Mathematical Modelling of Expected Default Frequency

One of the major frontiers in modern finance is the quantification of credit risk and the major resolution of the lessor companies is to identify lessees such that there arises no events of default. The insight to view the equity of a company as a call option provides a coherent framework for the objective measurement of credit risk. Subsequently, credit models were designed on the basis of market data rather than solely depending on the accounting based valuations. However, the market based structural models had its share of challenges in the form of determining value of assets and its volatility and obtaining a cardinal value for the default probability. The extension of the preliminary structural models based on the call options, coupled with empirical databases paved way for accurate models for credit-risk valuation. This efficiency was achieved by the Moody's Corporation through a model named KMV model through the computation of Expected Default Frequency (EDF). The KMV EDF model forms the basis of this analysis which arrives at the default probability of a particular industry and through a multi-variant regression analysis, compares the correlation between the market based EDF and accounting ratios. The model thus formed and verified aims to cater quick decision - making on the credit worthiness of the lease applicants, by determining the applicant's likelihood to default payments