Three essays on addiction and the real estate market.

Summary A large number of home loan defaults and the collapse of the housing market led to the failure of several investment banks in the United States. These factors also triggered the latest financial crisis. These events have given rise to a body of work that seeks to explain the factors determining the simultaneous failures of real estate lending. This thesis provides additional evidence of the importance of default dependence in the management of real estate loan portfolios. This thesis consists of three chapters identifying the key factors determining the dependence of home loan defaults and home prices. We show that a more accurate measure of credit risk is possible by taking into account the factors mentioned below. In chapter 1, we analyze the variation in the dependence of 13 regional price indices. We estimate a multivariate hidden Markov chain with two equidistant regimes. We model the transition probability using the growth of the interest rate and the loan-to-value ratio. Our results show that the average regional dependence of house prices varies over time. Moreover, this trend is related to changes in the interest rate and the loan-to-value ratio. Considering a subsample of metropolitan regions, we also show that a decrease in the loan-to-value ratio is associated with a higher probability of being in a high-dependence regime as described by a canonical tree copula. In Chapter 2, we use a composite likelihood copula and a mathematical function to analyze the pairwise default dependence of a set of securitized subprime mortgages from the Los Angeles area between 2000 and 2011. Our results show that default dependence is affected by the geographic distance between loans, the mean, and the dyadic differences in variables such as loan-to-value ratio, FICO credit scoring, and income at the borough level. In addition, we identify a contagion effect or a negative regional house price change index and a high default rate increases default dependence. Finally, our model gives a good estimate of the Value at Risk of the number of defaults in a block of securitized loans. In chapter 3, we analyze the efficiency of a portfolio of subprime mortgages. We estimate the spread and variance of returns using default probabilities obtained from a pairwise default dependence model. We analyze the 13 largest blocks of real estate loans, securitized between 2001 and 2005. Our results show that the diversification of loan blocks was not optimal. Moreover, we show that it is possible to further reduce the risk associated with loan pools by taking into account non-geographic risks.