Default Rate Under The Condition Of Variable Technology-based Smes Credit Portfolio Optimization Research

This paper discuss credit portfolio optimization of technological SMEs. We build the credit portfolio optimization modelinclude policy support, risk control, risk-return balance constraints based on0-1integer programming and CreditRisk+. First, assumptions for debtor defaults volatility are as follows:(1) fixed default rate of debtors;(2) the debtor’s default rate volatility is driven by single systematic factor;(3) the debtor’s default rate volatility is driven by one systematic factor and specific factor. Then, we apply CreditRisk+model to generate default loss distributions and the risk contributions under the assumptions above. Next, we build the loan project selection model in order to maximize the portfolio’s unit risk-adjusted returns including the establishment of enterprises in different stages of development policy lending ratio requirements, banks risk control constraints and limitations on the effective use of loan. Loan portfolio optimization results show that:1. The more cautious estimation of portfolio risk if we consider default rate volatility is driven by one systematic factor.The under fixed default rate assumption may not robustness because under this assumption will underestimate the risk of portfolio.2. Optimization results of loan project selection model on the basis of systematic and specific factor CreditRisk+better than that of systematic factor CreditRisk+.Assumption for debtor’s default rate volatility is important to estimate portfolio loss distribution and risk contribution of debtor. Assuming the debtor’s credit event driven by one systematic factor and specific factor is more close to the reality of technological SMEs:(1) The technological SMEs may face greater uncertainty, more vulnerable to external shocks. Estimation of loss distribution and risk contribution will be more cautious under this assumption (2) Introduction of specific risk factors will consider risk diversification effect brought by enterprise heterogeneity, under the assumption of fixed default rate and single systematic factor that there are likely to overestimate or underestimate the risk of the loan portfolio.