90年代末東亞金融危機造成多國貨幣大幅貶值，銀行紛紛倒閉。基本上金融危機可分為通貨危機(Currency Crisis)與銀行危機(Banking Crisis)；通貨危機是指當年中任一季名目匯率貶值超過25%，且貶值幅度比前一季超過10個百分點。諸多實證文獻顯示，高估一國匯率為其通貨崩潰之先驅；又由於近年來新興國家快速開放資本市場，以致於成為危機之導火線。為分析此一現象，本文首先編製金融帳權數之新台幣實質有效匯率指數，並將東亞之台灣、印尼、韓國、菲律賓、泰國等五國之匯率、相對物價（各國與美國物價）、金融帳餘額等變數做共整合關係檢定，觀察三個變數的長期均衡關係，再將誤差項加入模型中，建構向量誤差模型。實證結果發現，金融帳與相對物價對匯率有顯著之影響力。 / The 1997 East Asian Crises had made exchange rate depreciations and bank bankruptcies. Broadly speaking, it can be divided into currency crisis and banking crisis. Nominal exchange rate of any season in a year, which is depreciated over 25% and 10% than last season, is called a currency crisis. Lots of papers demonstrate that overvaluation is a precursor of a currency crash. Furthermore, developing countries have opened capital markets so rapidly that it became the tinderbox of crises. To analyze the phenomenon, this thesis first compile Taiwan’s financial weighted real effective exchange rate index, then examine exchange rates, relative prices (compare to American consumer price index), and net financial account of Taiwan, Indonesia, Korea, Philippine, and Thailand with cointegrated test to identify the long run equilibrium relationships between variables; then adding error terms into models to estimates vector error correction model (VECM). The empirical results show that financial account and relative price influence exchange rate significantly.

本論文包括3篇時間序列方法在財務的應用。第一篇以門檻向量自我迴歸模型(threshold vector autoregression)分析股市訊息傳遞的不對稱效果；第二篇利用不對稱共整合模型(asymmetric cointegration)分析中國大陸股市之間長期均衡關係；第三篇根據追蹤資料共整合檢定(panel Cointegration test)檢定購買力平價說。 第一篇文章利用門檻向量自我迴歸模型分析Nasdaq股市對台灣、日本與韓國股市不對稱的訊息傳遞效果。實證結果發現，當Nasdaq市場處於下跌狀態時（壞消息狀態），Nasdaq市場干擾對亞洲股市的衝擊較大，反之，當Nasdaq市場處於上漲狀態時（好消息狀態）時，Nasdaq市場干擾對亞洲股市的衝擊較小，而在壞消息狀態時，Nasdaq指數大跌對Jasdaq指數與Kosdaq指數的衝擊效果大於Nasdaq指數大漲的效果，Nasdaq指數小跌所產生的衝擊與小漲所產生的效果具有對稱性。 第二篇文章以Enders and Siklos(2001)不對稱共整合模型探討，中國大陸上海及深圳A股與B股股價指數之間長期不對稱的均衡關係，實證結果發現，在1992年10月至2001年8月，上海A股指數與深圳A股指數之間具有不對稱共整合關係，且當上海A股處於好消息狀態（股市上漲）時，其誤差修正項的調整速度較壞消息狀態（股市下跌）之下為快，此外，上海A股指數與深圳A股指數之間其有雙向的連動關係。在B股開放之後，則是深圳股市A股與B股指數存在不對稱共整合關係，同時Granger因果關係檢定顯示深圳B股指數領先A股指數。 第三篇文章利用Pedroni(2001)追蹤資料共整合檢定，探討大麥克漢堡價格與CPI兩種不同的價格指數用於檢定購買力平價說的有效性，根據14個國家1992-1999年的追蹤資料得到的實證結果顯示，以名目匯率作為被解釋變數，則大麥克漢堡價格與CPI都是支持PPP假說，然而若以相對價格為被解釋變數，則只有大麥克漢堡價格是支持PPP假說，而以CPI為基礎的PPP假說則是無法得到支持。除此之外，本文的實證結論並不受生產力差異的影響。 關鍵字：門檻向量自我迴歸模型、不對稱共整合、追蹤資料共整合、股票市場、購買力平價說 / This dissertation includes three financial applications using time series methods. The first article investigates the asymmetric effects of information transmissions in stock markets using threshold vector autoregression model. The second article uses asymmetric cointegration to study the long-run equilibium relationships among Chinese stock markets. The third article uses panal cointegration to test purchasing-power parity (PPP). Firstly, we examines the asymmetric effects of information transmissions of Nasdaq stock market on Taiwan, Japan, and Korea stock markets by using a threshold vector autoregressive model. And also, we check whether Nasdaq stock market have different impacts on organized stock exchanges (including TAIEX, NIKKEI 225 Index, Korea Composite Index) and over-the-counter markets (including Taisdaq Index, Jasdaq Index, and Kosdaq Index) or not. The empirical results indicate that negative innovations in Nasdaq market (bad news regime) have large influence on Asia stock markets. Particularly, the positive innovations in Nasdaq market (good news regime) have small influence on Asia stock market. The large negative innovations in Nasdaq market have great influence than those of the large positive innovations on Jasdaq Index and Kosdaq Index in bad news regime. The second article uses Enders and Sikios's (2001) asymmetric cointegration model to investigate the long-run asymmetric equihbrium relationships. The empirical results find that there exits an asymmetric cointegrated relationship between Shanghai A share index and Shenzhen A share index for the period from October 1992 to August 2001. The adjustment parameters of error correction term at Shanghai A share market are larger in bad-news regime than those in good-news regime. This result reveals investors at Shanghai possess over-reaction behavior on news of stock market. Moreover, there exists a bi-directional Granger causality between Shanghai A share index and Shenzhen A share index. We find there exists an asymmetric cointegrated relationship between Shenzhen A share index and Shenzhen B share index after 19 February 2001. Furthermore, the Shenzhen B share index leads Shenzhen A share index after 19 February 2001. The third article uses Pedroni's (2001) panel cointegration test to examine the validity of PPP hypothesis by two different price indces, i.e. Big Mac prices and CPI. Our panel observations include 14 countries from 1992 to 1999. The empirical evidence indicates Big Mac PPP and CPI PPP is supposed if we use nominal exchange rate as the explanatory variable. Nevertheless, the Big Mac PPP is valid but CPI PPP not valid if we use price level as the explanatory variable. Moveover, our concludtion does not influenced by productivity bias. Keywords: threshold vector autoregression, asymmetric cointegration, panel cointegration, stock markets, purchasing-power parity

本研究之宗旨在於探究中國大陸對亞洲區域內國家的金融市場影響程度之變化。由過去的各國股市日報酬率資料間相關程度與政策改變間的影響結果，來觀察是否未來在兩岸政策更開放下會使中國大陸對台灣的影響程度上升，進而使國際間投資組合的風險分散效果下降。本研究自DataStream選取台灣、香港、中國大陸、泰國、印尼、新加坡、馬來西亞、菲律賓、日本以及美國等十國的股價指數日資料，以對數轉換為日報酬率後年化加以分析。選取時間自1991年7月15日(中國大陸上海證券交易所股價指數公開後)至2008年12月31日。本研究選用的方法為使用風險值(VaR; Value at Risk)的概念來取代傳統的標準差，衡量以該十國所分別組成的各投資組合風險值變動情形；以及由風險值所衍生出的Diversification Benefit與Incremental VaR的結果。發現到僅由亞洲區域國家內組成的投資組合風險分散效果逐漸下降；且效果並不如有納入區域外國家(如美國)的投資組合。接著本研究將Gaussian Copula模型放入VaR中以增加對極端值的捕捉能力，結果發現本研究所選用的指數加權移動平均法所求得之相關係數已可有效反應出各國之間的相依程度，即加入Copula的效果有限。另外藉由Copula所求得之相關係數顯示，台灣、香港對中國大陸之間的相依程度已逐漸上升，並開始出現超越美國之現象，其中又以2005年為上升趨勢的起點。最後本研究以向量自我迴歸模型(VARs)來驗證2005年前後中國大陸股市對其他亞洲區域國家的影響力是否存在結構性的改變；並再佐以變異數拆解之方法來觀察2005年前後各國家之間自發性衝擊對彼此之間的影響程度變化。研究結果發現，透過VARs可證明中國大陸對亞洲區域各國的影響力在2005年後轉變為顯著；僅對美國不存在此一現象。另外變異數拆解的結果也顯示各國之間的相依程度在2005年後有明顯的上升，中國大陸對各國的影響程度亦然。透過本研究之結論，在未來兩岸將簽訂金融監理備忘錄使整合關係提升的環境下，需提醒投資人整合關係的上升將使得以之為標的之投資組合風險分散效果下降，需作為投資策略之考量。 / The object of this research is to find out the trend of dependence and correlation between China and other Asian countries. Based on past information about the relationship between equity markets’ correlation and changes in policies, this research can make suggestions to the foreseeable future of Taiwan and China whose relationship will be more solid due to new policy. The data of this research are gathered from DataStream, which includes Taiwan, Hong Kong, China, Thailand, Indonesia, Singapore, Malaysia, Philippines, Japan and United States. Selected from 1991/07/15 (when the Shanghai SE Composite went public) to 2008/12/31, this research calculates the annualized daily return using natural logarithms of two consecutive daily index prices. This research uses Value at Risk (VaR) to measure the risk exposure of portfolios formed by ten countries, and extends to the use of Diversification Benefit and Incremental VaR. The results found out that the diversification effects of portfolio which includes only Asian countries are decreasing and inferior to the effects when cross region countries are included. The second study of this research is to combine Gaussian Copula Model with VaR to capture the effects of extreme values. Empirical results found out that the VaR using Exponentially Weighted Moving Average method is good enough for analyzing Asian stock markets. The correlation in Copula model suggests that the dependence between Taiwan and China had increased since 2005 and has the increasing trend which might overwhelm the dependence between Taiwan and United States. Final research is about using Vector Autoregressions Model (VARs) to testify is there exist any structural change of dependence before and after 2005, and using Variance Decomposition to observe the relationships between these ten countries. The results found out that there exist structural change in 2005, the post-2005 periods shows that for Asian countries the effect from China are significant and greater than pre-2005 periods.

隨著網際網路的蓬勃發展，傳統的地理資訊系統也從早期的單機系統朝Web GIS的方向發展，但是關於地理資料的格式卻仍舊莫衷一是，沒有一個為業界所共同遵從的標準，其結果除了人力與財力資源的浪費，也造成不同單位間的地理資料整合上的困難。傳統的電子地圖採用點矩陣的圖形格式，因檔案太大而常造成資料傳輸上的延遲，而且圖形的解析度與品質不佳；此外在建置上十分不便，需要專門的處理軟體才能進行編輯修改。因此傳統GIS的處理方式已經不能滿足網路化的GIS應用系統的資訊需求。 　在XML出現之後，W3C與業界也體認到這樣的需求，因此新一代的網路二維圖形標準，可變動向量圖形（Scalable Vector Graphics，SVG）便應運而生，雖然目前SVG仍在候選建議階段，但鑑於它的諸多特點與優越性，目前已獲得業界各大公司的支持。本論文便在此種情況下產生研究動機，我們期望透過SVG這種新興的向量圖形格式，找出解決目前GIS在地理空間資料上所面臨的困境。經過本研究所實作出來的雛形系統顯示，以SVG作為新一代的Web GIS地理空間資料格式不但可行，而且突破許多傳統方式的瓶頸和缺點。 / With the development of Internet, traditional GIS was being changed from single user to Web GIS. But the file formats of geographic spatial data are still various. We don’t have a simple and effective standard. The result are financial and manpower resource wasting. It is inconvenient and difficult to integrate geographic spatial data between different GIS and organizations. Traditional maps are bitmapped format, with lower quality at high resulation. We have to use particular tools when modifying bitmaps. Therefore, traditional way in GIS should be improved. 　The Scalable Vector Graphics（SVG） format is a new XML grammer for defining vector-based 2D graphics of the Web and other applications. SVG was created by World Wide Web Consortium（W3C）, the non-profit, industry-wide, open–standards consorium. Over twenty organizations, including Sun Microsystems, Adobe, Apple, IBM, and Kodak, have been involved in defining SVG. SVG is a subset of XML, which is rapidly becoming the foundation for all modern Web applications. SVG gave us a motive to do the investigation. We hope to use the SVG format to solve the problems in GIS. In the result of the prototype system in our thesis, we find out that SVG should be the better, effective spatial data format of Web GIS.

近年來由於亞洲金融風暴的肆虐，產生經濟不景氣，使得失業的問題逐漸受到社會所關注，本論文企圖以三個時間序列方法：1.單變量ARIMA模型；2.轉換函數(TF)模型；3.向量自迴歸(VAR)模型來建立台灣地區的失業率時間序列預測模型。資料則是利用台灣地區民國75年1月至民國87年12月的失業率月資料作實證預測分析，為了知道資料是否來自時間趨勢模型，測試是否經過差分消掉一部份的記憶會發生預測的誤差，所以先以多步(multi-step)預測和一步(one-step)預測的方法計算出民國88年1月至88年12月預測值，而預測評估準則則採用(1)MAPE、RMSPE、MPE及泰爾不等係數(THEIL)；(2)變化方向誤差與趨勢變化誤差兩大方向來做預測比較。最後將算出的12期預測值與行政院主計處整體統計資料庫中所得到的失業率實際值利用預測評估準則做比較，結果發現一步預測法較多步預測法準確；而向量自迴歸模型(VAR)在大部份的預測期數上有較小的MAPE、RMSPE、MPE及THEIL值，因為此VAR模型考慮了在變數之間的共整合現象，有助於模型的預測，所以有較好預測的能力；反而是較複雜的ARIMA模型及轉換模型預測能力稍差一點。 / In this thesis, we plan to construct three time series models to forecast the Taiwan unemployment Rate. These time series models are ARIMA model、transfer function (TF) model and Vector Autoregressive (VAR) model. The data set consists of monthly observations for the period 75:1-87:12 for unemployment rate. We want to know if the data came from time trend model. First, we use multi-step forecasting and one-step forecasting to calculate 12 forecasted values from 88:01-88:12. Then We compare the prediction performance of these two methods by using：(1) MAPE、RMSPE、MPE and Theil’s Inequality Coefficient (THEIL)；(2) Direction of Change Error and trend Change Error etc. It is found that one-step forecasting is more correct than multi-step forecasting and the forecasting performance of VAR model is improved by explicitly taking account of cointegration between the variables in the model，so VAR model has lower MAPE、RMSPE、MPE and THEIL for most horizons. However，the more parsimonious ARIMA and transfer function models have higher MAPE、RMSPE、MPE for most horizons.

自1997年以降，受到亞洲金融風暴的衝擊，亞洲各國匯率巨幅波動，於是如何增進匯率預測的準確度已成為重要的研究課題。而自1973年布列敦森林體制崩潰，各工業國家改採浮動匯率以來，匯率巨幅波動致使國際收支理論不再能解釋匯率如何決定，於是1970年代，學者們紛紛提出各種匯率決定理論，其中以貨幣學派模型與資產組合平衡模型最受到重視。然而，自1978年始，這些結構模型的解釋能力逐漸受到質疑，在1983年Meese and Rogoff甚至提出結構模型的樣本外預測能力不如隨機漫步模型的樣本外預測表現，引起學者們的討論到底何者的樣本外預測表現較佳。而隨著計量方法的演進實證研究已由恆定的計量方法演進至非恆定的計量方法，在非恆定的計量方法方面，MacDonald and Taylor(1993、1994)、吳宜璋(1996)等人的研究皆採誤差修正模型來做預測。 本研究亦採誤差修正模型來做預測，但對其他學者的研究稍作改良：1.加入結構變動虛擬變數2.以向量誤差修正模型而非一條誤差修正的式子來做預測，在此以整個體系的觀點來做預測3.以背氏方法加入相驗情報來改善預測。 結論為在金融風暴發生期間，匯率受非基本面因素影響較大時，貝氏向量自迴歸模型預測表現較佳。而在金融風暴發生之前，匯率受基本面影響較小時，以貝氏向量誤差修正模型為良好的預測模型。 / This study improves other scholars' empirical studies by testing structure changes and by using Vector Error Correction Model to forecast N.T. Dollars. Futhermore,use Bayesian Method to improve predition .The conclusion is Bayesian VAR Model perform better when forecasting period include Asian finanl crisis . And Bayesian VECM Model is better model when forecasting period don't include Asian financial crisis.And the out of sample prediction performance of structure model is better than Random Walk Model.

傳統貨幣需求函數的估計，使用的影響因素包括物價、所得及利率。但是近年股市的蓬勃發展，對貨幣需求造成了一定程度的影響。 Friedman 就股市對貨幣需求的影響提出 4 大效果，分別是交易效果、資產組合調整效果、財富效果及替代效果。其中替代效果為負，其他的效果為正。然而並非只有股市會對貨幣需求造成影響，貨幣需求同樣會影響股市。本文採用 Johansen Procedure 估計法，首先建立一般的貨幣需求模型，使用的雙變數包括貨幣需求、物價、所得及利率，實證結果確定這些變數存在 2 條共積關係，一是貨幣需求共積方程式，一是物價共積方程式。然後我們將股市成交量放入，同樣確定這些變數間具有 2 條共積關係。 Johansen Procedure 有 5 種模型，分別適用於不同的情況，我們要事先由資料來判斷使用哪一個模型並不容易，因此本文採用了多項標準，包括共積係數符號及其大小、向量誤差修正模型誤差項常態性與序列相關檢定、重要統計值(RSS、AIC、SC)等，用來作為選擇最適模型的依據。經由實證結果我們發現，不論是否加入股市成交量，模型三都是最適當的模型，也就是資料有不為零的平均數與線性趨勢，但共積方程式只有截距項。 就貨幣需求共積方程式殘差對各變數的影響來看，M1A 與 M1B 的連續增加，都會使股市成交量擴大，而 M1B 的連續增加還會形成物價上漲的壓力。而就物價共積方程式殘差對各變數的影響來看，解釋上較不容易。這可能是因為台灣地區物價長期處於穩定，加上台灣股市受到心理及消息面的影響性很大，要用總體變數作一個完整的解釋並不十分容易。雖然如此，貨幣市場與股票市場間的互動仍然極具有研究價值。 / Traditionally, when estimating the money demand, we use price index, income, and interest rate as its influcing factors. But the stock market that is booming these years has made certain influence on money demand. Milton Friedman pointed out that there are 4 effects that stock market can influcnce money demand. They are trading effect, portfolio reconstruction effect, wealth effect, and subsitution effect. Among these effects, subsitution effect has negative influence on money demand and other 3 effects have positive influence on mondy demand. However, not only does the stock market has influence on mondy demand, money demand also has influence on stock market. In my thesis, I applied Johansen Procedure estimation method. First, I established a traditional model on money demand. The variables I used including money demand, price index, income, and interest rate. From the empirical outcome we are sure that there are 2 cointegration equations among these variables.One is the money demand cointegration equation and the other is the price cointegration equation. Next we add the stock trading volume to the model. We also make sure that there are 2 cointegration relationships among them. There are 5 models in Johansen Procedure estimation method, and they are applied in different situations. It is not easy to decide which model to apply in advance. So in the thesis, we used many criteria, including the value and the sign of the coefficients, the the serial correlation and the normality test of the residuals from the vector error correction model, and important statistics(RSS, AIC, SC) to decide which model to apply. According to the empirical outcome, whether stock trading volume is included, model 3, which is there are means and linear trend in data but the cointegration equation only has intercept is the proper model we selected. About the residuals from the money demand cointegration quation's influence on variables, we find that the continuous increase in M1A and M1B will make enlarge the stock trading volume. Besides, the coutinuous increase in M1B will cause the price to raise. And about the residuals from the price cointegration equation's influence on variables, it is a little bit difficult to interpret. Maybe it is because the price is very stable in Taiwan and the stock market in Taiwan is affected by psychology side and information side easily. So it is not easy to use the macro economic variables to interpret fully. Althought it is the case, the interaction between the money market and the stock market still worth researching.

本文是探討管理浮動匯率時期（1978年第三季至1993年第三季），台灣地區經常帳盈餘發生的原因，同時考慮匯率因素、貨幣市場及商品與勞務市場吸納的情況。利用兩個向量自迴歸模型，分別納入：(1)匯率、利率、經常帳、消費節約及貨幣供給，(2)匯率、利率、經常帳、財政盈餘及貨幣供給，藉由因果關係檢定、預測誤差分解、及衝擊反應，分析經常帳失衡的原因。 　　實証結果指出：台灣地區經常帳盈餘，深受匯率、財政盈餘及消費節約的影響，這個結論與我國低估幣值與出口拓展的政策一致。且經常帳盈餘並不能夠顯著的影響貨幣供給，這個結論與央行沖銷的措施一致，其目的無非是要隔離國外部門影響國內貨幣。足見自由化的匯率政策，不但讓匯率反應出合理的水準值，同時可追求獨立的貨幣政策，配合著獎勵投資、消費及增加公共支出，增加國內吸納，藉以減少鉅幅的經常帳盈餘。

本研究的目的在探討台灣貨幣市場短天期利率衍生性金融商品（30天期商業本票利率期貨、90天遠期利率協定〈以下簡稱FRA〉）對其即期利率（30天期商業本票利率、90天期商業本票利率）之『價格發現』功能。可由兩方面來檢定利率遠期協定或利率期貨市場之『價格發現』功能：（1）市場效率性：FRA、利率期貨價格可否作為未來到期日時即期利率之不偏預期；（2）FRA、利率期貨與即期利率價格間之領先-落後關係。 選取各交易日的日資料作為觀察值。在研究方法上採用ADF單根檢定、效率性檢定、向量自我相關模型（VAR）、Granger因果關係檢定、誤差正交檢定、共整合檢定、誤差修正模型。 結論結果發現，90天遠期利率協定（FRA）對90天期商業本票利率進行『價格發現』的分析，以「市場效率性檢定」的結果顯示此市場無效率，亦即無『價格發現』，可能是因為買FRA的機構投資人目的不是持有到到期，僅為判斷短期利率走勢方向，可能買個幾天欲賺取差價利潤，所以非為未來現貨價格的不偏預期；以「領先-落後關係分析」，顯示其無『價格發現』，此一結果的可能解釋是由於台灣FRA市場非集中市場公開交易，交易量尚不及現貨市場。因此市場資訊的不透明可能使遠期契約價格不如現貨價格般具代表性。 30天期商業本票利率期貨對30天期商業本票利率進行『價格發現』的分析，以「市場效率性檢定」結果顯示在到期日前適當的期間（24~36天）此市場具有效率性，即存在『價格發現』；而「領先-落後關係分析」結果則無明顯的領先落後，不具有期貨領先現貨的『價格發現』，此部分我們可能提出的解釋為：在30天期商業本票利率期貨剛推出不久，一般市場上的交易者大多是從事避險交易，鮮少進行投機行為，所以不具有短天的領先落後關係，其顯示價格發現是在考慮市場存在風險溢酬下，到期前24~36天的利率期貨價格是未來現貨價格的預期。

給定兩個隨機變數的條件機率矩陣A和B，相容性問題的主要課題包 含：(一)如何判斷他們是否相容？若相容，則如何檢驗聯合分配的唯一性 或找出所有的聯合分配；(二)若不相容，則如何訂定測量不相容程度的方 法並找出最近似聯合分配。目前的文獻資料有幾種解決問題的途徑，例 如Arnold and Press (1989)的比值矩陣法、Song et al. (2010)的不可約 化對角塊狀矩陣法及Arnold et al. (2002)的數學規劃法等，經由這些方法 的啟發，本文發展出創新的特徵向量法來處理前述的相容性課題。 當A和B相容時，我們觀察到邊際分配分別是AB′和B′A對應特徵值1的 特徵向量。因此，在以邊際分配檢驗相容性時，特徵向量法僅需檢驗滿足 特徵向量條件的邊際分配，大幅度減少了檢驗的工作量。利用線性代數中 的Perron定理和不可約化對角塊狀矩陣的概念，特徵向量法可圓滿處理相 容性問題(一)的部份。 當A和B不相容時，特徵向量法也可衍生出一個測量不相容程度的簡單 方法。由於不同的測量方法可得到不同的最近似聯合分配，為了比較其優 劣，本文中提出了以條件分配的偏差加上邊際分配的偏差作為評量最近似 聯合分配的標準。特徵向量法除了可推導出最近似聯合分配的公式解外， 經過例子的驗證，在此評量標準下特徵向量法也獲得比其他測量法更佳的 最近似聯合分配。由是，特徵向量法也可用在處理相容性問題(二)的部份。 最後，將特徵向量法實際應用在兩人零和有限賽局問題上。作業研究的 解法是將雙方採取何種策略視為獨立，但是我們認為雙方可利用償付值表 所提供的資訊作為決策的依據，並將雙方的策略寫成兩個條件機率矩陣， 則賽局問題被轉換為相容性問題。我們可用廣義相容的概念對賽局的解進 行分析，並在各種測度下討論賽局的解及雙方的最佳策略。 / Given two conditional probability matrices A and B of two random variables, the issues of the compatibility include: (a) how to determine whether they are compatible? If compatible, how to check the uniqueness of the joint distribution or find all possible joint distributions; (b) if incompatible, how to measure how far they are from compatibility and find the most nearly compatible joint distribution. There are several approaches to solve these problems, such as the ratio matrix method(Arnold and Press, 1989), the IBD matrix method(Song et al., 2010) and the mathematical programming method(Arnold et al., 2002). Inspired by these methods, the thesis develops the eigenvector approach to deal with the compatibility issues. When A and B are compatible, it is observed that the marginal distributions are eigenvectors of AB′ and B′A corresponding to 1, respectively. While checking compatibility by the marginal distributions, the eigenvector approach only checks the marginal distributions which are eigenvectors of AB′ and B′A. It significantly reduces the workload. By using Perron theorem and the concept of the IBD matrix, the part (a) of compatibility issues can be dealt with the eigenvector approach. When A and B are incompatible, a simple way to measure the degree of incompatibility can be derived from the eigenvector approach. In order to compare the most nearly compatible joint distributions given by different measures, the thesis proposes the deviation of the conditional distributions plus the deviation of the marginal distributions as the most nearly compatible joint distribution assessment standard. The eigenvector approach not only derives formula for the most nearly compatible distribution, but also provides better joint distribution than those given by the other measures through the validations under this standard. The part (b) of compatibility issues can also be dealt with the eigenvector approach. Finally, the eigenvector approach is used in solving game problems. In operations research, strategies adopted by both players are assumed to be independent. However, this independent assumption may not be appropriate, since both players can make decisions through the information provided by the payoffs for the game. Let strategies of both players form two conditional probability matrices, then the game problems can be converted into compatibility issues. We can use the concept of generalized compatibility to analyze game solutions and discuss the best strategies for both players in a variety of measurements.