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• W158775740 abstract "This thesis describes the research into modelling cash ows for ResidentialMortgage Backed Securities (RMBS). RMBS notes are secured by proceeds,interest and principal payments, of the underlying mortgage pool. A transactionis divided into several classes of notes with di�erent risk pro�les, thoughthey all reference to the same underlying assets.The quality or creditworthiness of an RMBS transaction is assessed by creditrating agencies. During the credit crisis substantial losses were su�ered onseveral RMBS notes, sometimes up to the most senior ones. In response, therating agencies downgraded a lot of RMBS transactions, and more importantlythe market questioned the ability of the rating agencies to assess thequality of structured credits. As a consequence pricing RMBS notes becamevery subjective. This forces investors to develop their own pricing modelsinstead of relying on rating agencies. Finally, regulatory supervisors havereacted by requesting more transparency from issuers, resulting in the obligationfor issuers to make available to investors detailed loan-level data onthe underlying mortgage pool. The new regulations gave rise to research onhow to purposefully apply loan-level data to consistently and arbitrage freevalue an RMBS note.In this thesis we develop a model based on loan-level data to forecast thecash ows to the noteholders. This model has a stochastic part, the cashows from the mortgage pool, and a deterministic part, the allocation ofthese cash ows to the noteholders established by the transaction structure.Besides interest payments, default and early repayment are determinants ofthe size and timing of cash ows from the underlying mortgage pool. In thisresearch, both the default and early repayment model are based on survivalanalysis, which allows for the estimation of month-to-month default and earlyrepayment probabilities at a mortgage level. The Cox proportional hazardsmodel adopted is able to incorporate both mortgage speci�c variables andtime-varying covariates relating to the macro-economy. Since both defaultand early repayment can cause a mortgage to be terminated before maturity,these causes are termed 'competing risks'. In this paper we will extend theCox model such that it explicitly accounts for the competing risk setting.We �nd that the probability of default for a mortgage is higher if:� the ratio of loan to foreclosure value is higher;� the borrower has a registered negative credit history;� the ratio of main income to total income associated with the loan ishigher;� there is only one registered borrower;� the income of the borrower is not disclosed to the lender, but to anintermediary.For early repayment, we �nd that the probability of occurrence for a mortgageis higher if:� the ratio of loan to foreclosure value is higher;� the applicant is younger;� the total income of the borrower(s) is lower;� the 3-months Euribor is higher;� it is an interest reset date;� the re�nancing incentive is higher.We obtain a method to estimate the month-to-month default and early repaymentprobabilities for a speci�c mortgage with certain characteristics andage. Monte Carlo simulation is used to compute di�erent realisations of defaultand early repayment for the underlying mortgage pool over the maturityof the RMBS. Finally, the deterministic structure of the notes allows us toderive the corresponding discounted cash ows to the noteholders and estimatea pro�t distribution for an RMBS note.The research resulted in a tool for NIBC to assess the quality of a mortgagepool and employ this information to arbitrage free value a correspondingRMBS note." @default.
• W158775740 created "2016-06-24" @default.
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• W158775740 date "2011-01-01" @default.
• W158775740 modified "2023-09-23" @default.
• W158775740 title "Cash flow modelling for Residential Mortgage Backed Securities: a survival analysis approach" @default.
• W158775740 hasPublicationYear "2011" @default.
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