Explanation
The VaR of a fixed income instrument is given by Duration x Volatility of the interest rate x z-factor corresponding to the confidence level. Therefore as the volatility of the yield goes up, the value at risk for the instrument goes up.
At the same time, the value of the bond is given by the present value of its future cash flows using the current yield curve. This value is unaffected by the volatility of the underlying interest rates. Therefore a change in volatility of interest rates does not affect the value of the bond.
Therefore Choice 'd' represents the correct answer.

Explanation
This is easy to calculate as follows: At the 99% confidence level, the VaR=2.326 * Std Deviation (remember the z values at the 95% and 99% levels, the PRMIA exam may not give you these values). Thus the 1-day standard deviation is $250m/2.326, and the 250-day standard deviation is 250 * ($250m/2.326) = $1,699.4m.
Remember: if you know the VaR, you know the standard deviation. Once you know the standard deviation for any period of time, you can convert it into standard deviation for another period using the square root of time rule. You can also calculate the VaR at a different confidence level too.

Explanation
Some risk experts have suggested the use of extreme value theory to model tail risk or extreme events for operational risk. The generalized Pareto model or the Peaks-over-Threshold (POT) model are often used to model extreme value distributions, and therefore Choice 'a' is the correct answer.

Explanation
Rating agencies target both accuracy and stability when they assign ratings. These two objectives can sometimes conflict, so a balance needs to be struck between the two. Rating agencies do not target any particular 'accuracy ratio' or rankings. Therefore Choice 'c' is the correct answer.