Value at Risk (VaR) Calculator

Value at Risk (VaR) measures maximum expected loss at given confidence level over time horizon. 100k portfolio with 95% 1-day VaR of 2,000 means: 95% of days portfolio loses less than 2,000 (or 5% of days exceed 2,000 loss). Used by banks (Basel regulations require VaR reporting), hedge funds, traders for risk budgeting.

Example: 1M portfolio, 8% expected return, 15% volatility. 95% 1-year VaR = 166,000. Means: 95% confident annual loss won't exceed 166k. 5% of years could lose more. 99% VaR more conservative (269k). Time horizon and confidence level both increase VaR - longer + more confident = bigger expected worst case.

VaR limitations: assumes normal distribution (real markets have fat tails - extreme events more common than normal predicts). Doesn't capture loss magnitude beyond threshold (5% worst case could be -10% or -90% - VaR doesn't say). Stress tests and Expected Shortfall (CVaR) better for tail risk. Use VaR for routine risk budgeting, scenario analysis for tail events. Both Basel III banking regulations and most institutional risk frameworks now include VaR + stress testing.

Quick example

With portfolio value of 1,000,000 and expected annual return of 8% (plus annual volatility of 15% and confidence level of 95%), the result is 166,750.00. Change any figure and watch the output shift — it's often more useful to see the pattern than to memorise the formula.

Which inputs matter most

You enter Portfolio Value, Expected Annual Return %, Annual Volatility %, Confidence Level %, and Time Horizon (days). Not every input has equal weight. Adjusting one input at a time toward extreme values shows which ones move the result most.

What's happening under the hood

Parametric VaR using normal distribution. Z-score scaled by horizon volatility minus expected return. The formula is listed in full below. If the number looks off, you can retrace the calculation by hand — that's the point of showing the working.

Why run this

Running the numbers makes the trade-offs concrete. Small changes in the inputs can move the result more than intuition suggests, which is hard to judge without working it out.

What this doesn't capture

This is a simplified model that holds its assumptions constant. Real outcomes vary with market conditions, costs, taxes, and timing, so the figure is best read as one scenario rather than a forecast.