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This paper presents a framework of setting the impawn rate dynamically by dividing the impawn period into different risk windows. Besides, it proposes that compared with pledging loan of bonds and stocks, the essence of inventory financing is to forecast the long-term risk from short-term data, and trade off between the risk window and the term of financial product (impawn period). Based on the dataset of spot steel (?HRB335), usually traded in the over-the-counter markets, this paper establishes the model of VaR-GARCH(1,1)-GED, which can better depict the feature of the heteroskedasticity, leptokurtosis and fat-tails of the returns, forecasts VaR of steel during the different risk windows in the impawn period through methods of out-of-sample. To improve the coverage of the model, this paper introduces the coefficient K, and then gets the impawn rate consistent with the risk tolerance of banks. The main results show that the amended model may control the risk better while reducing the efficiency loss compared with existing methods. It puts forward a dynamic impawn rate mode for banks. |
