本論文之研究目的在以成本與利益觀點，驗證產品資訊搜尋過程，消費者於對搜尋時間成本與產品資訊信心程度之主觀估計，在極大化程度對消費者產品資訊搜尋行為影響所扮演的中介變數角色，藉此瞭解產品資訊搜尋階段，極大化程度對消費者資訊搜尋行為與態度之影響機制。 極大化程度為一種個人追求最佳選擇程度之人格特質傾向。過去極大化程度在消費者行為領域之相關研究，多聚焦於探討不同極大化程度消費者之選項數量偏好、時間成本投入意願與決策後情感反應之差異，甚少有消費者資訊搜尋過程相關議題之討論。本研究認為，產品資訊搜尋實為消費者整體選擇與決策歷程最重要之階段，經常影響消費決策之最終品質，因此若要真正瞭解極大化程度對消費者選擇行為與態度差異之影響，除從極大化人格特質基本定義做為影響之解釋外，亦須藉由探討極大化程度在產品資訊搜尋過程，對消費者資訊成本與利益認知之影響中，連結出整段消費者選擇行為歷程之影響機制關係。 本論文以Ratchford (1982) 所提之「資訊搜尋之成本－利益模式 (The Cost-Benefit Model for Information Seeking)」為理論基礎，並將研究分為兩部份，研究一為探討不同極大化程度消費者在產品挑選機制與產品屬性要求標準上的差異，透過受測者對四項產品之屬性重要度評估、對特定屬性規格之期望標準，得知不同極大化程度受測者在產品屬性重視的程度、視為重要的屬性數量，以及產品屬性要求標準上之差異。研究二則採取2 (資訊延遲時間高、低)×2 (產品屬性離散程度高、低) 組間設計實驗，透過本研究設計之虛擬產品購物網站平台，讓受測者執行產品資訊搜尋任務，從中衡量受測者對產品資訊搜尋時間成本與資訊信心之主觀估計，驗證單位搜尋時間估計與單位資訊效用估計在極大化程度對受測者產品資訊搜尋數量、搜尋過程滿意度與產品知覺價值中，扮演之中介變數角色，以瞭解箇中之內在心理機制。 研究結果顯示，極大化程度與產品屬性重視程度及屬性要求標準呈現顯著正向關係，極大化受測者對產品屬性的重視程度與對產品屬性的要求標準皆較滿足化者高。足見不同極大化程度消費者對選擇之追求目標差異，會具體展現於產品遴選機制與屬性要求標準上。而經過中介變數關係檢定後也發現，極大化程度越高之受測者所估計之搜尋時間與對資訊在決策幫助上的信心越低，因而正向影響了搜尋的產品數量，搜尋時間成本與資訊效用估計亦分別成為受測者對搜尋過程滿意度以及對產品知覺價值之中介變數。 本論文之研究成果除驗證極大化選擇目標與產品遴選機制及屬性要求標準之關聯性外，亦進一步得知極大化程度影響消費者產品資訊搜尋行為與態度之內在心理機制，成功將系統性之消費者資訊搜尋經濟模式與極大化概念結合，為極大化程度研究領域帶來更深入且具理論基礎之發現。研究成果亦可作為通路或產品廠商思索產品陳列與資訊呈現方式時之參考依據，以降低顧客之主觀成本花費、提升產品資訊帶給顧客決策上的利益，提高顧客對個人整體消費過程之滿意度與所選產品之知覺價值。 / The purpose of this research is to demonstrate whether consumers’ subjective estimations of search time and product information confidence are the mediators mediating the effects of maximization tendency on consumers’ product information seeking behavior and attitude. From the perspective of information cost-benefit, the psychological mechanism will be found from this effect of personality on consumer behavior in this research. Maximization tendency was conceptualized in recent ten years to describe individual’s personality that strives for pursuing the best choice. After this concept was developed, most of the researches in this domain focused on discussing in the relationships between maximization orientation and consumers’ choice preferences such as the differences in the amount of alternatives, the aspiration to invest search time, and affective response after making decision. However seldom of them paid their attentions to the stage of product information search to probe the mechanism for the effect of maximization tendency on consumers’ searching behaviors about product information. Since the information seeking is the most important process to influence consumers’ decisions, the current study aims to explore the effects of maximization tendency on the individuals’ subjective estimations of time cost and benefit of product information. Hereby, the whole picture of the causal relationship in consumers’ information searching process would be drawn in this study. Referring to the rationales of Ratchford’s cost-benefit model, this research conducts two studies: the first part is to assess the differences in the criteria and attribute standard of consumers’ product selection with differential maximization tendencies. The second part is to conduct a 2 (the delay length of information appearance: low and high)×2 (the the dispersion of information attributes: low and high) between subject design experiments to demonstrate the mediating effect of two variables: consumers’ subjective estimation of time cost and information confidence during searching for information in the relations between maximization tendency and consumers’ information seeking behavior. The result shows the relationship between participants’ maximization orientation and their selection criteria as well as attribute demand standard exists. In general, maximizers have more complex choice criteria and higher picking standards than satisficers do when they choose the same products. The psychological mechanism is confirmed to help us understand how maximization tendency affect seeking behaviors and attitudes of product information from consumer’s product information seeking behavior and attitude. Manufacturers and store owners are suggested to apply these findings in the arrangement of alternatives and the display of product attribute information in order to reduce customers’ subjective estimation of time cost and improve their perception on information utility to, eventually, increase their satisfaction with the whole consumption experiences.

University of Macau / Faculty of Education

針對金融時序資料變異數不齊一的性質，隨機波動模型除了提供於ARCH族外的另一選擇；且由於其設定隱含波動本身亦為一個隨機波動函數，藉由設定隨時間改變且自我相關的條件變異數，使得隨機波動模型較ARCH族來得有彈性且符合實際。傳統上處理隨機波動模型的參數估計往往需要面對到複雜的多維積分，此問題可藉由貝氏分析裡的馬可夫鏈蒙地卡羅法解決。本文主要的探討標的，即在於利用馬可夫鏈蒙地卡羅法估計美元/新台幣匯率隨機波動模型參數。除原始模型之外，模型的擴充分為三部分：其一為隱含波動的二階自我回歸模型；其二則為藉由基本模型的修改，檢測匯率市場上的槓桿效果；最後，我們嘗試藉由加入scale mixture的方式以驗證金融時序資料中常見的厚尾分配。

競爭風險之下對邊際分配的估計，是許多領域中常遇到的問題。由於主要事件及次要事件互相競爭，只要一種事件先發生即終止對另一事件的觀察，在兩事件同時發生的機率為0之下，連一筆完整的資料我們都無法蒐集到。除非兩事件互為獨立或加上其它條件，否則會有邊際分配無法識別的問題。但是獨立的條件在有些情況下並不合理，為解決相依競爭風險之邊際分配無法識別的問題，可先假定兩事件發生時間之間的關係。 由於關聯結構定義出兩變數間的結合關係，我們可利用關聯結構解釋兩事件發生時間之間的關係。假定兩變數之相關性參數為已知，且採用機率積分轉換的觀念，本論文討論了Zheng 與 Klein提出的關聯結構-圖形估計量，是否會依設限程度、相關性強度和關聯結構形式的不同，以致估計能力有別。 / The problem of estimating marginal distributions in a competing risks study is often met in scientific fields. Because main event and secondary event compete with each other, and a first occurring event prevents us from observing another event promptly, the intact lifetimes or survival times are unable to be collected in the circumstances that the probability of both lifetimes coinciding is 0. Unless lifetimes being independent or adding other conditions, there is a problem that the marginal distributions are non-identifiable. But the condition of independence is not always reasonable, we may assume the relation between lifetimes has some special form Because the copula defines the association between two variables, it can be employed to explain relation between lifetimes. Assuming that the dependence parameter in the copula framework is known, and adopting the concept of the probability integral transformations, this thesis has demonstrated whether the estimating abilities of the copula-graphic estimator, that Zheng and Klein put forward, are different in rates of censoring, intensities of dependence, and forms of the copula.

偵測新興議題對於研究者而言是一個相當重要的問題，研究者如何在有限的時間和資源下探討同一領域內的新興議題將比解決已經成熟的議題帶來較大的貢獻和影響力。本研究將致力於協助研究者偵測新興且具有未來潛力的研究議題，並且從學術論文中探究對於研究者在做研究中有幫助的學術智慧。在搜尋可能具有研究潛力的議題時，我們假設具有研究潛力的議題將會由同一領域中較具有影響力的作者和刊物發表出，因此本研究使用貝式估計的方法去推估同一領域中相關的研究者和學術刊物對於該領域的影響力，進而藉由這些資訊可以找出未來具有潛力的新興候選議題。此外就我們所知的議題偵測文獻中對於認定一個議題是否已經趨於成熟或者是否新穎且具有研究的潛力仍然缺乏有效及普遍使用的衡量工具，因此本研究試圖去發展有效的衡量工具以評估議題就本身的發展生命週期是否仍然具有繼續投入的學術價值。 本研究從許多重要的資料庫中挑選了和資料探勘和資訊檢索相關的論文並且驗證這些在會議論文中所涵蓋的議題將會領導後續幾年期刊論文相似的議題。此外本研究也使用了一些已經存在的演算法並且結合這些演算法發展一個檢測的流程幫助研究者去偵測學術論文中的領導趨勢並發掘學術智慧。本研究使用貝式估計的方法試圖從已經發表的資訊和被引用的資訊來建構估計作者和刊物的影響力的事前機率與概似函數，並且計算出同一領域重要的作者和刊物的影響力，當這些作者和刊物的論文發表時將會相對的具有被觀察的價值，進而檢定這些新興候選議題是否會成為新興議題。而找出的重要研究議題雖然已經縮小探索的範圍，但是仍然有可能是發展成熟的議題使得具有影響力的作者和刊物都必須討論，因此需要評估議題未來潛力的指標或工具。然而目前文獻中對於評估議題成熟的方法僅著重在議題的出現頻率而忽視了議題的新穎度也是重要的指標，另一方面也有只為了找出新議題並沒有顧及這個議題是否具有未來的潛力。更重要的是單一的使用出現頻率的曲線只能在議題已經成熟之後才能確定這是一個重要的議題，使得這種方法成為落後的指標。 本研究試圖提出解決這些困境的指標進而發展成衡量新興議題潛力的方法。這些指標包含了新穎度指標、發表量指標和偵測點指標，藉由這些指標和曲線可以在新興議題的偵測中提供更多前導性的資訊幫助研究者去建構各自領域中新興議題的偵測標準。偵測點所代表的意義並非這個議題開始新興的正確日期，它代表了這個議題在自己發展的生命週期上最具有研究的潛力和價值的時間點，因此偵測點會根據後來的蓬勃發展而在時間上產生遞延的結果，這表示我們的指標可以偵測出議題生命力的延續。相對於傳統的次數分配曲線可以看出議題的崛起和衰退，本研究的發表量指標更能以生命週期的概念去看出議題在各個時間點的發展潛力。本研究希望從這些過程中所發現的學術智慧可以幫助研究者建構各自領域的議題偵測標準，節省大量人力與時間於探究新興議題。本研究所提出的新方法不僅可以解決影響因子這個指標的缺點，此外還可以使用作者和刊物的影響力去針對一個尚未累積任何索引次數的論文進行潛力偵測，解決Google 學術搜尋目前總是在論文已經被很多檢索之後才能確定論文重要性的缺點，學者總是希望能夠領先發現重要的議題或論文。然而，我們以議題為導向的檢索方法相信可以更確實的滿足研究者在搜尋議題或論文上的需求。 / This research presents endeavors that seek to identify the emerging topics for researchers and pinpoint research intelligence via academic papers. It is intended to reveal the connection between topics investigated by conference papers and journal papers which can help the research decrease the plenty of time and effort to detect all the academic papers. In order to detect the emerging research topics the study uses the Bayesian estimation approach to estimate the impact of the authors and publications may have on a topic and to discover candidate emerging topics by the combination of the impact authors and publications. Finally the research also develops the measurement tools which could assess the research potential of these topics to find the emerging topics. This research selected huge of papers in data mining and information retrieval from well-known databases and showed that the topics covered by conference papers in a year often leads to similar topics covered by journal papers in the subsequent year and vice versa. This study also uses some existing algorithms and combination of these algorithms to propose a new detective procedure for the researchers to detect the new trend and get the academic intelligence from conferences and journals. The research uses the Bayesian estimation approach and citation analysis methods to construct the prior distribution and likelihood function of the authors and publications in a topic. Because the topics published by these authors and publications will get more attention and valuable than others. Researchers can assess the potential of these candidate emerging topics. Although the topics we recommend decrease the range of the searching space, these topics may so popular that even all of the impact authors and publications discuss it. The measurement tools or indices are need. But the current methods only focus on the frequency of subjects, and ignore the novelty of subjects which is critical and beyond the frequency study or only focus one of them and without considering the potential of the topics. Some of them only use the curve of published frequency will make the index as a backward one. This research tackles the inadequacy to propose a set of new indices of novelty for emerging topic detection. They are the novelty index (NI) and the published volume index (PVI). These indices are then utilized to determine the detection point (DP) of emerging topics. The detection point (DP) is not the real time which the topic starts to be emerging, but it represents the topic have the highest potential no matter in novelty or hotness for research in its life cycle. Different from the absolute frequent method which can really find the exact emerging period of the topic, the PVI uses the accumulative relative frequency and tries to detect the research potential timing of its life cycle. Following the detection points, the intersection decides the worthiness of a new topic. Readers following the algorithms presented this thesis will be able to decide the novelty and life span of an emerging topic in their field. The novel methods we proposed can improve the limitations of impact factor proposed by ISI. Besides, it uses the impact power of the authors and the publication in a topic to measure the impact power of a paper before it really has been an impact paper can solve the limitations of Google scholar’s approach. We suggest that the topic oriented thinking of our methods can really help the researchers to solve their problems of searching the valuable topics.

風險值大多是在假設資產報酬為常態分配下計算而得的，但是這個假設與實際的資產報酬分配不一致，因為很多研究者都發現實際的資產報酬分配都有厚尾的現象，也就是極端事件的發生機率遠比常態假設要來的高，因此利用常態假設來計算風險值對於真實損失的衡量不是很恰當。 針對這個問題，本論文以歷史模擬法、變異數-共變異數法、混合常態模型來模擬報酬率的分配，並依給定的信賴水準估算出風險值，其中混合常態模型的參數是利用準貝式最大概似估計法及EM演算法來估計；然後利用三種風險值的評量方法：回溯測試、前向測試與二項檢定，來評判三種估算風險值方法的優劣。 經由實證結果發現： 1.報酬率分配在左尾臨界機率1％有較明顯厚尾的現象。 2.利用混合常態分配來模擬報酬率分配會比另外兩種方法更能準確的捕捉到左尾臨界機率1％的厚尾。 3.混合常態模型的峰態係數值接近於真實報酬率分配的峰態係數值，因此我們可以確認混合常態模型可以捕捉高峰的現象。 關鍵字：風險值、厚尾、歷史模擬法、變異數-共變異教法、混合常態模型、準貝式最大概似估計法、EM演算法、回溯測試、前向測試、高峰 / Initially, Value at Risk (VaR) is calculated by assuming that the underline asset return is normal distribution, but this assumption sometimes does not consist with the actual distribution of asset return. Many researchers have found that the actual distribution of the underline asset return have Fat-Tail, extreme value events, character. So under normal distribution assumption, the VaR value is improper compared with the actual losses. The paper discuss three methods. Historical Simulated method - Variance-Covariance method and Mixture Normal .simulating those asset, return and VaR by given proper confidence level. About the Mixture Normal Distribution, we use both EM algorithm and Quasi-Bayesian MLE calculating its parameters. Finally, we use tree VaR testing methods, Back test、Forward tes and Binomial test -----comparing its VaR loss probability We find the following results: 1.Under 1% left-tail critical probability, asset return distribution has significant Fat-tail character. 2.Using Mixture Normal distribution we can catch more Fat-tail character precisely than the other two methods. 3.The kurtosis of Mixture Normal is close to the actual kurtosis, this means that the Mixture Normal distribution can catch the Leptokurtosis phenomenon. Key words: Value at Risk、VaR、Fat tail、Historical simulation method、 Variance-Covariance method、Mixture Normal distribution、Quasi-Bayesian MLE、EM algorithm、Back test、 Forward test、 Leptokurtosis

本文以2003到2006年美國上市之不動產投資信託（REITs）的資產稅賦遞延交換做研究，並用資產出售交易作為比較，觀察稅賦遞延交換對股票報酬和股利的影響，研究結果發現稅賦遞延交換對於股票報酬有負的宣告效果，然而出售資產的交易有正的且顯著的宣告效果，由於美國REITs基於稅法規定，作為免稅體，每年要以股利的形式分配百分之九十的盈餘給股東，稅賦遞延交換並不能像資產出售交易一樣帶來現金流入，因此對於未來股東的股利所得有所影響，股東對於股票報酬沒有正向的反應，但是股東會考慮稅賦遞延交換會帶來資產重配置的效率，再加上REITs通常會支付比規定還要多的股利，因此稅賦遞延交換的對於股票報酬的負影響會因此而減弱，進一步針對交易方式還有REITs股利分配進行研究，研究的結果支持稅賦遞延交換後的股利比起直接出售交易後所發放的股利還要少。本文除了研究股東對於交易宣告的反應之外，也綜觀不同資產交易方式的現金流量和REITs股利的關連性，藉此瞭解影響REITs選擇交易方式的內涵因素，以及對股票報酬和股利的影響。 / This research examines the tax deferred exchanges made by public U.S. Real Estate Investment Trusts (REITs) over 2003-2006 as well as the transactions of sell-off. The purpose of this study attempts to explore the effects of tax deferred exchange on stock returns and dividend distribution. Result of this study shows that announcement effect of tax deferred exchange is negative in stock value. On the contrary, the relationship between sell-offs and stock value is significantly positive. The reason to explain the difference on announcement effect between two types of property transaction is the specific taxable earning distribution restriction on REITs. U.S REITs have to pay out 90 % of taxable earnings in the form of dividends to their shareholders to exempt from tax. As a result, tax deferred exchange doesn’t bring cash inflow contributing to dividend increase and then shareholders react a lower stock return on tax deferred exchange than on sell-offs. However, the negative effect is weakened by the efficiency of asset reallocation and the regular dividend distribution over tax law restriction. In the analysis of dividend payment, the result of dividend examination supports the hypothesis that tax deferred exchange without cash inflow make dividend fewer than sell-offs. This study may be of importance in explaining the reaction of shareholders on tax deferred exchange of REITs’ property, as well as in providing shareholders with a better understanding of the relationship between cash flow and dividend distribution in order to clarify the cause that affect REITs to utilize different types of transaction and the factors that affect stock return and dividend.

金融監理制度影響一國商業銀行經營績效的相關議題，一直受到學者與政府當局的重視，為瞭解亞洲地區銀行業在中央銀行與監理單位不同管理下的利潤效率，找出最適的制度設計，本研究根據Huang、Huang與Liu（2014）提出之隨機共同利潤邊界（stochastic meta-profit frontier），採用兩階段估計法，蒐集中國大陸、香港、印度、日本、韓國、馬來西亞、巴基斯坦、菲律賓、新加坡、斯里蘭卡、泰國以及阿拉伯聯合大公國等十二國商業銀行資料，分成開發中和已開發國家兩個群組，將環境變數納入無效率模型中，進行實證分析，比較不同群組的利潤效率差異，發掘影響效率的主要變數與方向，從而獲得重要政策意涵。 根據實證分析結果，中央銀行介入銀行監理程度越高，商業銀行利潤效率越低；金融監理單位整合程度越高，商業銀行利潤效率越高；中央銀行獨立程度越高，商業銀行利潤效率越低；已開發國家群組的平均技術缺口比率與共同邊界技術效率值皆高於開發中國家群組，符合預期。共同利潤效率最高的是日本，最低的是韓國。平均而言，各國若在共同利潤邊界上從事生產，能提升41.9%至75%的利潤。 / The effects of degrees of financial supervision on performance of commercial banks have long been important issues and drawn much attention to academic researchers and government authorities. This study applies the stochastic meta-profit frontier, recently developed by Huang, Huang, and Liu (2014), to estimate and compare profit efficiencies of commercial banks from 12 Asian countries, i.e., Mainland China, Hong Kong, India, Japan, South Korea, Malaysia, Pakistan, Philippines, Singapore, Sri Lanka, Thailand, and United Arab Emirates. We divide the sample countries into two groups, i.e., developing and developed countries. This enables us to further investigate the effects of different supervisory systems, enforced by central banks (CB) and supervisory authorities, on commercial banks’ profit efficiencies, as well as to make a suggestion about the optimal supervision regimes in the area. Note that a set of supervisory indices are considered as environmental variables that explain profit inefficiency. Using the two-stage estimation procedure, the empirical results are summarized as follows. First, it is found that bank’s profit efficiency decreases with the increase in a CB’s supervision sectors. Second, the unification of supervisory authority has positive effect on bank’s profit efficiency. Third, the more independent is the CB, the less profit efficient the commercial bank is. Fourth, banks in the group of developed countries are found to have higher technology gap ratios and meta-profit efficiencies than those in the group of developing countries, as expected. Fifth and finally, Japan and South Korea has the highest and the lowest level of meta-profit efficiency, respectively. Evidence is found that if an average commercial bank were adopting the best technology, it can earn roughly 41.9% to 75% more profits than otherwise.