≈ ₹33,600
Where this is taught
A calculator gives you a number. These explain what the number means and when it misleads you.
- Technical Analysis10 minExpected shortfall: how bad the bad days really areValue at Risk tells you a bad day happens — expected shortfall tells you how bad. The metric that fills VaR’s dangerous blind spot, why regulators now prefer it, and what it still cannot see.
- Technical Analysis11 minValue at Risk: the loss you should not exceed on a normal dayA single number for how much a portfolio might lose, at a chosen confidence, over a chosen horizon. How VaR is built, what it deliberately hides, and why its blind spot has caused real disasters.
- Technical Analysis13 minMean reversion: trading the rubber bandThe mirror image of trend following — many small wins, rare large losses, and a hit rate that flatters until the day it does not. What makes one work where the other fails.
- Technical Analysis10 minSkewness and kurtosis: why returns aren’t a bell curveVolatility assumes returns follow a neat bell curve. They don’t. How skewness and kurtosis measure the lopsidedness and fat tails that volatility misses — and why the difference is where crashes live.
- Risk & Psychology14 minThe near miss you filed as a successA margin call at 2.40, funds arranged by 2.55, and a position that recovered over the following three weeks. He tells it as a story about holding his nerve. It was a sample from the tail that did not finish, and it is the most valuable thing that happened to him all year.