Study On The Default Probability Estimation And Interest Rate Pricing Of P2P Lending

In a long time,the most important factor that investors focus on when searching P2 P loans is the interest rate of the loan.However,the collapse of P2 P lending platforms since 2016 makes the default risk a more important factor for investors.Because of the imperfectness of Chinese P2 P lending platforms' credit system,default risks of loans sometimes cannot be revealed perfectly so that the theoretical interest rate of a loan may not equal the actual interest rate of a loan and the actual interest rate may not accurately reflect the real default risk of the loans.Additionally,the paper find that the interest rates of loans with high credits are more likely to be overrated,and the interest rates of loans with low credits are more likely to be underrated.Furthermore,the paper find that loaners whose interest rates overrated are mostly belong to service industry of low level or service industry of high population mobility,and loaners whose interest rates underrated are mostly belong to labor-intensive industry such as agriculture or manufacturing industry,while loaner belongs to other industries can receive a relatively rational interest rate.Although it is better for regulators that platforms price interest rates as accurately as possible,for investors it does not matter whether the actual interest rate is accurate in covering default risk.For investors,the higher the possibility that the real interest rate can completely cover the default risk and the intensity of the interest rate covering the default risk,the more valuable it is for investors.Therefore,the paper replace the theoretical interest in the pricing model above with the actual interest rate to calculate the risk premium of different loans which have different levels of interest rate and figure out proportion of loans whose risk premium is positive and average risk premium to explore the proportion and strength of loans covering default risk.Among them,the results shows that as the interest rate increases,the proportion of loans that can completely cover the default risk shows a trend of first rising and then declining,and the overall trend is inverted U-shaped.Loans which have medium interest rate have the lowest proportion whose default risk cannot be covered by the real interest rate of loans.The results also show that the average revised risk premium decreases with the increase of interest rate,but loans which have medium level interest rate have little difference with the loans which have low level interest rate.Because investors need to make a trade-off between the risk coverage proportion and the risk coverage intensity,the paper constructs a risk game matrix and considers that the optimal strategy for investors is to invest in loans which have medium level(13%-14%)interest rate.The contribution of this paper is to creatively calculate the theoretical interest rate that can exactly cover the default risk on the basis of analyzing the influencing factors of default risk of the loans and calculating the default probability estimates of different loans by using the Logit model.Because calculating theoretical interest rates needs to solve 3357 different nonlinear equations which have three different parameters(loan amount,loan term,and default probability estimate),the paper use Plyr and RootSolve package in R language to solve them and get all the theoretical interest rates of different loans.After that,the paper analyzes whether the actual interest rates of borrowers with different credit grades and different industries are overvalued or undervalued so that providing suggestions for investors and regulators of P2 P lending industry.Moreover,the paper replaces the theoretical interest rate in the pricing model with the real interest rate,figuring out the proportion and strength of loans of different levels of interest rate covering default risks so that finding out what kinds of loans are more valuable for investors.