Quantitative Risk Analysis Flashcards
7 cards from real CRA practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Quantitative Risk Analysis flashcards as text
What is 'model risk' in the context of quantitative risk analysis?
Answer: The risk that a quantitative model produces incorrect outputs due to flawed assumptions or errors
Model risk arises when a model's assumptions, logic, or implementation are incorrect, leading to inaccurate risk estimates and poor decisions.
A copula function in risk modeling is used primarily to:
Answer: Model the dependence structure between random variables independently of their marginals
Copulas capture the joint dependence structure between variables while allowing separate modeling of each variable's marginal distribution.
In risk-adjusted performance measurement, RAROC is calculated as:
Answer: Risk-adjusted return divided by economic capital
RAROC (Risk-Adjusted Return on Capital) = Risk-adjusted net income / Economic capital, used to compare performance across business units on a risk basis.
In decision tree analysis for risk, a 'risk-neutral' decision maker selects the branch with:
Answer: The highest expected monetary value (EMV)
A risk-neutral decision maker maximizes expected monetary value without a preference for or against variance.
Which statistical test is commonly used to assess whether observed loss data fits a hypothesized parametric distribution?
Answer: Kolmogorov-Smirnov (K-S) test
The K-S test compares the empirical cumulative distribution function of the data to the theoretical CDF of the hypothesized distribution.
Stress testing in quantitative risk analysis differs from scenario analysis primarily because stress testing:
Answer: Applies extreme but plausible shocks to risk factors to assess resilience under adverse conditions
Stress testing subjects portfolios or processes to severe adverse conditions to identify vulnerabilities, while scenario analysis explores a broader range of defined situations.
A risk architect observes that two risk factors have a Pearson correlation of 0.85 in normal conditions but move in tandem almost perfectly during market crises. This phenomenon is known as:
Answer: Tail dependence
Tail dependence describes the tendency of variables to become more strongly correlated in the tails of their joint distribution, particularly during extreme events.