Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/139144
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dc.contributor.advisor蔡政憲zh_TW
dc.contributor.author楊瑾容zh_TW
dc.contributor.authorYang, Chin-Jungen_US
dc.creator楊瑾容zh_TW
dc.creatorYang, Chin-Jungen_US
dc.date2021en_US
dc.date.accessioned2022-03-01T08:42:51Z-
dc.date.available2022-03-01T08:42:51Z-
dc.date.issued2022-03-01T08:42:51Z-
dc.identifierG0108358023en_US
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/139144-
dc.description碩士zh_TW
dc.description國立政治大學zh_TW
dc.description風險管理與保險學系zh_TW
dc.description108358023zh_TW
dc.description.abstract臺灣壽險公司每年新契約保費收入屢創新高,大量的保費收入需足夠龐大的投資市場容納,報酬率需與早期壽險公司承諾的高利率保單抗衡,標的剩餘年限應以負債期間相當,避免資產負債錯配問題,文中有多項證據顯示我國資本市場與壽險業投資所需不符。投資環境的困境伴隨主管機關逐步鬆綁對於國外投資之限制,壽險公司逐漸將資金轉向海外,國外投資比例過高已成為近幾年壽險業常態,2020年整體國外投資比例高達64.73%,匯率風險即成為壽險公司燃眉之急的問題,如何降低匯率風險及避險成本成為一重要課題。\n利率部分將以CIR模型模擬國內外短期利率,匯率則引用利率平價理論建構匯率動態過程,藉由隨機利率及匯率的模擬,進行無本金交割遠期外匯避險,觀察不同匯率情境下避險成本及效益如何變化。經由多次避險模擬,視其結果分佈並進行模擬分析,依本研究模擬結果可得出以下結論:\ni. 避險比例與避險成本的波動度呈正向變動,但與避險損益波動度成反向變動,為避險可減緩因匯率變動所造成整體避險損益波動之證據。\nii. 在匯率平穩時,短期匯率波動仍會造成避險成本的起伏,在長期下避險成本及避險損益即會趨於平穩;匯率上升,即臺幣貶值的情境中,避險成本及避險損益相較匯率下跌情境將產生較大的波動。\niii. 雖本研究主要探討匯率風險所造成的威脅,但發現兩國利差與避險成本關聯較大,而匯率波動幅度對於整體避險損益有較大影響。\niv. 利率模擬方式中,拔靴法可以作為市場變動因素較小時的避險損益依據;CIR模型則作為市場變化較大時,避險損益變化之依據。\n近年也有許多研究論文採不同方式描述匯率風險相關議題,在此希望藉由簡化的模擬分析對於我國壽險業匯率風險問題產生洞見,使更多專業人士有相關研究依據並持續鑽研此議題。zh_TW
dc.description.abstractTaiwan life insurance companies’ new contract premiums have repeatedly hit record high. The dilemma of investment environment is accompanied by the gradual loosening of restrictions on foreign investment by Financial Supervisory Commission. The life insurance companies have gradually shifted their funds to overseas. The overall foreign investment proportion in 2020 reached 64.73%. How to reduce currency risk and hedging costs becomes an important issue.\nThrough the simulation of random interest rate and exchange rate, using non-deliverable forward as an example to hedge. Scenario analysis and simulation analysis are the ways to display the results. The following are conclusions based on the simulation results of this research:\ni. The hedging ratio and the volatility of hedging costs are reverse relationship, but the hedging ratio and the hedging profit are positive changes.\nii. When the exchange rate scenario is stable, the hedging cost and profit will stabilize in the long run. If it is the appreciation scenario of exchange rate, the hedging cost and profit have greater volatility than the depreciation scenario.\niii. The interest rate difference between two countries is relatively related to the hedging cost and the exchange rate fluctuations have a greater impact on the overall hedging profit and loss.\niv. Bootstrapping method can be used when market changes are small; CIR model can be used when market changes are large.en_US
dc.description.tableofcontents目 次\n第一章 緒論 1\n第一節 研究動機 1\n第二節 研究目的 5\n第三節 研究架構 5\n第二章 文獻探討 6\n第一節 拔靴法 6\n第二節 短期利率模型 7\n第三節 匯率模型 8\n第三章 臺灣壽險業匯率避險現況 9\n第一節 臺灣壽險業避險實務 9\n第二節 匯率避險工具之介紹 12\n第四章 研究方法 14\n第一節 拔靴法 14\n第二節 短期利率模型 15\n第三節 匯率模型 17\n第四節 匯率避險策略 18\n第五章 模擬結果與分析 21\n第一節 參數估計與基本假設 21\n第二節 情境分析 24\n第三節 模擬分析 32\n第六章 結論與建議 38\n參考文獻 39zh_TW
dc.format.extent3193927 bytes-
dc.format.mimetypeapplication/pdf-
dc.source.urihttp://thesis.lib.nccu.edu.tw/record/#G0108358023en_US
dc.subject匯率風險zh_TW
dc.subject避險成本zh_TW
dc.subject無本金交割遠期外匯zh_TW
dc.subjectCurrency risken_US
dc.subjectHedging costen_US
dc.subjectNon-Deliverable Forwarden_US
dc.title隨機利率及匯率下避險效益之研析 ― 以無本金交割遠期外匯為例zh_TW
dc.titleHedging Cost Evaluation under Random Interest Rate and Exchange Rate ― Using Non-Deliverable Forward as an Exampleen_US
dc.typethesisen_US
dc.relation.reference參考文獻\n一、 中文文獻\n李冠杰,2018,匯率避險策略對壽險業之影響―以利率變動型壽險商品為例,國立政治大學風險管理與保險學系碩士學位論文。\n呂學翰,2020,保險公司生死合險保單匯率風險避險分析:考量無本金遠期匯率及匯率選擇權,國立政治大學金融學系碩士學位論文。\n張士傑,2020,匯率風險對我國壽險業之短中長期經營影響,財團法人台北外匯市場發展基金會專題研究計畫。\n蔡政憲,2015,強化保險業國外投資之匯率風險管理與監理機制之研究,國立政治大學保險業永續發展研究中心。\n二、 英文文獻\nBranson, W. H. 1969. The Minimum Covered Interest Differential Needed for International Arbitrage Activity. Journal of Political Economy, 77(6): 1028-1035.\nByun, J.-C. and S.-N. Chen. 1996. International real interest rate parity with error correction models. Global Finance Journal, 7(2): 129-151.\nCarlstein, E., Do, K.-A., Hall, P., Hesterberg, T., and Künsch, H. R. 1998. Matched-Block Bootstrap for Dependent Data. Bernoulli, 4(3): 305-328.\nCox, J. C., Ingersoll, J. E., Jr., and Ross, S. A. 1985. An Intertemporal General Equilibrium Model of Asset Prices. Econometrica, 53(2): 363-384.\nDaniel L. Thornton. 1989. Tests of Covered Interest Rate Parity. Federal Reserve Bank of St. Louis Review: 55-66.\nDornbusch, R. 1976. Expectations and exchange rate dynamics. Journal of Political Economy, 84: 1161-76.\nEfron, B. 1992. Bootstrap Methods: Another Look at the Jackknife. Breakthroughs in Statistics: Methodology and Distribution. S. Kotz and N. L. Johnson. New York, NY, Springer New York: 569-593.\nHall, P., Horowitz, J. L., and Jing, B.-Y. 1995. On blocking rules for the bootstrap with dependent data. Biometrika 82(3): 561-574.\nHärdle, W., Horowitz, J., and Kreiss, J.-P. 2003. Bootstrap Methods for Time Series. International Statistical Review 71(2): 435-459.\nLongstaff, F. A. and E. S. Schwartz. 1992. Interest Rate Volatility and the Term Structure: A Two-Factor General Equilibrium Model. The Journal of Finance 47(4): 1259-1282.\nVasicek, O. 1977. An equilibrium characterization of the term structure. Journal of Financial Economics 5(2): 177-188.zh_TW
dc.identifier.doi10.6814/NCCU202200314en_US
item.openairecristypehttp://purl.org/coar/resource_type/c_46ec-
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item.grantfulltextembargo_20250220-
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