本篇論文使用了LHP的近似方法去評價擔保債權憑證，並推導出漸進極值因子模型，又稱單因子copula模型，單因子copula模型被廣泛運用在CDO之風險管理與一些風險因子模擬之應用，但由於2008年之金融海嘯造成市場標準模型Gaussian copula model會有評價上的誤差，所以為了能在市場不穩定時能更精確的求算出分券價差，我們必須找到一個更簡單且快速捕捉到市場不穩定性的模型。在這篇論文中，我們引用了Anna Schloesser在2009年所提出以NIG copula model為基礎的兩個延伸，讓模型更穩健和且擁有良好的性質去進行模擬，NIG Regime-Switch 模型有兩大特色: (i)可以用一致的方法去評價不同到期日的分券，放寬了同一分券必須是相同到期日的假設，和(ii)有不同的相關係數狀態，對於金融風暴來說，狀態轉換可以有效地降低市場不穩定所帶來的評價誤差。本文也對不同模型下的CDO進行風險分析與避險，分券的期望損失廣泛被信評公司視為一項審定信用評等重要的風險衡量指標，但是並無法真實反映出擔保債權憑證分券之間相對風險之大小，因此本文採用期望損失率的觀念，利用期望損失佔本金的比例來比較各分券之相對風險，且本文也求算出CDO之避險參數，讓投資人了解對合成行擔保債權憑證分券避險時所需之避險部位，分券持有人也可依據所要規避的風險類型，選擇市場上現有的信用違約交換指數或是單一資產之信用違約交換(single-name credit default swap)來進行避險。 / This paper presents the Large Homogeneous Portfolio (LHP) approach to the pricing of CDOs and we derive the one-factor copula model. It is popular that the one-factor copula models are very useful for risk management and measurement applications involving the generation of scenarios for the complete universe of risk factors. However, since the financial crisis in 2008 induces some errors in the valuation by Gaussian copula model, which is originally adopted by credit rating firms, it is necessary to have a simple and fast model that can capture the market unstableness. In this paper we apply two extensions of the NIG copula model, which are first present by Anna Schloesser (2009), since they make the model well defined and powerful for scenario simulation. The NIG Regime-Switch copula model allows for two important features: (i) tranches with different maturities modeled in a consistent way, and (ii) different correlation regimes. The regime-switching component of the NIG copula model is especially important in view of the financial crisis. This paper also targets on different models to conduct risk analysis and hedging strategy. The expected loss of tranches is widely used by credit rating organizations as one of the important indicators for risk measurement. However, it can’t reflect the relative risk level between CDO’s tranches. Therefore, our research adopts the concept of expected loss rate, which use the proportion of expected loss to total principal amount to compare the relative risk of each tranche. Moreover, when we want to hedge the spread risk of synthetic CDO tranches, the holders of tranches can choose the existing CDS index or the single-name CDS based on different risks types to hedge. The employment of the NIG Regime-Switch copula model not only has more precise estimation for the spread of tranches but also possess more stable hedge ratio to hedge.

財政透明度為建立一個良好政府治理的基礎。近年來隨著中國大陸高速的經濟發展，中央政府相關單位亦注意到財政公開的重要性。然而，目前中國財政資訊仍處於不透明的狀態。另一方面，中國大陸貪腐現象無所不在，內部腐敗行為更是日益猖獗，因此如何打擊貪腐、提升中國地方政府的財政透明度，就成為迫在眉睫的問題。 因此，本文的研究目的主要探討中國貪腐程度對地方政府財政透明度的影響：第一，瞭解當今社會對於財政透明度的提倡與國際規範；第二，考量貪汙與財政透明度之間可能存在非線性關係，建構一個追蹤平滑轉換迴歸模型（Panel Smooth Transition Regression Model，PSTR），瞭解中國大陸財政資訊的公開情形是否因各地區貪腐程度的不同而有所差異；最後，對於中國大陸嚴重的貪腐與財政透明度的關聯做深入探討，以期能為中國大陸財政不透明與不重視情況提出政策建議。

本文主要探討台灣電視新聞的言談結構(discourse structure)，以及標示各單位的言談標記(discourse marker)。本研究分析25則電視新聞，文類限定於社會新聞。首先，在結構上，每一則新聞包含兩大結構︰導語(news kernel)以及旁白與影片(news body)。兩大結構又可細分為七個較小的單位，分別為︰開場白 (opening)、摘要 (abstract of the news)、事件現場畫面 (event scene presentation)、主要新聞事件 (main news events)、後續發展 (follow-up)、評語 (evaluation)、結尾 (routine ending)。而這七個單位還可再細分為更小的單位。此外，本文所探討的言談標記可分為五類︰1. 指涉詞 (referential forms) 2. 連詞 (connectives) 3. 地方副詞 (locative phrase) 4. 話題轉換填充詞 (topic shift fillers) 5. 畫面轉換 (shot shift)。是故，本文研究重點有二︰1.將新聞結構分為三個階層—Level 1、Level 2、Level 3，並探討出現於不同階層的言談標記在類型與數量上是否反映出階層 (hierarchy)？ 2. 標示各個結構的言談標記為何？ 研究結果指出︰1. 三個階層的言談標記在類型上除了Level 1固定有畫面轉換之外，其餘兩個階層皆無固定的言談標記。另外，在數量上僅Level 1可同時出現多個言談標記，Level 2與Level 3在數量上並無差異，顯示出電視新聞為口說語(spoken language)的一種，訊息與訊息之間的連結性比表現出文體結構階層性更為重要 2. 標示各單位的言談標記並無一致性。受到各單位特性影響，言談標記呈現不同的分佈。 / The present study examines twenty five pieces of broadcast news about crimes and damages in Taiwan. The purpose is to examine the relationship between the discourse structures and their corresponding markers. The discourse structure of a piece of broadcast news is divided into seven components and they are categorized into three levels. Level 1 includes news kernel and news body. Level 2 includes abstract in news kernel, main news events, follow-ups, evaluation, and routine ending in news body. Level 3 contains the smaller units in the Level 2 units. The boundary markers to be examined are divided into four categories: topic shift filler, referential forms, connectives, and shot shift. The present study has two major findings. First, the amounts of markers only show significant difference in Level 1. Down to Level 2 and Level 3, linearity overrides hierarchy. Second, the types of markers are decided by the nature of each unit. The opening is always marked by shot shift and speaker shift plus topic shift fillers/temporals/additives. The abstract section is marked by locative phrase plus referential forms. The event scene presentation section is marked by shot shift and speaker shift plus referential forms. The main news events section is marked by shot shift plus temporals which signal the exact time. Then, the follow-up section is marked by shot shift plus referential forms/connectives. The evaluation section is marked by shot shift plus referential forms. The routine ending section is marked by a relatively longer pause.

臺灣在二十世紀中完成了人口轉型，特別是生育轉型的幅度與速度最為劇烈。也正因為生育轉型過於成功，臺灣此刻正面臨超低生育率導致的人口衰滅危機。近年來，人口學界針對生育率變遷，熱中於探討生育率的步調（tempo）與數量（quantum）效應，藉此瞭解時期生育率變遷的趨勢。 生育步調與數量的分析，本質上仍是時期性測量，未能真正瞭解年輪生育率的變遷，以致對於時期生育率趨勢的分析無法解決根本問題。這個現象，對於臺灣生育率研究特別必須加以處理。然而，臺灣雖然是人口資料的「寶庫」，有關生育的人口統計，卻只有存在於二十世紀下半葉，亦即，二十世紀前半葉的完整生育統計已經無法獲取。本研究試圖結合人口普查、戶籍統計，以及抽樣調查資料，運用參數式模型（parametric mode）和人口轉換（demographic translation）等人口分析方法，嘗試重建二十世紀完整的時期與年輪生育率，藉此，分析年輪生育率與時期生育率之間的變遷關係，最終瞭解未來生育率發展的可能後果。 / Demographic Transition has been completed during the middle of 20th century in Taiwan, and the extent and speed of transition are spectacularly rapid. Due to the over succeed of the demographic transition, lowest-low fertility pattern has stricken Taiwan society and probably led to a horrible extinction. Recently, in order to project the pattern of fertility rate, demographers endeavored to figure out how tempo and quantum effects contribute to fertility rate. Unfortunately, analysis of tempo and quantum effects is essentially periodic measurement. It leads no way to understand the pattern of cohort fertility in Taiwan. However, although Taiwan’s demographic statistics is well known as the world’s treasure trove, the fertility statistics are available for only 50 years. It means that we are not capable of having the first half 20th century’s fertility rate in Taiwan. We use demographic analytic methods such as parametric mode and demographic translation to analyze combined data which is constituted of census data, vital statistics, and survey data. The object of this research is to re-build the 20th century’s fertility rate in Taiwan. Once we have the intact fertility rate in 20th century, we could realize the pattern of period and cohort fertility transition. Furthermore, we will have a better chance to project Taiwan’s fertility rate in the future.

本文旨在探討具有捕捉交易密集度特性的波動率測度模型是否能幫助投資者改 善其資產配置的決策。因此，本文分別考量了利用兩種不同價格抽樣方式所計算 出來的實現波動率 (realized volatility) 模型： (1) 日曆時間抽樣法 (calendar time sampling scheme) 與 (2) 交易次數時間抽樣法 (transaction time sampling scheme)。相較於另一廣為應用的一般化自我迴歸條件異質變異 (Generalized Autoregressive Conditional Heteroskedasticity) 模型而言，這兩種實現波動率模型的優點除了在於它們可以捕捉日內資產報酬率的動態變化之外，交易次數時間抽樣法更可以另外捕捉市場的交易密集度。因此利用交易次數間抽樣法所計算出的實現波動率相對提供給投資者較多的訊息。本文利用了West, Edison and Cho (1993) 所提出的資產組合期望效用模型衡量三種波動率測度的預測績效：(1) 實現波動率 - 日曆時間抽樣法 (2) 實現波動率 - 交易次數時間抽樣法 (3) 指數型一般化自我迴歸條件異質變異 (Exponential Generalized Autoregressive Conditional Heteroskedasticity)。我們的實證結果發現，只有在投資者風險趨避係數越小的條件下，此三種波動率測度模型兩兩之間才有較大的期望效用差距；另外，有趣的是，當市場存在異常的交易波動現象時，交易次數時間抽樣法下的實現波動率所產生的期望效用值總是不輸給另外兩種波動率測度模型的結果。 / This paper examines whether volatility measures that account for trading intensity would help investors make better decisions in their asset allocation. Specifically, we consider two versions of realized volatility (RV), namely, one (RV-C) constructed by regular calendar time sampling, and the other one (RV-T) constructed by transaction time sampling. Comparing to models in the GARCH family, both of these two RVs can capture intraday variations of asset return dynamics. In particular, the RV-T incorporates intraday trading intensity, and hence provides even more valuable information for investors. With the utility-based approach developed by West, Edison, and Cho (1993), we compare the predictive performance of RV-C, RV-T, and the EGARCH model in terms of utility generated with each of these three volatility measures. Our empirical results show that the three measures differ from each other mostly when investors are less risk-averse. Most interestingly, the time-deformed RV-T weakly dominates the RV-C and the EGARCH model when the markets are extremely volatile.

The development of mobile services in the exhibition industry has become a popular issue in a mature internet environment. To successfully implement mobile services in the exhibition industry, exhibitors must be adequately involved in the unprecedented innovation activities. However, for exhibitors to buy into the service, it is essential for them to perceive the value of the service and actually achieve that level of value. With this in mind, this research aims to explore the value of mobile service investment and related value barriers from the perspective of exhibitors. We use the limit-to-value framework to examine the valuation process for mobile services in the context of the exhibition industry and focus on exhibitors in particular. This study can help us to understand the critical value-discounting factors and the valuation process for exhibitors as they consider adopting and using innovative mobile services in the exhibition industry.

本研究採用門檻迴歸模型 (Threshold Autoregression Model)，試圖找出董監事等內部人之申報轉讓比率、持股比率及質押比率等門檻值，進而分析門檻值以內及以外，指標對於代理變數：融資成長率、營收成長率以及本益比與加權指數報酬率的影響程度與方向。本研究實證結果發現： 一、在申報轉讓比率方面： 當申報轉讓比率低於門檻值，存在所謂的群聚效果。當申報轉讓比率高於門檻值時，市場動能與加權指數報酬率無顯著關係，投資人於此階段進行投資決策時應該要謹慎小心。 二、在持股比率方面： 在持股比率低於門檻值時，加權指數報酬率對於前期營收成長率表現的修正幅度較大，意謂著董監事等內部人根據其對未來營收資訊掌握的優勢，反應其對營收資訊的真實性，而藉由持股轉讓的行為，使加權指數大幅度的修正。 三、在質押比率方面： 不管高於或低於門檻值，均無法利用董監事等內部人質押比率為門檻變數來分析本益比效果對加權指數報酬率的影響。造成其檢定失效的原因，可能是樣本小且模型受到極端值的影響所造成。

我國壽險產業在產品、獲利、通路、法令及未來發展方向等各方面的改變，造成各壽險公司必須在經營策略上有所改變。而基於資訊系統對企業影響演進的歷程與策略協同模式的觀點，當代企業，資訊技術已扮演著舉足輕重的角色，從降低成本與提升效率到企業再造與典範移轉。雖然資訊系統是協助組織面對環境改變與企業經營的基礎，也是在知識經濟下以知識為基礎的新產品與服務的基石，但是若企業的策略無法與IT的策略緊密的結合，資訊技術就無法發揮其應有的功效。 老舊系統在面對包括驟變的產業模式、驟變的商業模式、新興的資訊技術與新的資訊技術架構等多面向的衝擊，實在無法協助企業，達到敏捷性企業的境界，因此必需要考慮資訊系統的轉換。然而，老舊系統的轉換卻又是費時、耗錢且冗長的工作，同時，很多企業的系統轉換，並不是一次完成，而是靠一連串的系統改善或再造專案來完成，就更容易造成前後不一致的狀況，而無法達成預期的目標，因此，在進行資訊系統轉換之時，必須要擬定老舊系統轉換策略，才能夠整合各自獨立的專案，朝向一致的目標邁進。 / Life insurance industry of our country is in the changes of various fields such as products, profits, distribution channels, regulations and future thrusts. Lots of insurance companies have to change their strategy. As we knew information technology has been playing very important roles, for example, IT can provide critical revenue opportunities and cost savings during tough times and IT has become both an enabling element and driving force within this rapidly shifting industry, but base on the theory of business IT alignment, if IT strategy could not align with business strategy then it could not work as efficiency as we expected. The need for agility is commonplace across every industry. Could the legacy systems support this kind of change? Unfortunately, most legacy systems prevent businesses from being more adaptable to change. The only way is transforming legacy architectures into reliable, adaptable assets that contribute to ability of an enterprise to respond to continuous, fast-paces change. But transforming the legacy system is time-consuming, expensive and tediously long work, we have to set up legacy systems transformation strategy to ensue successful.

在真實世界中，我們可以觀察到許多財務或經濟變數(股價、匯率、利率等)有時波動幅度非常微小，呈現相對穩定的狀態(Regime)；有時會由於政治因素或經濟環境的變動，突然一段期間呈現瘋狂震盪的狀態。針對這種現象，已有學者提出狀態轉換波動度模型(Regime Switching Volatility Model，簡稱RSV)來捕捉此一現象。 本篇論文選擇每年交易金額非常龐大的外匯選擇權市場，以RSV模型為基礎，採用馬可夫鏈蒙地卡羅法 ( Markov Chain Monte Carlo，簡稱MCMC ) 中的吉普斯抽樣(Gibbs Sampling)法來估計RSV模型的參數，依此預測外匯選擇權在RSV模型下的價格。我們再將此價格與Black and Scholes(BS)法及實際市場交易的價格資料作比較，最後並提出笑狀波幅與隱含波動度平面的結果。結果顯示經由RSV模型與MCMC演算法所計算出來的選擇權價格確實優於傳統的BS方法，且能有效解釋波動率期間結構 (Volatility Term Structure) 與笑狀波幅 (Volatility Smile) 的現象，確實反應且捕捉到了市場上選擇權價格所應具備的特色。

距離期望值4至6倍標準差以外的罕見機率電流值，是當前積體電路設計品質的關鍵之一，但隨著精確度的標準提升，實務上以蒙地卡羅方法模擬電路資料，因曠日廢時愈發不可行，而過去透過參數模型外插估計或迴歸分析方法，也因變數蒐集不易、操作電壓減小使得電流值尾端估計產生偏差，上述原因使得尾端電流值估計困難。因此本文引進統計方法改善罕見機率電流值的估計：先以Box-Cox轉換觀察值為近似常態，改善尾端分配值的估計，再以加權迴歸方法估計罕見電流值，其中迴歸解釋變數為Log或Z分數轉換的經驗累積機率，而加權方法採用Down-weight加重極值樣本資訊的重要性，此外，本研究也考慮能蒐集完整變數的情況，改以電路資料作為解釋變數進行加權迴歸。另一方面，本研究也採用極值理論作為估計方法。 本文先以電腦模擬評估各方法的優劣，假設母體分配為常態、T分配、Gamma分配，以均方誤差作為衡量指標，模擬結果驗證了加權迴歸方法的可行性。而後參考模擬結果決定篩選樣本方式進行實證研究，資料來源為新竹某科技公司，實證結果顯示加權迴歸配合Box-Cox轉換能以十萬筆樣本數，準確估計左、右尾機率10^(-4) 、10^(-5)、10^(-6)、10^(-7)極端電流值。其中右尾部分的加權迴歸解釋變數採用對數轉換，而左尾部分的加權迴歸解釋變數採用Z分數轉換，估計結果較為準確，又若能蒐集電路資訊作為解釋變數，在左尾部份可以有最準確的估計結果；而篩選樣本尾端1%和整筆資料的方式對於不同方法的估計準確度各有利弊，皆可考慮。另外，1%門檻值比例的極值理論能穩定且中等程度的估計不同電壓下的電流值，且有短程估計最準的趨勢。 / To obtain the tail distribution of current beyond 4 to 6 sigma is nowadays a key issue in integrated circuit (IC) design and computer simulation is a popular tool to estimate the tail values. Since creating rare events via simulation is time-consuming, often the linear extrapolation methods (such as regression analysis) are applied to enhance efficiency. However, it is shown from past work that the tail values is likely to behave differently if the operating voltage is getting lower. In this study, a statistical method is introduced to deal with the lower voltage case. The data are evaluated via the Box-Cox (or power) transformation and see if they need to be transformed into normally distributed data, following by weighted regression to extrapolate the tail values. In specific, the independent variable is the empirical CDF with logarithm or z-score transformation, and the weight is down-weight in order to emphasize the information of extreme values observations. In addition to regression analysis, Extreme Value Theory (EVT) is also adopted in the research. The computer simulation and data sets from a famous IC manufacturer in Hsinchu are used to evaluate the proposed method, with respect to mean squared error. In computer simulation, the data are assumed to be generated from normal, student t, or Gamma distribution. For empirical data, there are 10^8 observations and tail values with probabilities 10^(-4),10^(-5),10^(-6),10^(-7) are set to be the study goal given that only 10^5 observations are available. Comparing to the traditional methods and EVT, the proposed method has the best performance in estimating the tail probabilities. If the IC current is produced from regression equation and the information of independent variables can be provided, using the weighted regression can reach the best estimation for the left-tailed rare events. Also, using EVT can also produce accurate estimates provided that the tail probabilities to be estimated and the observations available are on the similar scale, e.g., probabilities 10^(-5)~10^(-7) vs.10^5 observations.