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Credit Risk Transfer, Credit Loss Models and Real Estate Valuations

—Credit risk is a perennial topic in the estate evaluation area. This work is a complement for the existing three credit losses estimating models PD(probability of default), LGD(loss given default) and EAD(exposure at default) since these three models cannot provide the insights from a behavioral perspective. Compared to the three existing models, this research derives the credit loss part of the unpaid principal balance of the mortgage from the forecast of agent behaviors. In real estate finance, default and prepayment risks are the most commonly types of credit risk to be considered from the lender perspective. Default risk of the former usually comes from high debt-to-income ratio, high loan-to-value ratio and bad credit history. Prepayment risk is risk with the premature return of principal on a mortgage. Lenders would add prepayment penalty to the real estate price to take care of this risk. In the event of prepayment, the loan is shortened, and the lender fail to collect future interest. This project studies how to model real estate value losses from the advent of credit events like default and prepayment. The study models the probability, intensity and severity of the credit risk as well as size of the impact.