CFM Risk Assessment & Asset Allocation 3 — Questions and Answers
Question 1: The Black-Litterman model improves upon traditional mean-variance optimization primarily by:
- Eliminating the need for a covariance matrix
- Combining market equilibrium returns with investor views (Correct answer)
- Using only historical returns to estimate expected returns
- Restricting portfolios to long-only positions
Correct answer: Combining market equilibrium returns with investor views
Black-Litterman blends implied equilibrium returns (from market cap weights) with manager-specific views, producing more stable and intuitive portfolio allocations.
Question 2: A fund manager uses a strategic asset allocation of 60% equity / 40% bonds. After a strong equity rally, the portfolio drifts to 70/30. Rebalancing back to 60/40 is an example of:
- Tactical asset allocation
- Dynamic hedging
- Disciplined risk management that sells winners and buys underperformers (Correct answer)
- Momentum investing
Correct answer: Disciplined risk management that sells winners and buys underperformers
Rebalancing restores target risk exposure by trimming outperforming assets and adding to underperforming ones, maintaining the intended risk profile.
Question 3: Which of the following best describes liquidity risk in asset allocation?
- The risk that interest rates rise and bond prices fall
- The risk of being unable to sell an asset quickly at fair value (Correct answer)
- The risk of counterparty default on a derivative contract
- The risk that inflation erodes real returns
Correct answer: The risk of being unable to sell an asset quickly at fair value
Liquidity risk is the potential inability to exit a position without significantly impacting the asset's price or incurring excessive transaction costs.
Question 4: An investor's risk tolerance is best described as:
- The maximum drawdown they have experienced historically
- The level of portfolio volatility they can financially and emotionally sustain (Correct answer)
- Their target Sharpe ratio
- The percentage of their portfolio in equities
Correct answer: The level of portfolio volatility they can financially and emotionally sustain
Risk tolerance encompasses both the financial capacity to absorb losses and the psychological willingness to endure portfolio volatility without making panic decisions.
Question 5: Downside deviation differs from standard deviation in that it:
- Measures volatility above the mean only
- Penalizes only returns that fall below a minimum acceptable return (Correct answer)
- Uses logarithmic returns instead of arithmetic returns
- Excludes outlier observations from the calculation
Correct answer: Penalizes only returns that fall below a minimum acceptable return
Downside deviation focuses only on negative deviations below a threshold (minimum acceptable return), making it more aligned with investor loss aversion.
Question 6: In a liability-driven investing (LDI) framework, the primary risk being managed is:
- Benchmark tracking error
- The mismatch between asset cash flows and liability obligations (Correct answer)
- Equity market beta exposure
- Currency risk from international allocations
Correct answer: The mismatch between asset cash flows and liability obligations
LDI focuses on matching or hedging the interest rate and duration sensitivity of assets to pension or insurance liabilities, minimizing surplus volatility.
Question 7: The Sortino ratio improves on the Sharpe ratio by:
- Using the risk-free rate as a benchmark instead of a market index
- Replacing total volatility with downside deviation in the denominator (Correct answer)
- Adjusting for skewness and kurtosis in return distributions
- Including transaction costs in the return calculation
Correct answer: Replacing total volatility with downside deviation in the denominator
The Sortino ratio uses downside deviation rather than total standard deviation, rewarding funds that have upside volatility without penalizing them for positive return variability.
CFM Risk Assessment & Asset Allocation 3
The Black-Litterman model improves upon traditional mean-variance optimization primarily by: