Show how exposure measures for equities, fixed income, and options can help gauge and control market risk and volatility risk
The idea
For equities, beta times the market return gives the expected return on the position. For bonds, the percentage price change is approximately −modified duration × Δy + ½ × convexity × (Δy)². For options, delta is the value change per unit move in the underlying, gamma the change in delta, and vega the value change per point of implied volatility, so ΔV ≈ delta × ΔS + ½ × gamma × (ΔS)² + vega × Δσ. A delta-hedged book removes first-order price risk but keeps gamma and vega exposure. The trap in calculations is forgetting to square the change in the convexity or gamma term, or dropping the one-half.
In the app: 2 practice questions on this outcome, a narrated walkthrough with diagrams, spaced review that brings it back before you forget it.
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- Explain how value at risk (VaR) is applied to gauge the risk of a portfolio
- Contrast three ways to estimate VaR: Monte Carlo simulation, historical simulation, and the parametric (variance–covariance) method
- Estimate VaR by Monte Carlo simulation, by historical simulation, and by the parametric method, and explain what each result means
- Set out the strengths and weaknesses of VaR
- Set out the ways VaR has been extended
- Explain sensitivity and scenario risk measures and weigh them against VaR
- Set out how sensitivity and scenario risk measures are applied
- Set out the strengths and weaknesses of sensitivity and scenario risk measures
- Explain the limits used to control market risk, among them stop-loss limits, scenario limits, position limits, and risk budgeting
- Explain how risk measures can guide decisions on allocating capital
- Set out the risk measures relied on by insurers, pension funds, asset managers, and banks