Study On Decision Optimization Of Combined Pledge Loan Of Forest Rights Based On Value Fluctuation

Forest pledge loan is an important financial innovation,which liberates the use function of forest right and expands the income source of bank.This paper,taking forest rights as the pledge to loan-to-value ratio as decision variables,the study was based on the combination of forest right pledge loan value decision optimization problem,to solve the problem of financing needs of forest production and operation,expanding the bank’s income sources and how to effectively reduce the risk of forest right mortgage loan business,etc.,to provide feasible references.Firstly,based on the random fluctuation of forest right value with market demand,an optimization model of forest right pledge decision based on incomplete information static game is constructed to determine the optimal guarantee rate of Banks.Secondly,the dynamic decision optimization model of forest right pledge under bounded rationality is constructed.Thirdly,based on the static pledge mode and the premise that the price change of forest right combination is relatively independent and obeys lognormal distribution,the possibility of cooperative game between forest farmers and third-party management companies is considered.The results show that under the static game with incomplete information,the higher the loan guarantee rate,the higher the expected return of the bank,and the higher the default risk of the foresters.Under the dynamic game of incomplete information,the foresters will repay the bank loans when they mature,and the bank will also choose to lend to the foresters.In addition,when there is cooperation between forest farmers and third party management,Banks can improve the inspection frequency and increase the penalty of rent-seeking behavior of third party management companies.Finally,the paper puts forward some reasonable Suggestions for the decision making and risk prevention of the portfolio pledged loan of forest rights in Banks from the aspects of asset evaluation,credit information management,risk management,intelligent decision making and the end-of-term price forecast of forest rights.