Fundamental Credit Analysis through Dynamical Modeling and Simulation of the Balance Sheet: Case Study of Chinese Real Estate Developers

Abstract

Fundamental credit analysis, widely performed by fixed-income analysts and financial institutions, has yet to develop a method that computes, directly from a company’s financial statements, the default probability, recovery rate upon default, and the fundamental valuation of a company’s credit risk in terms of the prices of its debts. This article introduces a computationally scalable approach to achieve these goals by modeling the dynamics of the multidimensional balance sheet, in which default is defined as the negative level of cash. Using six to eight years of annual financial statements up till 2020 as inputs, the method is applied to several Chinese real estate developers to forecast by simulation their future financials, including default scenarios, and to derive their fundamental credit spreads. The results both agreed and disagreed with the market-traded credit spreads at the time of the forecasts. The model priced the China Evergrande Group’s debt in deep distress-levels more than six months before the company’s actual default.