政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/31185

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/31185

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政大典藏 > College of Commerce > Department of Money and Banking > Theses > Item 140.119/31185

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/31185

Title:	可贖回區間雪球型結構債之評價與風險管理 Pricing and Risk Management of Callable Snow Range Note
Authors:	高于晴 Kao,Yu Ching
Contributors:	廖四郎 Liao,Szu-Lang 高于晴 Kao,Yu Ching
Keywords:	市場模型最小平方蒙地卡羅風險管理參數校準 BGM Quanto Sausage Monte Carlo Bucketed Delta
Date:	2006
Issue Date:	2009-09-14 09:29:41 (UTC+8)
Abstract:	本研究使用Lognormal Forward LIBOR Model（LFM）利率模型，針對可贖回區間雪球型結構債進行評價與風險管理，一般評價可贖回商品常使用樹狀模型，但由於LFM模型在機率測度轉換後為非馬可夫隨機過程，樹狀之節點會以指數遞增且無法重合，故並不適用；此外，本商品計息方式為路徑相依型，無法求得其封閉解，因此本研究使用Longstaff and Schwartz（2001）所提出的最小平方蒙地卡羅法，來處理同時具有可贖回與路徑相依特性的商品評價與避險；至於結構債存續期間內之每日指標參考利率，本研究使用Brigo（2001）之漂移項內插法求算非標準期間遠期利率，以計算每季之應計配息與商品價格；最後，利用已拋捕的利率平價理論估計歷史遠期匯率，以模擬台幣計價之國外遠期利率動態，進而求算轉換為Quanto後之商品理論價值。此外，關於可贖回區間結構債的風險管理，由於本研究之商品價格函數不具有連續性，若在蒙地卡羅法之下直接使用重新模擬的方式來求算避險參數，其結果較不準確，而Piterbarg （2004）對於計算可贖回區間型利率商品之避險參數時，建議採用能使價格函數平滑化之Sausage Monte Carlo，故本研究分別對ㄧ般蒙地卡羅與Sausage Monte Carlo進行敏感度分析，而研究結果發現Sausage模擬法所計算之避險參數模擬標準差較小，其模擬結果較精準。
Reference:	中文部份 [1] 曹若玹，「可贖回雪球式商品的評價與避險」，國立政治大學，碩士論文，民國95年。 [2] Philippe Jorion著，風險值，黃達業、張容容譯，台灣金融研訓院。英文部分 [1] Brace, A., D. Gatarek and M. Musiela “The Market Model of Interest Rate” . Dynamics Mathematical Finance 7, p127-155,1997. [2] Brigo, D., “A Note on Correlation and Rank Reduction”,working paper,2002 [3] Brigo, D. and F. Mercurio. Interest Models, Theory and Practice , Springer-Verlag , 2001. [4] Glasserman, P., Monte Carlo Method in Financial Engineering, New York,Springer,2004. [5] Glasserman, P., and X., Zhao.“Fast Greeks by Simulation in Forward LIBOR Models”, Journal of Computational Finance ,3:5-39,1999 . [6] Glasserman, P., and Yu, B. “Number of Paths Versus Number of Basis Functions in American Option Pricing”,Annuals of Applied Probability 14(4),2004. [7] London, Justin. “Modeling derivatives in C++ / Justin London”, Hoboken, N.J. ,J. Wiley, c2005 [8] Longstaff, F. and Schwartz, E. “Valuing American Options by Simulation: A Simple Least-Squares Approach”, The Review of Financial Studies, Vol. 14, No.1, pp. 113-147,2001. [9] Musiela, Marek, Martingale methods in financial modelling, Berlin ; New York : Springer, c1997 [10] Piterbarg.V.V. “A Practioner’s Guide to Pricing and hedging Callable Libor Exotics in Forward Libor Models”,SSRN Working Paper,2003. [11] Piterbarg.V.V. “Computing Deltas of Callable Libor Exotics in Forward Libor Models”,Journal of Computational Finance 7(3),p107-144,2004 [12] Piterbarg.V.V. “Pricing and Hedging Callable Libor Exotics in Forward Libor Models”, Journal of Computational Finance 8(2),p65-117,2004. [13] Roberto,K. Structured products : a complete toolkit to face changing financial markets, John Wiley & Sons Ltd,2002. [14] Rebonato, R. Volatility and Correlation: In the Pricing of Equity, FX and Interest-Rate Options, John Wiley & Sons Ltd., West Sussex,1999. [15] Shreve, S. Stochastic Calculus for Finance II, Springer-Verlag, New York.,2004. [16] Svoboda, S. Interest Rate Modelling, Palgrave Macmillan, New York,2004.
Description:	碩士國立政治大學金融研究所 94352018 95
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G0094352018
Data Type:	thesis
Appears in Collections:	[Department of Money and Banking] Theses

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