(3.215.180.226) 您好!臺灣時間:2021/03/06 13:48
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

我願授權國圖
: 
twitterline
研究生:李慧慈
研究生(外文):Lee Hui-Tzu
論文名稱:中央銀行之外匯管理
論文名稱(外文):The Management of Foreign Reserves of Central Bank-The VaR Perspective
指導教授:張大成張大成引用關係
指導教授(外文):Ta-Cheng Chang
學位類別:碩士
校院名稱:東吳大學
系所名稱:國際貿易學系
學門:商業及管理學門
學類:貿易學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:英文
論文頁數:35
中文關鍵詞:中央銀行外匯風險值歷史模擬法蒙地卡羅模擬法邊際風險值成分風險值
外文關鍵詞:VaRcentral bankforeign reserveshistorical simulationMonte Carlo simulationmarginal VaRcomponent VaRRAPM
相關次數:
  • 被引用被引用:4
  • 點閱點閱:311
  • 評分評分:系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔
  • 下載下載:79
  • 收藏至我的研究室書目清單書目收藏:4
中央銀行持有外匯準備的目的除了在促進國際貿易的進行外,也可作為進入外匯市場干預匯率的工具。此外,外匯準備也可視為國家資本的累積,同時可作為國際信用的保證以及降低金融危機的發生。傳統上,央行在管理外匯準備的態度和方法上都偏向保守、謹慎,但另一方面,也可能因為過度的消極,而犧牲了報酬的追求。本文的目的則是在探討相對積極和有效率的外匯準備管理方式。
本文的基本觀念是建構在「風險值」的觀念上。所謂風險值就是在某一程度的信賴水準之下和一定的時間內,資產所可能產生的最大預期損失。本文採用四種方式來計算投資組合的風險值:簡單移動平均法、指數加權移動平均法、歷史模擬法和蒙地卡羅模擬法。根據國際貨幣基金所出版的年報裡的分類,我們計算出全球、工業化國家和開發中國家在1995至2000年間的外匯投資組合風險值。並且利用巴賽爾公約的規定和概似比檢定來比較這些方法的準確性和有效性,再選出其中一個方法以供後續的研究。另外,利用風險調整的績效衡量指標同時考慮風險和報酬,根據這項指標針對工業化國家和開發中國家的績效衡量作一比較。再者,由於歐元已在2002年成為歐洲地區的共通貨幣單位,本文也藉由同時調整歐元和美元的權數來分析歐元的出現是否對外匯準備的管理有無影響。從資產管理的角度來看,將投資組合的風險值細分為marginal VaR和component VaR來描述每一貨幣對投資組合風險值的貢獻程度,藉由這項分析,可以提供管理者在作風險管理時更明確的決策方向。最後,利用不同計算風險值方法的比較,得知若在一開始選取了錯誤的計算方式,最後則會導致錯誤的決策結果。
Central banks hold foreign reserves o facilitate international trade and as a mean of financing exchange rate interventions in the foreign exchange market. Moreover, foreign exchange reserves can be regarded to cumulate assets or capital, and guarantee foreign debt to promote international credit or lower down risk of financial crisis. Traditional management of foreign reserves tends to over passive and conventional. The purpose of this paper is try to investigate a more aggressive and efficient management method for central bankers.
A fundamental component of this framework is value-at-risk (VaR), an estimate of maximum potential loss to be expected over a given period a certain percentage of the time. This paper examines four VaR approaches: SMA, EWMA, historical simulation and Monte Carlo simulation approach. According to the classification of IMF annual report, we calculate portfolio VaR of three divisions between 1995 and 2000. Comparing their accuracy and efficiency by Basel regulation and LR test to select a relative better method, which is historical simulation in our research. Next, introducing the concept of risk-adjusted performance measurement (RAPM) to consider risk and return at the same time and compare the results of industrial and developing countries. This index also provides a useful tool for following research. As Euro has become the unit currency in Europe, we discuss the effect of Euro by adjust the weights of US dollar and Euro. In addition, decomposing the portfolio VaR with marginal VaR and component VaR to outline more efficient management of foreign reserves. Finally, a comparison of different approach presents the result that wrong decision would be made if a wrong approach was selected in the beginning.
List of tables……………………………………………………………………………i
List of figure………………………………………………………………………….ii
Acknowledgments…………………………………………………………………….iii
Abstract……………………………………………………………………………….iv
1. Introduction…………………………………………………………………..…1
2. Methodology……...…………………………………………………...…3
2-1 Parametric Method…………………………………………………..4
2-1-1 Simple moving average (SMA)…………………………..…….4
2-1-2 Exponentially weighted moving average (EWMA)…………….5
2-2 Historical simulation………………………………...…………....6
2-3 Monte Carlo simulation……………………………………………7
2-4 Back testing…..…………………………………………………………….8
2-5 VaR decomposition…………..…………………………………...……...9
2-5-1 Individual VaR……..………………………….………………...10
2-5-2 Marginal VaR……………………………………………………....10
2-5-3 Component VaR…………………….……….……….…………...11
3. Empirical results………...……………………………………………..….....12
3-1 Data sources……………………………………………….…………..…12
3-2 VaR………………………………………….………….……………..….14
3-3 The effect of Euro………………………………….………………….....16
3-4 Risk management…………………………………………….………......18
3-5 An examination of different approaches………………….………..…….19
4. Conclusion………………………………………….………….……..20
Tables………………………………………………………………………..22
Reference……………………………………………………………………………..31
Appendix……………………………………………………………………………..33
1. Basle Committee on Banking Supervision (1996), “Supervisory Framework for the use of ‘Backtesting’ in Conjunction with the Internal Models Approach to Market Risk Capital Requirements,” BIS.
2. Barry Eichengreen and Donald J Mathieson (2000), “The Currency Composition of Foreign Exchange Reserves: Retrospect and Prospect.” IMF Working Paper, WP/00/131. (Washington: International Monetary Fund)
3. Beschloss, Afsaneh, Wendy Mendes (1999-2000), “Reserve Management Policies and Practices.” Central Banking, Vol Ⅹ, Number 4, pp.88-96.
4. Darryll Hendricks (1996), “Evaluation of Value-at-Risk Models Using Historical Data.” FRBNY Economic Policy Review, pp.39-70.
5. Dooley, Michael P., J. Saul Lizondo and Donald J. Mathieson (1989), “The Currency Composition of Foreign Exchange Reserves. ” IMF Staff Papers 36, pp. 285-434.
6. Garman, M.B. (19967a), “Taking VAR to Pieces”, RISK 10/10, pp.70-71.
7. International Monetary Fund (1994-2001), Annual Report, Washington: International Monetary Fund.
8. Jeremy Berkowitz and James O’Brien (2001), “How Accurate are Value-at-Risk Models at Commercial Banks? ” FEDS Working Paper, No. 2001-31..
9. Jorion, Philippe (2000), Value at Risk: The New Benchmark for Controlling Market Risk, New York, McGraw-Hill.
10. Jon Danielsson and Casper G. de Vries (1997), “Value-at-Risk and Extreme Returns” http://www.gloriamundi.org/var/wps.html.
11. Jon Danielsson and Casper G. de Vries (1997), Beyond the Sample: Extreme Quantile and Probability Estimation, Mimeo, Tinbergen Institute Rotterdam, Discussion Paper, Erasmus University.
12. José R. Aragonés, Carlos Blanco, and Juan Mascareñas (2001), “Active Management of Equity Investment Portfolios.” The Journal of Portfolio Management, Vol 27 Iss3, pp.29-pp.46.
13. Katerina Simons (2000), “The Use of Value at Risk by Institutional Investors.” New England Economic Review, Boston, pp. 21-pp.30.
14. Kavin Down (1998), Beyond Value At Risk: The New Science of Risk Management. John Wiley & Sons, Chichester: John Wiley & Sons.
15. Kupiec, Paul (1995), “Techniques for Verifying the Accuracy of Risk Measurement Models.” Journal of Derivatives 2 (December), pp. 73-pp.84.
16. Mario I. Blejer and Liliana Schumacher (1998), “Central Bank Vulnerability and the Credibility of Commitments: A Value-at-risk Approach to Currency Crises.” IMF Working Paper, WP/98/65.
17. Mario I. Blejer and Liliana Schumacher (1998), “VaR for central banks.” Risk, Vol 11 No 10, pp.65-pp.67.
18. Matthew Pritsker (1997), “Evaluating Value at Risk Methodologies: Accuracy versus Computational Time.” Journal of Financial Services Research 12, pp. 201-pp.241.
19. Tian Hongwei and Zhang Wei (1998), “A New Method to Compute Value-at-Risk: Extreme Value Theory.” http://www.gloriamundi.org/var/wps.html.
20. Thomas J Linsmeier, Neil D Pearson (2000), “Value at risk.” Financial Analysts Journal, Vol 56 Iss2, pp.47-pp.67.
21. Winfried G. Hallerbach (1999), “Decomposing Portfolio Value-at-Risk: A General Analysis” Tinbergen Institute Graduate School of Economics.
22. Younes Bensalah (2000/12), “Steps in Applying Extreme Value Theory to Finance: A Review.” Bank of Canada Working Paper 2000-20.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
系統版面圖檔 系統版面圖檔