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| Title: | 投資組合保險策略之延伸及應用 |
| Authors: | 林郁棻 |
| Contributors: | 陳威光
江彌修
林郁棻 |
| Keywords: | 投資組合保險
多資產蒙地卡羅模擬
動態調整風險參數 |
| Date: | 2003 |
| Issue Date: | 2009-09-14 09:26:48 (UTC+8) |
| Abstract: | 近年來，投資理財已經成為全民運動，昔日的定存族早已不復見，投資人在進行資產配置時，除了希望能有固定的保障本金及配息之外，更希望能在市場走勢看好時同時享有增值的利益，而投資組合保險便能滿足這些投資人的需求，部分的投資者及基金經理人，也開始運用投資組合保險進行資產配置。
為了更進一步瞭解投資組合保險策略實際上的運作及其特性，本研究利用蒙地卡羅模擬法，針對不同市場（多頭、空頭、盤整）以及資產間相關係數不同下（高度正相關、低度正相關），模擬多支股票所形成的投資組合，探討「複製性賣權策略（SPO）」、「固定比例投資組合保險策略（CPPI）」、「時間不變性投資組合保險策略（TIPP）」、「固定比例策略（CM）」、「買入持有策略（BH）」在不同市場走勢下相對的績效，並找出在不同市場下最適合各種策略的調整法則。此外，針對CPPI與TIPP策略提出動態調整風險參數m值的概念（MCPPI、MTIPP策略），試著改進此兩種策略在傳統上風險參數固定不動的缺點。在實證部分，除了驗證MCPPI與MTIPP的績效是否真的較佳，並檢驗蒙地卡羅模擬中模擬適合不同策略的調整方式的結果是否正確。
經由模擬可發現：多頭時期，SPO與CPPI策略以每日調整為佳，TIPP及CM策略以5%落差調整為佳，而且SPO策略的平均報酬最高；盤整時期，SPO、CPPI、TIPP策略以5%落差調整較好，CM策略以1%落差調整較好，期末報酬以TIPP策略為佳；空頭時期，SPO與TIPP策略以每日調整為佳，CPPI策略以1%落差調整較好，CM策略以5%落差調整較佳，期末報酬也以TIPP策略為優。經由實證可以證明，不論市場走勢為何，MCPPI、MTIPP策略的績效均比傳統的CPPI、TIPP來的好，顯示動態調整風險參數確實能增加投資組合的績效；此外，若能正確預測市場走勢，並依照蒙地卡羅模擬的結果選擇正確的調整法則，將能有效的提升投資組合保險策略的績效。
In order to find out the characteristic and operation of portfolio insurance strategies, this study makes an extensive Monte Carlo simulation comparison of five portfolio insurance strategies (Synthetic put option (SPO), Constant Proportion Portfolio Insurance (CPPI), Time-Invariant Portfolio Protection (TIPP), Constant Mix (CM), Buy and Hold (BH) ) . For each strategy, some measures (average return, standard deviation, protection error and opportunity cost) are calculated to compare its performance. Besides, these strategies are compared in different market situations (bull, bear, no-trend markets) and with different asset correlation (highly correlated, low correlated), taking into account transaction costs and the price limit.
The Monte Carlo simulations show the optimal rebalancing discipline of different portfolio insurance strategies in different markets; moreover, via the simulation process, we can find out a dominant role of TIPP strategies in bear and no-trend markets and a preference for SPO strategies in bull markets. These results are independent of the asset correlation.
In historical simulations, we bring out an extended method for CPPI and TIPP strategies, called MCPPI and MTIPP strategies, which increase the risk multiplier (m) when market price goes up and decrease the risk multiplier when market price goes down. Comparing the portfolio insurance strategies mentioned above (SPO, CPPI, TIPP, CM, BH, MCPPI, MTIPP) ,we can find out that MCPPI and MTIPP strategies can dominate CPPI and TIPP strategies in all market ; besides, if we can use the optimal rebalance discipline correctly, it will effectively enhance the performance of portfolio insurance strategies.
Although in historical and Monte Carlo simulations, we can’t conclude any strategy which is dominant in all market situations, but we can summarize that SPO strategy can dominate other strategies in bull market, and MTIPP and TIPP strategies can dominate other strategies in bear and no-trend market. |
| Reference: | 【英文部分】
1.Bala Arshanapalli, T Daniel Coggin and William Nelson, “Is fixed-weight asset allocation really better?”, The Journal of Portfolio Management, Spring 2001.
2.Black, Fischer and Robert Jones, “Simplifying Portfolio Insurance”, Journal of Portfolio Management, Fall 1987, pp.48-51.
3.Choie, Kenneth S. and Eric J. Seff, “TIPP: Insurance without Complexity : Comment, ” Journal of Portfolio Management, Fall 1989, pp.107-108.
4.Estep, Tony and Mark Kritzman, “TIPP: Insurance without Complexity,”Journal of Portfolio Management, Summer 1988, pp.38-42.
5.Francois Longin, “Portfolio insurance and market crashes” , Journal of Asset Management, Sep 2001.
6.Jarrod W Wilcox, ”Better risk management”, The Journal of Portfolio Management, Summer 2000.
7.Michael J. Brennan and Eduardo S. Schwartz ,”Time invariant portfolio insurance strategies” ,The Journal of Finance, June 1988.
8.P.Bertrand and J.L.Prigent, ”Portfolio insurance :the extreme value approach to the CPPI approach” ,October 2002.
9.P.Bertrand and J.L.Prigent, ”Portfolio Insurance Strategies: OBPI versus CPPI”
10.Perold, Andre F. and William F. Sharpe, “Dynamic Strategies for Asset Allocation,” Financial Analysts Journal, Jan/Feb 1988, pp.16-26.
11.Riccardo Cesari and David Cremonini, ”Benchmarking, portfolio insurance and technical analysis: a Monte Carlo comparison of dynamic strategies of asset allocation” , Journal of Economic Dynamics & Control,2003,pp.987-1011.
12.Roger G. Clarke, and Robert D. Arnott , ”The Cost of Portfolio Insurance: Tradeoffs and Choices” ,Financial Analysts Journal, Nov/Dec 1987.
13.Rubinstein Mark and Hayne E. Leland, “Replicating Options with Positions in Stock and Cash” , Financial Analysts Journal, July/August 1981, pp.63-71.
14.Zhu, Yj and Robert C. Kavee, “Performance of Portfolio Insurance Strategies”, The Journal of Portfolio Management, Spring 1988,pp48-54.
【中文部分】
1.李文濤，投資組合保險策略調整與配置之研究，國立中山大學財務管理研究所/碩士論文，民國九十年六月。
2.邱瑜明，投資組合保險策略—在台灣股市之相關研究，國立政治大學金融研究所碩士論文，民國八十八年六月。
3.徐中民，投資組合保險成本之探討--台灣股市之實證研究，國立成功大學企業管理研究所碩士論文，民國八十九年六月。
4.黃証國，應用基因演算法於動態投資組合保險中操作策略的最適化，國立交通大學資訊管理所碩士論文，民國九十一年六月。
5.許翠珊，投資組合保險與投資人之效用—台灣股市之實證，國立成功大學企業管理研究所碩士論文，民國九十一年六月。
6.蔡惠名，擴充固定比例（CPPI）與時間不變性投資組合保險策略（TIPP）於投資組合之應用，國立中央大學資訊管理所碩士論文，民國九十二年六月。
7.賴彌煥，權變投資組合保險在台灣股市之應用，國立成功大學企業管理研究所碩士論文，民國八十八六月。 |
| Description: | 碩士
國立政治大學
金融研究所
91352009
92 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0091352009 |
| Data Type: | thesis |
| Appears in Collections: | [金融學系] 學位論文
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