Abstract

In order to measure the portfolio credit risk of commercial banks in energy saving and environmental protection industry accurately, this paper proposes the value VaRGP of green credit risk and constructs a related model based on Pair Copula grouping model, VaR method (combined with enumeration algorithm).The results show that the credit schemes that commercial banks focus on investing in two areas of industrial emission reduction and environmental restoration is consistent with the conclusion that the two fields have the strongest development momentum.Besides, at different levels of confidence, all of VaRGP have passed the return test, which fully shows that the model is feasible and effective to measure the credit risk in different green fields and to formulate the optimal combination strategy.

Highlights

  • In recent years, environmental pollution, resource depletion and other global environmental problems are increasingly prominent

  • The above risk measurement method cannot be fully applied to the green credit risk assessment of commercial Banks

  • This paper evaluates the green credit risk of commercial Banks from the perspective of the daily return rate of listed companies listed in "green and environmental protection".The modeling object is the daily closing price of the stocks of 35 listed enterprises listed in the ranking list of China's listed environmental protection industry segments from 2015 to 2017.They roughly divided into six categories according to their business fields: 1).Industrial energy conservation and emission reduction X1:(Triple environmental protection, Shenwu Environmental Technology, Kingland Technology, Kai Di Ecological, Green Eco-Manufacture, Shenwu Energy Saving, Beijing Shouhang Resources Saving Co.,Ltd.)

Read more

Summary

1.Introduction

Environmental pollution, resource depletion and other global environmental problems are increasingly prominent. The Copula function proposed by Sklar (1959) [6]is often used to describe the complex dependency structure among multiple variables in the financial market to measure the risk of investment portfolio. In order to simplify the calculation steps, we combined pair Copula group with value-at-risk VaR that introduces enumeration algorithm in this paper, apply it in the field of evaluating green credit risk and optimizing lending weight, and use return test to verify the feasibility and accuracy of the model.This provides basis for measuring the risk of green credit and making high-dimensional green loan portfolio decisions for commercial Banks

2.1Vine structure
2.2Pair Copula grouping model
2.3VaR based on enumeration algorithm
3.1Data preprocessing
3.2The estimation of Copula grouping model and risk optimal
Pass times in return test
3.4Optimal selection of green credit portfolio
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call