Value at Risk (VaR) - Notes

Value at Risk (VaR)

1. Definition

Value at Risk (VaR) is a statistical risk measure that estimates the maximum potential loss in the value of a portfolio over a specific time horizon at a given confidence level.

Example: “1-day VaR of $2.5 million at 95% confidence” means there is a 5% chance the portfolio will lose more than $2.5 million in a single day.

2. Where to use VaR

  • Banks & Financial Institutions – trading book risk, capital requirements.
  • Investment Funds – portfolio risk reporting to investors.
  • Corporate Risk Management – FX, commodities, interest rate exposures.
  • Regulators (Basel, RBI, SEC) – capital adequacy norms.

3. Assumptions

  1. Returns follow a normal distribution.
  2. Markets remain stable (no extreme shocks).
  3. Past price data represents future risks.
  4. Short time horizon (usually 1–10 days).

4. Numerical Example

Portfolio Value = $100 million
Daily Volatility (σ) = 2% = $2 million
Confidence Level = 95% (Z = 1.65)

VaR = Z × Ïƒ × Portfolio Value
VaR = 1.65 × 2,000,000 = $3.3 million

Interpretation: With 95% confidence, the maximum 1-day loss will not exceed $3.3 million. There is a 5% chance the loss could be higher.

5. What VaR Tells Us

  • Maximum loss at a chosen confidence level and horizon.
  • Comparable single number to express risk.
  • Useful for capital reserve estimation.

6. What VaR Does Not Tell Us

  • Does not measure losses beyond the confidence interval.
  • Ignores tail risk (extreme crisis events).
  • Heavily dependent on historical data.

7. Pros

  • Simple and intuitive – one number.
  • Standardized across institutions.
  • Flexible across assets and time horizons.
  • Regulatory acceptance (Basel norms).

8. Cons

  • Ignores extreme tail events.
  • Assumes normal distribution (often unrealistic).
  • Relies on historical data (backward-looking).
  • Not additive across portfolios.
Quick Recap:
VaR = “At X% confidence, maximum loss over Y horizon is Z.”
✅ Good for: risk measurement, reporting, regulation.
❌ Weak in: crises, tail risk, systemic shocks.

Post a Comment

Previous Post Next Post