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46. You are asked by your Chief Risk Officer to evaluate arguments he has heard to switch from VaR to conditional VaR as your firm’ main risk measurement tool. Which of the following arguments is not correct?
a. Conditional VaR is a coherent risk measure in contrast to VaR.
b. Conditional VaR estimated for a confidence level corresponding to one minus the probability of default for the firm’s target rating provides an unbiased measure of the amount of the economic capital required above the firm’s bankruptcy threshold point to achieve the probability of default associated with the firm’s target rating.
c. A low VaR does not mean that the firm will make small losses when VaR is exceeded, but a low conditional VaR means that the firm will make small losses when VaR is exceeded.
d. For the same confidence level, conditional VaR is greater than VaR.
47. Let N be an n×１vector of independent draws from a standard normal distribution, and let V be a covariance matrix of market time-series data. Then, if L is a diagonal matrix of the eigenvalues of V, E is a matrix of the eigenvectors of V, and C’C is the Cholesky factorization of V, which of the following would generate a normally distributed random vector with mean zero and covariance matrix V to be used in a Monte Carlo simulation?
a. NC’CN’
b. NC’
c. E’LE
d. Cannot be determined from data given
48. Realizing the benefits of netting of the counterparty exposure may be challenging because of
a. Differences in rating between the rating agencies.
b. Potential downgrade or withdrawal of the counterparty rating.
c. Cross-product netting.
d. Trades being booked in different jurisdictions.
49. The management of a bank wants to limit the credit loss to a specific sector within 5%. Concentration limit is the maximum loss as a percentage of capital divided by the inverse of the loan loss rate. With an estimated recovery rate of 60%, what should the concentration limit to that sector be as a percentage of capital?
a. 5%
b. 12.5%
c. 8.33%
d. 3%
50. Company A uses a Pareto distribution to model the loss severity of its low-frequency, high-severity operational risk events. A Pareto distribution has the following properties, given parameter and k:
Mean: , for k﹥1
Variance: , for k﹥2
Cumulative distribution function:
After fitting the distribution to historical loss data, the parameters are estimated as k = 2.4,
= 10,000. What is the unexpected loss of a low-frequency, high severity operational risk event at 99% confidence level?
a. 40,703
b. 23,560
c. 50,986
d. 68,129 | 
发表于 2009-3-31 14:33
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