本論文的研究目的，主要是希望利用新奇選擇權（exotic option）來降低保本型基金的高風險投資部分的權利金，提升參與率，藉此吸引投資人。因為近年來保本型基金面臨最大的問題就是『市場波動度變大，造成衍生性商品的價格上升，侵蝕了保本率。』(Lee,2001)，因為波動度和商品價格具有正比的關係。再加入浮動利率之考量之後，求出更精確的封閉解，以及本文所提『雙邊連動』，提升商品吸引力。 在精算科學界，Esscher transform是一種沿用已久的工具。Gerber and Shiu (1994)闡述在某些假設下評價衍生性證券時，Esscher transform是一種有效率的方法。本論文延伸『Esscher transform』方法來求出商品評價的公式解。 本論文的主要貢獻就是引用Esscher transform（Gerber and Shiu,1994架構傳統機率測度轉換並且求出上(下)出局、上(下)生效等保本型指數連動商品的封閉解，並且加入一個新的概念，『雙邊連動』，作為整篇論文的主要貢獻。基於上述原因，本論文研究成果可以分為下面幾項： 1.以『Esscher transform』為本論文的評價模型，加以說明驗證。 2.設計出雙邊保本的保本型指數連動商品，並且找出封閉解以及探討此種商品的可行性及市場性。 3.利用電腦模擬求算評價公式的避險參數。求出多元常態累積機率分配函數，以期能夠解出多資產連動商品的理論價格。並且整理出上下限型的機率密度整理表。 在程式應用的方面，本論文利用了『Mathematica』求取避險參數，因而不必再費時的計算就可以求出正確的避險參數，及利用計量軟體『R』來求算多元常態累積機率分配函數，使本論文的多因子分析不在只是理論。

Derivative pricing, and in particular the pricing of options, is an important area of current research in financial mathematics. Experts debate on the best method of pricing and the most appropriate model of a price process to use. In this thesis, a ``Switching Black-Scholes'' model of a price process is proposed. This model is based on the standard geometric Brownian motion (or Black-Scholes) model of a price process. However, the drift and volatility parameters are permitted to vary between a finite number of possible values at known times, according to the state of a hidden Markov chain. This type of model has been found to replicate the Black-Scholes implied volatility smiles observed in the market, and produce option prices which are closer to market values than those obtained from the traditional Black-Scholes formula. As the Markov chain incorporates a second source of uncertainty into the Black-Scholes model, the Switching Black-Scholes market is incomplete, and no unique option pricing methodology exists. In this thesis, we apply the methods of mean-variance hedging, Esscher transforms and minimum entropy in order to price options on assets which evolve according to the Switching Black-Scholes model. C programs to compute these prices are given, and some particular numerical examples are examined. Finally, filtering techniques and reference probability methods are applied to find estimates of the model parameters and state of the hidden Markov chain. / Thesis (Ph.D.)--Applied Mathematics, 2003.

Derivative pricing, and in particular the pricing of options, is an important area of current research in financial mathematics. Experts debate on the best method of pricing and the most appropriate model of a price process to use. In this thesis, a ``Switching Black-Scholes'' model of a price process is proposed. This model is based on the standard geometric Brownian motion (or Black-Scholes) model of a price process. However, the drift and volatility parameters are permitted to vary between a finite number of possible values at known times, according to the state of a hidden Markov chain. This type of model has been found to replicate the Black-Scholes implied volatility smiles observed in the market, and produce option prices which are closer to market values than those obtained from the traditional Black-Scholes formula. As the Markov chain incorporates a second source of uncertainty into the Black-Scholes model, the Switching Black-Scholes market is incomplete, and no unique option pricing methodology exists. In this thesis, we apply the methods of mean-variance hedging, Esscher transforms and minimum entropy in order to price options on assets which evolve according to the Switching Black-Scholes model. C programs to compute these prices are given, and some particular numerical examples are examined. Finally, filtering techniques and reference probability methods are applied to find estimates of the model parameters and state of the hidden Markov chain. / Thesis (Ph.D.)--Applied Mathematics, 2003.