Estimate & Simulation of Correlated Default Risk with Use Stochastic Intensity Model

Correlated default risk plays a significant role in financial markets and business. Primarily because the risk, alongside time value of money and asset valuation are three components financial analysis. In general, risk and more specifically, Correlated default risk are basic elements affecting the financial behavior. There are also risks in the real world and an important part of the financial system is responsible for the distribution of risk. With the probability distribution of the assets of the institution, we can and will be enable calculated risk. In this context, Dynamic intensity-based models, in which a firm default is governed by a stochastic intensity process, are widely used to model correlated default risk. The computations in these models can be performed by Monte Carlo simulation. the standard simulation method, which leads to biased simulation estimators. In This study, we reviews and develops an exact simulation method for intensity-based models that leads to unbiased estimators of credit portfolio loss distributions, risk measures, and derivatives prices. The new method includes two steps. In a first step, we construct same distribution of Markov chains with the default status and in a second step, we compute function obtained in first step, using accepted / rejected method.