Let me start off by saying that I am truly happy you are reading this e-book right now. Whether it be by sheer luck or destiny of some kind, I am ecstatic that your Internet travels somehow led you to these words that you are reading at this moment. It means that one more person has been saved!
One more fat loss hopeful will finally get their hands on the information they truly require to reach their goals, rather than being sucked down the rabbit hole of the money-hungry marketers looking to expand their bank accounts by flogging the latest miracle breakthrough.
Information problems have long been at the fore of analyses of credit markets. Indeed, one rationale for banks is as institutions to gather information and establish relationships with borrowers in an effort to surmount these problems. A striking feature of banks is the plethora of services that they offer and the economies of scope between them. For example, accounts and payments’ services provide valuable data to the bank on the creditworthiness of clients as potential borrower.
A limited number of papers have focused on whether banks should share information. Jappelli and Pagano (1993), in a model with adverse selection, show that exchanging information on borrower type decreases default rates and reduces average interest rates. In a related paper, Padilla and Pagano (1997) show that information sharing among borrowers would lead to lower interest rates and increased lending. There is also a growing body of empirical evidence that suggests that the existence of credit information sharing is associated with deeper credit markets. Barron and Staten (2003), Kalberg and Udell (2003) and Cowan and de Gregorio (2003) all suggest there is value in the existence of private credit bureau reporting services.
Monte Carlo simulation and a semi-analytical method are used to value a basket default swap and an homogeneous Collateralized Debt Obligation (CDO). The semi-analytical technique is based on the one factor copula model proposed by J.P. Laurent and J. Gregory [1]. We study the properties of a CDO with Monte Carlo and compare the spread calculation with the one obtained by the factor model.
In the last twenty years one of the main innovations in the field of Finance has been securitization. This is the process of pooling together a portfolio and issuing liability and equity notes backed by this pool of assets. It started in the late 1970s with mortgages backed securities and it has expanded to other instruments like credit card debt, student and car loans, junk bonds, etc. Its main purpose for the originator is to transfer some of the risk to the investors and to free up regulatory capital. The main advantage for the investors is diversification: they are able to invest in products that they would not have access otherwise.
