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L.1 · INTERMEDIATE · 2 MIN

Value at Risk: Three Ways to Measure Worst-Case Losses

Value at Risk answers one question: what is the most I could lose over a given period at a given confidence level? Three methods, three different assumptions, three different answers.

Quiz · 5 questions ↓

Compare

VaR MethodAssumptionStrengthWeakness
ParametricReturns are normally distributedFast, simple calculationUnderestimates tail risk (fat tails)
HistoricalFuture resembles the pastNo distribution assumptionMisses unprecedented events
Monte CarloSimulated return pathsMost flexible, handles complex portfoliosComputationally intensive, model-dependent

Formula

Parametric VaR = Portfolio Value × z-score × σ × √t

Key point

VaR tells you the threshold of a bad day, not how bad it gets. A 95% 1-day VaR of $50K means you expect to lose more than $50K only 5% of the time — but on that 5%, the loss could be $100K, $500K, or worse.

Try it

Calculate the 95% 1-day VaR for your portfolio using the historical volatility of your holdings. Does the number match your risk tolerance?

Check-in

Your 95% daily VaR is $25K. Over 250 trading days, how many days would you expect losses to exceed $25K?

Key insight

VaR is a useful risk summary but a dangerous false comfort. It works well for normal markets but fails precisely when you need it most — during crises when correlations spike and returns are far from normal.

Check-in

A portfolio has 1-day 95% VaR of $100K. What does this number ACTUALLY mean?

Key point

Going Deeper — this module contains a deep-dive on adverse selection and the Akerlof lemons dynamic. It is promoted to its own module: see 'Adverse Selection and Market Unraveling' (risk-1b) in this path.

Check your understanding

Sit with the ideas.

You manage a bond-heavy portfolio. Interest rates have been stable for two years, but you worry about a sudden rate shock. Which VaR method is LEAST appropriate for capturing this risk?

Why:
Continue this lesson in the appAdaptive practice · saves your progress · remediation when you miss

Other lessons in this course.

  1. 01Value at Risk: Three Ways to Measure Worst-Case Losses— reading now
  2. 02Adverse Selection and Market Unraveling
  3. 03Beyond VaR: Expected Shortfall and Tail Risk
  4. 04Portfolio Risk Decomposition: Where Is Your Risk Coming From?
  5. 05Stress Testing and Scenario Analysis
  6. 06Hedging Strategy Selection: When, What, and How to Hedge
  7. 07Risk-Adjusted Returns: Measuring What Matters
  8. 08Behavioral Risk Biases: The Investor's Worst Enemy
  9. 09Jensen's Inequality and Precautionary Saving
  10. 10Stochastic Dominance and Ranking Risky Payoffs
  11. 11The Two-Period Consumption-Savings Model
  12. 12Adverse Selection: Pooling and Separating Equilibria
  13. 13Moral Hazard and Agency Costs
  14. 14Knightian Uncertainty and Ambiguity Aversion
  15. 15Risk Metrics: Sharpe, Beta, and Drawdown
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