Logo image
銀行利率風險與金融商品市場風險之實證分析與應用
Thesis

銀行利率風險與金融商品市場風險之實證分析與應用

吳佳興
Masters, 國立清華大學, 統計學研究所
2012

Abstract

損失分配 風險值 資本計提率 經濟資本 DNS模型 現貨 期貨 遠期契約 交換 Loss Distribution Value at Risk (VaR) Capital Charge Rate Economic Capital DNS Model (Dynamic Nelson-Siegal Model) Spot Commodities Futures Forward Contracts Swaps
In this paper, our goal is to construct a complete bank’s market risk measurement. First we define the loss formulas of the exposure. Then we identify the risk factors which cause loss, and set the corresponding models. We use DNS term structure model to build the interest rate risk factor model, EGRACH model to build the equity risk factor model, Random Walk model to build the exchange rate risk factor model. Finally, we use Monte Carlo simulation to derive the loss distribution in order to obtain the corresponding VaR and capital charge rate. By using DNS interest rate risk factor model, we can derive the total loss distribution and VaR of the interest rate systemic risk, comparing with historical simulation or other method, to calculate the capital charge rate and economic capital. The results show that the economic capital is between 0.28% and 0.31%. We propose that banks can use our method to measure the exposure’s sensitivity by comparing the economic and regulatory capital. They can also adjust their financial business or investment. By using different risk factor models and the loss formulas of spot commodities, futures, forward contracts, and swaps, we can obtain the corresponding loss distribution and VaR. Furthermore, we can observe the change of VaR between the different financial instruments of the same underlying asset or the same financial instruments with different maturities. Finally, we can identify the reasons which impact for possible future loss.

Metrics

1 Record Views

Details

Logo image