We consider a financial market with a stock exposed to a counterparty risk inducing a drop in the price, and which can still be traded after this default time. We use a default-density modeling approach, and address in this incomplete market context the expected utility maximization from terminal wealth. We show how this problem can be suitably decomposed in two optimization problems in complet...

We propose a credit stress testing method that puts together: (1) a bottom-up corporate default prediction model capable of translating shocks to its input variables into the default likelihood of a target portfolio, and (2) a set of stress-testing regressions which relate the presumed adverse macroeconomic scenarios to shocks to the inputs of the default prediction model. This method can produ...

Credit default events show cross sectional as well as serial correlation. While the latter is often neglected by current credit risk models, this work incorporates both types of dependence. A Bernoulli mixture model is considered, where in each rating grade the probit of the stochastic Bernoulli parameter follows an autoregressive stationary process with exogenous variables. The model parameter...

In financial analysis, stochastic models are more and used to estimate potential outcomes in a risky framework. This paper proposes an approach of modeling the dependence losses on securities, loss portfolio is divided into sectors each including two subsectors. The Weibull model describe behavior default time while nested class Archimedean copulas at three levels maximum value risk portfolio.

Credit risk management is a process in which banks estimate probability of default (PD) for each loan applicant. Data sets of previous loan applicants are built by gathering their data, and these internal data sets are usually completed using external credit bureau’s data and finally used for estimating PD in banks. There is also a continuous interest for bank to use rule based classifiers to b...

We show how conservative portfolio compression, i.e., netting cycles in a financial network, can increase systemic risk even though the exposures of all banks to each other decrease. We argue that this is because cycles enable risk sharing between the involved banks and can thus dampen the effect of a shock on the rest of the financial system. We first provide an example where under certain sho...

Collateralized debt obligations, which are are securities with payoffs that are tied to the cash flows in a portfolio of defaultable assets such as corporate bonds, play a significant role in the financial crisis that has spread throughout the world. Insufficient capital provisioning due to flawed and overly optimistic risk assessments is at the center of the problem. This paper develops stocha...

the main idea of this paper is to study the dependence between the probability of default and the recovery rate on credit portfolio and to seek empirically this relationship. we examine the dependence between pd and rr by theoretical approach. for the empirically methodology, we use the bootstrapped quantile regression and the simultaneous quantile regression. these methods allow to determinate...

A portfolio credit derivative is a contingent claim on the aggregate loss of a portfolio of credit sensitive securities. We develop an economically motivated and computationally tractable top down valuation framework in which portfolio loss follows an affine point process. The magnitude of each loss is random and defaults are governed by an intensity that is driven by affine jump diffusion risk...

The problem in default probability estimation for low-default portfolios is that there is little relevant historical data information. No amount of data processing can …x this problem. More information is required. Incorporating expert opinion formally is an attractive option.