本文採用Lognormal Forward LIBOR Model (LFM) 利率模型，針對可贖回雪球式債券進行相關的評價與避險分析，而由於此商品的計息方式為路徑相依型態，價格沒有封閉解，故必須利用數值方法來進行評價。過去通常使用二元樹或三元樹的方法來評價具有可贖回特性的商品，但因為LFM是屬於多因子模型，所以不容易處理建樹的過程。而一般路徑相依商品的評價是使用蒙地卡羅法來進行，但是標準的蒙地卡羅法不易處理美式或百慕達式選擇權的問題，因此，本研究將使用由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並進行實證研究。 / 此外，關於可贖回商品的避險參數部分，由於商品的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，將會造成不準確的結果，而Piterbarg (2004)提出了兩種可用來計算在LFM下可贖回商品避險參數的方法，其實証結果發現所求出的避險參數結果較準確，因此本研究將此方法運用至可贖回雪球式利率連動債券，並分析各種參數變化對商品價格的影響大小，便於進行避險工作。

基於SEC之要求，越來越多美國金融機構於其財務報表附註中揭露金融交易資產之風險值；然而計算風險值涉及到許多假設，於是導致過去部分文獻對於風險值資訊揭露之可靠性產生質疑。本研究以風險值之揭露對於報表使用者之資訊價值作為研究課題；為求與附註揭露之風險值資訊比較，本研究以公司帳列之金融交易資產(Trading Assets)、金融交易收入(Trading Revenue)為基礎，利用蒙地卡羅模擬法模擬帳列金融交易資產於次期可能產生之最大潛在損失，並且透過OLS regression及panel data model探討： (1)風險值及金融交易資產潛在可能損失是否可以預測次期金融交易收入波動 (2)風險值與金融交易資產潛在可能損失資訊之提供是否影響次期股票交易量 (3)風險值與金融交易資產潛在可能損失資訊是否可以有效預測次期股價報酬 率變異。 實證結果顯示，風險值之揭露與金融交易資產潛在可能損失之資訊對於預計次期金融交易收入之波動與股價報酬率變異均呈現顯著正相關；易言之，上述兩種資訊之揭露均提供增額之資訊價值。惟另方面，風險值之揭露與金融交易資產潛在可能損失之資訊卻與次期股票交易量呈正相關，也就是說上述兩種資訊的揭露反而會造成投資人降低長期投資持有的意願。 / Financial institutions in the United States are required by the Securities and Exchange Commission to disclose their Value at Risk (VaR) in the footnotes of the financial statements. Over the years, VaR has been used by institutional investors, industry consultants, and regulators as one of the key measures of market risk. However, there are a number of approaches to calculating VaR and some of them may involve various statistical models and assumptions. Due to the fact that different models and assumptions may be used, the VaR numbers produced by different institutions are difficult to compare with one another. The usefulness of these numbers is therefore decreased. This thesis examines the usefulness of disclosures of VaR information. In order to compare with VaR disclosures, the implied potential maximum losses of trading assets are simulated by using Monte Carlo simulation. We then employ the OLS regression and the panel data models to investigate the following research questions: (1)whether VaR and implied potential maximum losses of trading assets disclosed by financial institutions are instrumental in predicting the variability of trading revenue for the next quarter; (2)whether VaR and implied potential maximum losses of trading assets disclosed by financial institutions affect investors' investing decision; (3)how useful are VaR and implied potential maximum losses of trading assets in predicting the volatility of daily stock return next quarter. The empirical results indicate that VaR and implied potential maximum losses of trading assets are significantly related to the variability of trading revenue and the volatility of daily stock returns next quarter. This evidence suggests that both types of disclosures provide incremental information on predicting the variability of trading revenue and investment risk in the future. Nevertheless, we also find that both VaR disclosures and implied potential maximum losses of trading assets are positively associated with future average stock trading volume, implying that investors tend to trade stock more frequently when the market risk information is disclosed.

本文採用 Chib， Nardari， 與 Shephard(2006) 的多變量動態因子隨機波動模型(MSV)， 來探討美、日、台三國的資訊、電腦類股股價報酬率波動的共同行為。 我們將模型中的因子解釋為產業的前景或信心，並藉由模擬的方式描繪出其樣貌，進而希望了解產業景氣循環在股價的波動行為中扮演什麼角色。 研究財務市場間的關聯性一值是一項重要的課題，也發展出各種的模型來描述既有的現象。 MSV 模型將看不到的解釋變量數量化，並將變數的波動行為切割為可由因子所解釋與不能解釋的部分。 且藉由將觀察值的誤差項以及單一因子的波動行為設定為隨機波動，放寬共變數變異數矩陣為定值的假設，讓每一時點都能依時變動，在同類的模型中對資料的設定是較少的。 在實證分析中我們有幾點發現：1. 因子能夠解釋資產間的波動行為，其反映在扣除因子波動之後的自有波動，其波動水準值的降低。 2. 在股價波動劇烈期間，因子解釋能力提高。 3. 因子的解釋能力在不同的國家中差異幅度很大，日本有超過一半的波動可以為因子的波動所解釋，而因子在台灣股價的波動行為只有兩成左右的解釋能力。

2008年9月雷曼兄弟突然宣佈破產，使得雷曼兄弟所發行之連動債成為無價值之債券。雷曼兄弟破產事件後讓投資人對於連動債有極大的恐懼，再加上現在全球經濟處於復甦的力道仍有所疑慮的情況，現今發行機構所發行之連動債，都是偏向連結單一商品的連動債，以避免投資人對複雜結構型連動債的恐懼，所以為了讓投資者可以進一步了解市場上所發行的結構型連動債，並且讓發行機構進一步了解其本身之商品，選取了市場上之結構型連動債進行評價與分析。 本篇論文選定之結構型連動債券為｢完全保本黃金連動債券｣，對此商品進行評價與分析。首先介紹商品之特性，此商品為一個付息債券加上一個連結黃金價格之亞式選擇權，由於此商品亞式選擇權的平均部份是算術平均，沒有公式解，所以利用蒙地卡羅模擬法來進行評價與分析，也使用反向變異法和控制變異法來改善傳統蒙地卡羅模擬法收斂速度較慢的缺點，最後結論部分針對商品之設計提出建議。

本論文的研究目的，主要是希望利用Martingale評價方法與蒙地卡羅模擬法評價出結構型商品條款中隱含的新奇選擇權（Exotic Options）價格，並進而推導出結構型商品的理論價值，並且，期望藉由對個案商品的評價與損益分析，讓讀者瞭解結構型商品的產品結構、報酬型態與成本及潛在風險；此外，本文也從發行券商的角度，探討券商所面臨的潛在風險並提出可行的避險策略。 Martingale評價方法(The Martingale Pricing Method)由Cox與Ross(1976)及Harrison與Kreps(1979)所提出，是一種求解衍生性商品評價的方法，在Martingale評價方法下，衍生性商品的理論價格可經由折現該商品未來期望現金流量而得，且期望值折現可在風險中立環境下進行，折現率使用無風險利率。Martingale評價法在財務工程界是一項沿用已久的數學工具。本論文的主要貢獻，就是延伸Martingale評價法，透過機率測度轉換，推導出多資產股權連動式商品的評價公式解，進而求算出商品的理論價值。 本論文採用在市場上銷售的兩個結構型商品作個案分析，兩個案分別為多資產股權連動式票券與路徑相依指數連動式債券，主要研究成果如下： □ 以Martingale評價法作為本論文的評價模型，採用多資產股權連動式票券為個案，延伸評價模型求出產品的封閉解，並探討此種商品的報酬型態與潛在風險。 □ 以蒙地卡羅模擬法評價本論文的另一項個案—路徑相依指數連動式債券的理論價值，並分別從投資人與發行商的角度，探討產品的利潤與風險。 □ 在程式應用方面，運用MATLAB軟體，以模擬並求算產品的理論價格。

本篇論文的目的在介紹階層貝氏之時間與空間統計模式(spatio-temporal model)，將此模式應用在疾病地圖的分析，以了解疾病在空間上的分佈狀態與時間趨勢。模型中除了納入時間、空間和年齡的效應外，也包括時間與空間、時間與年齡的交互作用，並考慮到空間相關性(spatial correlation)，然後以DIC值(Deviance information criterion)作為模式選取的準則。 本文並以民國88-90年全身紅斑性狼瘡的女性患病人數做為實證分析的資料。配適時間與空間統計模式後，以馬可夫鏈蒙地卡羅法(MCMC)來模擬參數值，估計出各時間、地區、年齡層的對數疾病發生率。由疾病地圖可看出，台灣地區全身紅斑性狼瘡的女性疾病發生率，以20-59歲的年齡層發生率較高，0-19歲的發生率較低。不管在哪一個年齡層，北部和中部地區的發生率都是最高的。時間趨勢方面，88-90年整體疾病發生率有遞減的趨勢，60歲以上的發生率也是遞減的趨勢。但在部分地區，則有發生率遞增的趨勢。 / In this study, we introduce the spatio-temporal model in a hierarchical Bayesian framework and use disease maps to display the spatial patterns and the temporal trends of disease. A special feature of the model is the inclusion of spatial correlations used to examine spatial effects relative to both regional and regional changes over time by group. Then, we use deviance information criterion (DIC) to compare complex hierarchical models. The methodology is illustrated by an analysis of female Systemic Lupls Erythematosus (SLE) morbidity data in Taiwan during the period 1999-2001.The model inference is implemented using Markov chain Monte Carlo method. The outcomes of the practical analysis appear that the higher morbidity rate occurs in 20-year and 40-year period. No matter what age group, the morbidity rate is highest in the north and the middle of Taiwan. Furthermore, the morbidity rate decreases with respect to year as well as over the 60-year period but it increases in some places.

財政部所推動保單紅利自由化及費率自由化政策提供壽險商品市場的另一發展方向，促進我保險市場良性競爭，且自民國九十二年自由分紅保單進入台灣壽險市場，已有數十家壽險公司相繼搶這塊大餅，目前市面上的分紅保單大多採用美式三元利差分紅方式，在紅利部分尚不可設定保證給付，亦即沒有保證保戶每年都一定會領到利差分紅。因此，本研究將介紹在歐洲廣為盛行、附最低保證給付的英式分紅保單，作為國內業者在分紅保單設計上的參考指標。 本研究主要以傳統壽險商品為研究範疇，在不考慮有解約權下以隨機模擬的方式對英式分紅保單進行公平定價。研究方法為在大量模擬下找出不同投資策略的Markowiz效率前緣曲線，並選用這些投資策略於給定不分紅保單的預定利率下，在公平精算原則為前提下以蒙地卡羅法(Monte Carlo Methods)的方式，針對不同目標期末紅利率(Terminal Bonus Target；TB)，找出分紅保單應有的合理預定利率及期間紅利率。再去衡量保險公司不同資產配置下，因為未達到期望紅利所造成的風險。此外，本研究更進一步地以靜態及動態投資策略探討保險公司失去清償能力(Insolvency Risk)的問題。 最後在上述架構下，本研究為了符合市場實際情況，分別針對不同保單期間與不同的繳費方式進行敏感度分析。

在因子模型下，損失分配函數的估算取決於混合型聯合違約分配。蒙地卡羅是一個經常使用的計算工具。然而，一般蒙地卡羅模擬是一個不具有效率的方法，特別是在稀有事件與複雜的債務違約模型的情形下，因此，找尋可以增進效率的方法變成了一件迫切的事。 對於這樣的問題，重點採樣法似乎是一個可以採用且吸引人的方法。透過改變抽樣的機率測度，重點採樣法使估計量變得更有效率，尤其是針對相對複雜的模型。因此，我們將應用重點採樣法來估計偏常態關聯結構模型的尾部機率。這篇論文包含兩個部分。Ⅰ：應用指數扭轉法---一個經常使用且為較佳的終點採樣技巧---於條件機率。然而，這樣的程序無法確保所得的估計量有足夠的變異縮減。此結果指出，對於因子在選擇重點採樣上，我們需要更進一步的考慮。Ⅱ：進一步應用重點採樣法於因子；在這樣的問題上，已經有相當多的方法在文獻中被提出。在這些文獻中，重點採樣的方法可大略區分成兩種策略。第一種策略主要在選擇一個最好的位移。最佳的位移值可透過操作不同的估計法來求得，這樣的策略出現在Glasserman等(1999)或Glasserman與Li (2005)。 第二種策略則如同在Capriotti (2008)中的一樣，則是考慮擁有許多參數的因子密度函數作為重點採樣的候選分配。透過解出非線性優化問題，就可確立一個未受限於位移的重點採樣分配。不過，這樣的方法在尋找最佳的參數當中，很容易引起另一個效率上的問題。為了要讓此法有效率，就必須在使用此法前，對參數的穩健估計上，投入更多的工作，這將造成問題更行複雜。 本文中，我們說明了另一種簡單且具有彈性的策略。這裡，我們所提的演算法不受限在如同Gaussian模型下決定最佳位移的作法，也不受限於因子分配函數參數的估計。透過Chiang, Yueh與Hsie (2007)文章中的主要概念，我們提供了重點採樣密度函數一個合理的推估並且找出了一個不同於使用隨機近似的演算法來加速模擬的進行。 最後，我們提供了一些單因子的理論的證明。對於多因子模型，我們也因此有了一個較有效率的估計演算法。我們利用一些數值結果來凸顯此法在效率上，是遠優於蒙地卡羅模擬。 / Under a factor model, computation of the loss density function relies on the estimates of some mixture of the joint default probability and joint survival probability. Monte Carlo simulation is among the most widely used computational tools in such estimation. Nevertheless, general Monte Carlo simulation is an ineffective simulation approach, in particular for rare event aspect and complex dependence between defaults of multiple obligors. So a method to increase efficiency of estimation is necessary. Importance sampling (IS) seems to be an attractive method to address this problem. Changing the measure of probabilities, IS makes an estimator to be efficient especially for complicated model. Therefore, we consider IS for estimation of tail probability of skew normal copula model. This paper consists of two parts. First, we apply exponential twist, a usual and better IS technique, to conditional probabilities and the factors. However, this procedure does not always guarantee enough variance reduction. Such result indicates the further consideration of choosing IS factor density. Faced with this problem, a variety of approaches has recently been proposed in the literature ( Capriotti 2008, Glasserman et al 1999, Glasserman and Li 2005). The better choices of IS density can be roughly classified into two kinds of strategies. The first strategy depends on choosing optimal shift. The optimal drift is decided by using different approximation methods. Such strategy is shown in Glasserman et al 1999, or Glasserman and Li 2005. The second strategy, as shown in Capriotti (2008), considers a family of factor probability densities which depend on a set of real parameters. By formulating in terms of a nonlinear optimization problem, IS density which is not limited the determination of drift is then determinate. The method that searches for the optimal parameters, however, incurs another efficiency problem. To keep the method efficient, particular care for robust parameters estimation needs to be taken in preliminary Monte Carlo simulation. This leads method to be more complicated. In this paper, we describe an alternative strategy that is straightforward and flexible enough to be applied in Monte Carlo setting. Indeed, our algorithm is not limited to the determination of optimal drift in Gaussian copula model, nor estimation of parameters of factor density. To exploit the similar concept developed for basket default swap valuation in Chiang, Yueh, and Hsie (2007), we provide a reasonable guess of the optimal sampling density and then establish a way different from stochastic approximation to speed up simulation. Finally, we provide theoretical support for single factor model and take this approach a step further to multifactor case. So we have a rough but fast approximation that execute entirely with Monte Carlo in general situation. We support our approach by some portfolio examples. Numerical results show that such algorithm is more efficient than general Monte Carlo simulation.

衡量投資組合的稀有事件時，即使稀有事件違約的機率極低，但是卻隱含著高額資產違約時所帶來的重大損失，所以我們必須要精準地評估稀有事件的信用風險。本研究係在估計信用損失分配的尾端機率，模擬的模型包含同質模型與異質模型；然而蒙地卡羅法雖然在風險管理的計算上相當實用，但是估計機率極小的尾端機率時模擬不夠穩定，因此為增進模擬的效率，我們利用Glasserman and Li (Management Science, 51(11),2005)提出的重點取樣法，以及根據Chiang et al. (Joural of Derivatives, 15(2),2007)重點取樣法為基礎做延伸的改良式重點取樣法，兩種方法來對不同的投資組合做模擬，更是將改良式重點取樣法推廣至異質模型做討論，本文亦透過變異數縮減效果來衡量兩種方法的模擬效率。數值結果顯示，比起傳統的蒙地卡羅法，此兩種方法皆能達到變異數縮減，其中在同質模型下的改良式重點取樣法有很好的表現，模擬時間相當省時，而異質模型下的重點取樣法也具有良好的估計效率及模擬的穩定性。 / When measuring portfolio credit risk of rare-event, even though its default probabilities are low, it causes significant losses resulting from a large number of default. Therefore, we have to measure portfolio credit risk of rare-event accurately. In particular, our goal is estimating the tail of loss distribution. Models we simulate are including homogeneous models and heterogeneous models. However, Monte Carlo simulation is useful and widely used computational tool in risk management, but it is unstable especially estimating small tail probabilities. Hence, in order to improve the efficiency of simulation, we use importance sampling proposed by Glasserman and Li (Management Science, 51(11),2005) and modified importance sampling based on importance sampling which proposed by Chiang et al. (2007 Joural of Derivatives, 15(2),). Simulate different portfolios by these two of simulations. On top of that, we extend and discuss the modified importance sampling simulation to heterogeneous model. In this article, we measure efficiency of two simulations by variance reduction. Numerical results show that proposed methods are better than Monte Carlo and achieve variance reduction. In homogeneous model, modified importance sampling has excellent efficiency of estimating and saves time. In heterogeneous model, importance sampling also has great efficiency of estimating and stability.

鑒於近年全球海外可轉換公司債發行檔數大增，然而以此商品為研究主題的文獻並不多，於是決定以此為研究目標。 　　影響海外可轉換公司債的價格因素包括股票價格、匯率、國內利率、國外利率和發行公司的違約機率，因此可買回、可賣回海外可轉換公司債是一個複雜的商品，而評價也較為困難。本文採用三維度二項樹和最小平方蒙地卡羅法建立評價海外可轉債的數值模型。為了更貼近真實世界，本文考量各變數間相關性和動態信用風險；另外，為了使評價更為精準，於股價過程中加入跳躍過程。 　　本文將模型運用至兩檔台灣公司所發行的海外可轉債，發現理論價格傾向於高估，但是理論價格與市價極為接近，尤其當以最小平方蒙地卡羅法評價時。另外本文也針對發行條件和模型中各個變數作敏感度分析，其中重要的是發現股票波動度、股票與匯率間相關係數在海外可轉債評價中扮演重要的角色。 / The number of Euro-convertible bonds issued has highly increased in the early 2010s. However, the related literature is barely found. This paper studies the pricing models of this investment product. Euro-convertible bonds are complex instruments affected by the credit risk of the issuers, the dynamic process of stock prices, the term structure of the interest rate and the movement of the exchange rate in the same time. Accordingly, building the ECB pricing model is a hard work. This paper presents a model considering the dynamic credit risk and jump in stock price process to make valuation more precise. Another advantage of models in this paper is use of stochastic interest rates for both local and foreign so as to make the model more staying with the real world. The other advantage is taking the correlation between each random variables into account. For pricing the Euro-convertible bonds, the numerical methodologies used in this paper are three-dimension binomial tree and least squares Monte Carlo approach. For purpose of assessing the performance of the model, two Euro-convertible bonds issued by Taiwan companies are chosen as samples and the difference between the theoretical price and market price during its issue period are provided. The results demonstrate that in spite of pretty slight overestimation, the least squares Monte Carlo simulation does a better job. In addition, this paper performs several kinds of sensitivity analysis to have in-depth understanding about the models. The consequence shows that the volatility of a stock return and the correlation between stock and exchange rate play a central role in ECB valuations.