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P2.T5.109. Credit and default risk analysis of mortgages

David Harper CFA FRM

David Harper CFA FRM
Staff member
AIMs: Define prepayment risk, reasons for prepayment, and the negative convexity of mortgages. Explain credit and default risk analysis of mortgages, including metrics for delinquencies, defaults, and loss severity.


109.1. With respect to the negative convexity of mortgages, each of the following is true EXCEPT:

a. Negative convexity is induced by higher prepayment rates (higher PSAs) associated with lower interest rates
b. Negative convexity is induced by lower prepayment rates (lower PSAs) associated with higher interest rates
c. The lender (or investor in an MBS pass-through) is economically short a call option with strike price equal to the outstanding principal amount
d. From the perspective of the mortgage investor (the long position in mortgage loan/MBS), the negative convexity, while unfavorable at low yields, tends to favorable at higher yields as durations shorten

109.2. Which of the following metrics is the best measure of TURNOVER as a driver of prepayments?

a. Change in the price of single-family homes on a period-over-period basis; i.e., real estate price appreciation
b. Existing home sales for single-family homes as a percentage of the number of such homes owned
c. Dollar volume of refinancing ("refi") transactions as a percentage of outstanding mortgage loan balances
d. The change in the level of the 30-year mortgage rate

109.3. In regard to the credit and default risk of mortgages, EACH of the following is true EXCEPT:

a. Strategic default is when the borrower can afford the monthly payment but voluntarily stops because the combined LTV (CLTV) well exceeds 100%
b. Default is the point where the borrower loses title to the property
c. A low loan-to-value, by definition, protects the lender against losses; i.e., protects against the possibility of non-zero loss severity
d. Evaluating credit risk in the mortgage sector is different than fixed income due to the need to (i) quantify and stratify characteristics of the thousands of loans, (ii) estimate how these attributes will translate into performance, and (iii) calculate returns based on these scenarios.