本研究以Schwartz與Moon（2000）提出的實質選擇權模型為基礎，再引入模糊理論，建立模糊實質選擇權模型。太陽能產業的益通為樣本公司，進行參數估計，並使用蒙地卡羅模擬，估計益通的合理價值。經過敏感度分析更進一步瞭解，影響公司價值最重要的因子為期初收入成長率與成本。 將本模型應用到其他電子產業，發現公司的股價常有遭到市場高估或低估，而偏離真實價值的情形發生。因此本研究建立一套投資策略，並參考模型估計的合理價格為投資的依據，希望能夠賺取價差。策略模擬的結果，獲利能力明顯優於長期持有的方式，也證明了本模型的實用性。 / In this study, we use the real option model from Schwartz and Moon (2000) as the basis, and then combine it with fuzzy theory to create Fuzzy Real Option Model. This study takes one company in solar power industry － E-TON as the sample company to conduct the parameter estimation. We also adopt the Monte Carlo Simulation method to assess the reasonable value of E-TON. After the sensitivity analysis, the results show that initial rate of growth in revenues and cost are the most important factors which influenced on the value of a company. Furthermore, we apply this model to other companies in electronics industry and discover that the stock prices are often overvalued or undervalued by the market. Therefore, we develop a set of investment strategies for people who want to make profits from the difference of prices. The result of strategic simulation shows that profit is apparently better than the way of buying and holding, and it proves the practicability of this model as well.

近幾年來，非線性時間數列分析有快速的發展。其中的門檻自迴歸模式(SETAR)，以具有許多線性ARIMA模式所不能配適的特性而受到重視。但是，自1978年Tong建立SETAR模式以來，門檻參數估計的問題一直是SETAR模式在發展應用上的一個瓶頸。本文將探討以實數編碼遺傳演算法，結合統計學上的模式選取準則，建構SETAR模式門檻與延遲參數估計程序的可行性。並從這個基礎上，進一步地研究較精確的門檻參數估計法。 / Non-linear time series analysis has rapidly developed in recent years. Self-exciting threshold autoregression(SETAR) model of non-linear time series models is attentive, because it has some characters which linear ARIMA model fail to fit. But, It has not yet been applied widely because the question of estimation of threshold parameter limits its development and application since Tong proposed SETAR model in 1978. In this paper, we will study the feasibility which constructs a procedure of estimation of SETAR's threshod and delay parameters with real-coded genetic algorithm and statistical criterion of model selection, and develop a more precise estimation of threshold parameter in the basis.

從民國87年所通過的強制汽車責任保險，可發現我國強制汽車責任險的理賠上限與承保範圍等有了重大的改變，造成汽車任意責任險的計算費率必須要重新估算，然而國內對此方面的文獻探討卻著墨不多，因此學生將會針對任意汽車體傷責任險費率釐算詳細加以探討。 而若要重新估計任意汽車責任險首先要做的工作就是要收集完整正確的損失資料，不過由於損失資料的收集相當困難，因此只能透過模擬的損失資料進行任意責任險的費率釐算。而在有模擬的損失資料情況下我們就可透過損失分佈理論進行下列的分析： (1)透過損失資料的特性推估任意汽車責任險可能之損失分佈為Lognormal 分佈。 (2)透過最大概似估計法與特殊法推估Lognormal分佈之參數，並且採用負對數蓋似函數選擇最佳之估計參數。 (3)透過與強制汽車責任險預期損失與汽車任意體傷責任險預期損失之比例關係，釐算汽車任意體傷責任險之純保費。 (4)建立兩種損失趨勢函數，並透過此兩趨勢函數計算汽車任意體傷責任險之高保額係數。 (5)透過上述步驟之計算結果與現行實施之汽車任意體傷責任險費率作比較，以探討是否現行費率是否有超收或不足的現象。 總之，希望此篇論文能夠對未來的汽車任意責任險之費率釐算與保險司費率監督有所幫助。 / Cause the Legislation Yuan passed the compulsory auto liability insurance bill in 1998, we must have a new actuarial pricing of voluntary auto third party insurance. However, all domestic insurers haven’t revised the rate because the absence of the empirical loss data. In addition, only a fewer researches have focused on the actuarial model of this type of insurance. In this paper, we will investigate the pure premium calculation of the voluntary auto insurance, and outline the appropriate model construction procedures. The data we use are not empirical loss data, we calculate the pure premium by the simulated data. The procedures of this study are summarized in the following: (1) Find the possible loss distribution of voluntary auto third party insurance policy. (2) Estimate the parameters of the loss distribution by the maximum likelihood estimate method and the special method of lognormal distribution. (3) Calculation the pure premium of voluntary auto third party insurance. (4) Calculation the increased limits factor(ILF)by two trend functions, and compare the results of two trend functions. (5) Finally, we examine the gross premiums of the voluntary auto third party insurance and compare our results with the actual voluntary auto liability insurance premiums. Altogether, we hope that this paper could be beneficial to the actuaries and also provide suggestions for the government surveillance.