The Estimation On Value At Risk Of Real Estate Loans Based On Adjusted CreditMetrics Model

With the rapid development of real-estate industry in China, the real-estate loanbecome a large component of commercial bank assets. However, the real-estate loanis with great credit risk generated by its big demand for money, long-terms of capitaloccupation and complex industry chains. Concerned with the role of cash flow inreal-estate industry operation, it largely determines the survival of the real-estatecompanies, and the survival of companies could guarantee the stable operation ofcommercial banks. Therefore, it is significant for commercial banks to measure thecredit risk of real-estate loans at regular intervals. This paper conduct a estimation onthe default probability of the listed real-estate companies based on the cash flowstimulation model raised by Marek Capinsiki which is an extension of Merton optionmodel, and measure the value at risk of the loans by employing CreditMetrics. Theinnovation of this practice is that the default probability comes from the cash flowmodel instead of the estimation based on historical data, which could largely improvethe prediction precision, and the organic combination of cash flow and CreditMetricsmodels promises a better adaption of models. With the continuous liberalization ofinterest rate of financial market, it raises a demand for commercial banks improvingassets pricing ability. The combination of these two models could be applies in manyfields such as the estimation of one loans’ marginal risk, the economic capital, thebusiness performance and the assets pricing. The new model raised by this papercould improve the commercial banks’ credit risk management and promises a betterrisk control.