臺灣博碩士論文加值系統

20世紀末，隨著財務的創新以及衍生性金融商品廣泛的使用，造成金融市場發生了很大的變革，導致市場上的投資者存在著很多的疑慮與不確定性，進而對投資望之卻步。1995年，巴塞爾監理委員會要求金融機構必須有效的估算、確認並揭露其風險值(Value-at-Risk)，提供給市場上投資者更多的資訊以促進全球金融體系的健全與穩定。風險值模型根據銀行過往的經驗、目前持有的投資組合、以及對未來市場的預期去估算出其潛在可能遭遇到的最大損失。Jorion(2002)和Liu, Ryan, Tan(2004)的研究指出，風險值模型所設算出的風險值對於下一期交易性資產收入的波動具有預測的能力；而本篇研究則是根據風險值模型的預測能力去推論金融銀行使用衍生性金融商品的目的，到底是用於避險還是投機。本篇針對美國十八間金融控股公司進行研究，研究的結果發現衍生性金融商品的使用可以降低市場風險對交易性資產收入波動的衝擊，因此推論出金融銀行業衍生性金融商品的使用確實是用於避險，與Riffe(1997)所做的結果相同。希望藉由本篇研究的結果，可以降低市場上投資者對於金融銀行業在使用衍生性金融商品方面的疑慮。

In the end of the 20th century, financial innovation and the comprehensive of derivatives usage caused the revolution in financial market; investors with poor knowledge of the new market were reluctant to invest. Basel Ⅱ (1995) required financial institutions to measure, identify, validate, and report Value-at-Risk for promoting the safety and stability of the global financial system. The estimated market risk model, Value-at-Risk (VaR), evaluates the potential loss based on bank’s holding portfolio, forward experiences, and future anticipation. Jorion (2002) finds that VaR is useful in predicting subsequent variability of trading revenues. Liu, Ryan, and Tan (2004) also find that VaR have predictive power for trading income variability and may increase with bank technical sophistication and over time. This study conjectures the purpose of derivatives usage in banking industry by the predictive power of VaR. The number of samples in this study is extended to 18 U.S commercial bank holding companies over the period of 1997 to the end of 2006. The findings suggested that VaR has well predictive power in predicting subsequent variability of trading revenue. Besides, the findings also suggested that the use of financial derivatives may reduce the influence of the market risk on the variability of trading revenue. Hence, the purpose of financial derivative usage was used for hedge to stabilize the fluctuation of trading portfolio in U.S Commercial Bank Holding Company.

Contents

Chapter 1 Introduction 1
Chapter 2 Literature Review and Research Hypotheses 7
2.1 Value-at-Risk 7
2.2 The role of trading revenue 9
2.3 Derivative usage for hedging or speculating 10
3.1 Data and sample characteristics 13
3.2 Regression analysis 17
Chapter 4 Empirical Results 23
4.1 Predictive power of Value-at-Risk 23
4.2 Purpose in using financial derivatives 23
Chapter 5 Conclusion 27
References 28
Appendix 30
Appendix A. JPMorgan’s Trading Value-at-Risk 30
Appendix B. JP Morgan’s financial statement of revenue 31
Appendix C. “Trading revenue”, “Total revenue”, and “the percentage of trading revenue to total revenue” for JP Morgan 32
Appendix D. JP Morgan Chase’s Derivative Contracts 33


Contents of Figure

Figure 1 “Notional amounts of derivatives contracts” and “Trading revenue” held by commercial bank holding companies over the period 1997 – 2006. 4
Figure 2 The integral notional amount of trading-related revenue, total revenue, and the percentage of trading-related revenue to total revenue from 18 commercial bank holding companies over the period of 1997 to 2006 6
Figure 3 The regression result and the scatter plot of the absolute value of bank’s unexpected trading revenues in quarter t+1 and VaR-based market risk estimated in quarter t: pooled sample of the 18 commercial bank holding companies 24

Contents of Table

Table 1 The 18 commercial bank holding companies’ trading revenue and the change in trading revenue over the period 1997 - 2006 5
Table 2 Summary of total assets, SIC code, CIK code, and first disclosure dates by the sample of the commercial bank holding company which with disclose VaR on their financial report. 20
Table 3 Distribution of notional amounts of derivatives by sample firms fiscal years, maturity, and type of risk exposure 22
Table 4 Descriptive statistics of sample firms 21
Table 5 The regression result of the absolute value of bank’s unexpected trading revenues in quarter t+1 and VaR-based market risk estimated in quarter t, after controlling other control variables: pooled sample of the 18 commercial bank holding companies 25
Table 6 The regression result of the absolute value of bank’s unexpected trading revenues in quarter t+1 and VaR-based market risk estimated in quarter t 26

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