VaR methods for the dynamic impawn rate of steel in inventory financing under autocorrelative return

被引:37
作者
Juan, He [1 ]
Jiang Xianglin [2 ]
Jian, Wang [1 ]
Daoli, Zhu [3 ]
Lei, Zhen [4 ]
机构
[1] SW Jiaotong Univ, Coll Traff Transportat & Logist, Chengdu 610031, Peoples R China
[2] Fudan Univ, Inst Financial Studies, Shanghai 200433, Peoples R China
[3] Tongji Univ, Sch Econ & Management, Shanghai 200092, Peoples R China
[4] Huaxia Bank, Dept Credit Risk Management Chengdu, Chengdu 61000, Peoples R China
关键词
Finance; AR (1)-GARCH (1,1)-GED; Long-term VaR forecasting; Dynamic impawn rate; Inventory financing;
D O I
10.1016/j.ejor.2012.06.005
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
This paper proposes the way of setting the dynamic impawn rate by dividing the impawn periods into different risk windows. In an efficient financial market, the return is hypothetically independent, while in a pledged inventory market where spot transactions predominate, the return is auto-correlative. Therefore, the key to setting the impawn rate is to predict the long-term risk. In this experiment, using the database of spot steel, we established a model with the formula AR (1)-GARCH (1,1)-GED, forecasting the VaR of steel during the different risk windows in the impawn period through a method of out-of-sample, and got the impawn rate according with the risk exposure of banks. The results of our experiment indicated that the introduction of coefficient K into the model can significantly improve bank risk coverage and reduce its efficiency loss. Besides, the impawn rate obtained by the model correlates positively with the lowest price in the future risk windows. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:106 / 115
页数:10
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