本研究以新台幣兌美元之匯率日資料作為主要研究標的，同時加入台灣加權股價指數及金融業隔夜拆借利率之日資料作為股價與利率之代理變數，利用Beveridge-Nelson分解趨勢的方法將變數資料拆解成趨勢項與循環項之時間序列資料，藉此捕捉匯率資料具有景氣循環的特性。在循環項的序列資料，以向量自我迴歸模型來分析並予以估計，趨勢項的部分，利用共整合檢定來探討趨勢項變數間長期的均衡關係，再以向量誤差修正模型予以估計，得到未來30天期之匯率走勢。接著，再以RMSE與MAE指標來衡量不同模型之匯率預測績效，以期能找出最適之匯率預測模型。 實證研究結果發現，將匯率資料先透過Beveridge-Nelson分解趨勢的方法予以拆解後，再利用時間序列模型進行分析及預測，時間序列模型的預測能力都比原始匯率利用時間序列模型進行預測或透過ARIMA模型進行預測還要來的好。因此，根據實證研究的結果，若企業與政府在進行匯率預測的分析時，能夠考慮先將匯率資料透過Beveridge-Nelson分解方法予以處理，便能更有效提升模型的預測能力，除了企業能夠降低避險成本來提高公司整體績效，對於國家而言，有效的掌握匯率的趨勢便能夠迅速且正確的制定政策，提升國家的經濟發展。

本研究計畫探討以RN神經網路模型預測國內債券價格的效度。目前一般用於財務預測的神經網路論著主要為BPN模型，惟BPN模型有其限制，所以本研究計畫將（1）分析比較統計計量模型，BPN神經網路，RN神經網路系統對國內公債價格之預測績效。（2）分析不同時期的預測能力，找出景氣和預測變數的關係，同時將比較各個時期統計計量模型和神經網路模型是否同時有效， 抑或有些有效， 有些無效，以探討各工具是否具有互補性或替代性。並探討預測績效是否受到背後經濟環境的影響。 我們研究對象為國內公債，其每日交易資料取樣時間自民國八十一年開始。影響債券價格的因素可拆解成實質利率，預期通貨膨脹率和風險貼水三層面，本研究總體變數之選取，亦循此三項範疇以求周延。 本研究之研究成果對理論及實務應用將有下列三項預期貢獻：（1）比較不同其常的債券在不同景氣狀況下，各不同預測模型的預測效度差異，探討各時期各工具之預測能力，可提供投資實務界對預測工具之選擇，應用與搭配。（2）對債券報酬率預測研究，分析總體變數，利率風險等變數對債券報酬率的影響，可進一步暸解影響債券價格的相關因素及程度。（3）以往神經網路應用在財務預測領域上， 皆以BPN 神經網路為主，此處引進RN神經網路，比較兩者的表現，可提供學術理論界之驗證。 / This research project empirically investigates the accuracy of Reasoning Neural Networks (RN) in forecasting Taiwan's bond prices. We explore (1) the relative predictive abilities of Vector Error Correction Model (VECM), which serve as a representative econometric model, Back Propagation Neural Networks (BPN), which is adopted by most current studies in the application of neural networks in finance, and RN, and (2) th3 potential variations in the three models' predictive power in different phases of economic cycle. Specifically, we aim to study if the three models substitute or complementone another. In addition, we explore the extent to which the relativepredictive abilities of the three models varies with underlying macroecomonic factors. The explanatory variables adopted in this study include all potential drives to (real) risk-free rate, expected inflation rate, and riskspremiums. In this study, we examine the government bond terms to maturity,coupon rate, and prices of government bonds during 1992-1995. This project would contribute to both academic and application researchin the following three aspects : (1) Few, if any , prior study explores whether and how various neuralnetworks and/or eco- nomic models perform under different macro-economicvariables. Our empirical results may indicate an appropriate model ( ormodels ) to improve forecasting of bond prices. (2) This study shows how RN, BPN, and VECM models perform in forecastinggovernment bonds yields to maturity. (3) The BPN model prevails in financial forecasting. Nevertheless, BPNis subject to a few short comings and may thus be a sub-optimal model. This study analyzes if RN is more cost-effective in forecasting bond prices than BPN.

本篇主要為原物料指數與總體經濟物價間動態關聯性的研究。由於近年來糧食價格高漲，本研究選取CRB現貨指數（Commodity Research Bureau）、CCI期貨指數（Continuous Commodity Index），與CRB農產品指數為原物料指數以觀察原物料價格對總體面物價影響的程度；研究期間為2001年10月至2011年3月；總經物價指標選擇生產者物價指數（PPI）、消費者物價指數（CPI）、再加上國內生產毛額（GDP）；選取的國家為美國、臺灣與中國。本研究以Johansen共整合、向量自我迴歸模型、向量誤差修正模型、Granger因果關係檢定及衝擊反應分析等方法，探討三項原物料指數與總體經濟指標的互動關係。 研究結果顯示，原物料指數與總體指標之間的長期均衡關係不明顯。因果檢定顯示，CCI指數在因果檢定上領先CRB指數與CRB農產品指數；除了美國的GDP之外，CCI指數也領先各項總體經濟指標，但不論是CRB現貨指數或CRB農產品指數，對總經物價指標的領先-落後關係都不明顯，表示在CCI指數為較佳的預測指標。由衝擊反應分析的結果顯示，除了有共整合關係的變數間相互影響為長期性之外，受影響的物價指標僅在短期內會受到原物料價格變動的影響：總體物價指標面對原物料價格波動的反應約3期之後反應便逐漸消失，顯示原物料價格與總體物價指數之間的短期失衡期間並不長。 / This paper investigates the relationship between the commodity indexes and macroeconomic price indexes. Due to the sharp increase of food price in recent years, we add CRB index (Commodity Research Bureau), CCI index (Continuous Commodity Index), and CRB foodstuffs index in the research to see the magnitude of commodity price indexes to macroeconomic price indexes. This paper selects United State, Taiwan and China as samples and manages to find out the relationship of commodity indexes and macroeconomic price indexes by applying monthly data from October 2001 to March 2011. Macroeconomic price indexes are PPI (Producer Price Index), CPI( Consumer Price Index) and plus GDP Index. This paper tries to get the answer by applying Johansen Cointegration Test, Vector Autoregression Model(VAR), Vector Error Correction Model (VECM), Granger causality test and Impulse Response Analysis. The result does not show obvious long-term relationship between commodity price indexes and macroeconomic price indexes; and Granger causality test exhibits that CCI index takes the lead in the change of time. But we do not get consistent result between CRB index, CRB foodstuffs index and macroeconomic price indexes in Granger causality test which means commodity spot indexes do not necessarily lead in the change of time. This result implies that CCI index a better indicator in forecasting. According to Impulse Response Analysis, macroeconomic price indexes are influenced by commodity index only in a short period of time and this result tells us that the disequilibrium between commodity indexes and macroeconomic price indexes will not last long.

自行車一詞儼然成為綠色環保的代名詞之一，台灣自行車業過去在國際間，被認定為品質粗糙的產品，在經過多年努力的情況下，台灣自行車業不斷的備受肯定，隨著近年全球暖化議題、全球性健康概念、油價飆漲、金融海嘯爆發等，諸多原因造成自行車從不被看好的代步工具，演變到現在成為休閒運動工具的轉變，其中；台灣自行車2008年的金融海嘯中，相較於其他傳統產業，不論是出口產值或是股價不降反漲，大舉逆勢成長，其中巨大(Giant)、美利達(Merida)、愛地雅(Ideal)，成車製造商，近年來分別占出口前三大。 所以本研究要探討，金融海嘯爆發的前後，對台灣自行車業帶來的影響，研究資料選定為2000年1月至2013年12月間的巨大股價(9921)、美利達股價(9914)、愛地雅股價(8933)、台灣股價加權指數(TWII)、原油價格、工業生產指數的月資料，共168筆。透過單根檢定檢測資料是否為定態，利用共整合檢定確定是否含有至少一組解，搭配向量誤差修正模型檢測變數間的長短其關係，在利用複迴歸模型檢測。 研究結果顯示，巨大、美利達、愛地雅和台灣加權股價指數具有顯著關係，由於台灣自行車屬於出口導向以及中高價位產品，故全球景氣對台灣自行車業深具影響。其中，巨大和美利達除了ODM外，亦有自有品牌在全球銷售，愛地雅定位專業ODM專業代工廠，前者發展不同市場。 / The word "bicycle" has become one of the pronouns of environmental protection. In the past, Taiwan bicycling industry was treated as low-quality products internationally. With long-time effort, Taiwan bicycling industry was highly appreciated. Recently, global warming issue, cosmopolitan health sense, dramatically increased oil price, the eruption of financial crisis, and many reasons lead the bicycles have not positively evaluated as means of transportation. Now, it becomes the outdoor recreation mean. Comparing Taiwan bicycling industry with other traditional industry, it doesn't fall down but highly increase no matter export value or stock price. The manufacturer of Giant, Merida, and Ideal are the top 3 of export recently. So this study want to explore the things happened before and after the outbreak of the financial crisis that affects bicycle industry in Taiwan, research data for selected between January 2000 and December 2013, relationship between the Giant(9921) shares, Merida (9914) shares, Ideal(8933) shares, TWII, the price of crude oil, industrial production index. Through the Unit Root Test to test whether the data is the steady state or not. By using cointegration test to make sure whether contains at least one group of solutions and vector error correction model to detect the length of the relationship between variables, and using the multiple regression model to test. Results of the research shows that Giant, Merida, Ideal has significant relationship with TWII, because Taiwan bicycle are export-oriented and high price products, so the global boom has profound influence to Taiwan bicycle industry, among them, the Giant and Merida except the ODM, have their own brands in global sales, Ideal professional locate, ODM professional contract, the former develops different markets. / 摘要 I Abstract II 謝辭 III 目錄 IV 圖目錄 VI 表目錄 VII 第一章　緒論 1 第一節　研究動機 1 第二節　研究目的 3 第三節　巨大機械工業股份有限公司簡介 4 第四節　美利達工業股份有限公司簡介 5 第五節　愛地雅工業股份有限公司簡介 6 第六節　研究架構 7 第二章　文獻回顧 9 第一節　國內相關文獻 9 第二節　國外相關文獻 11 第三節　國內外文獻一覽表 12 第三章　研究方法 20 第一節　單根檢定 20 第二節　共整合檢定 22 第三節　向量誤差修正模型(VECM) 24 第四節　迴歸分析 24 第四章　實證分析 26 第一節　資料來源與處理 26 第二節　敘述統計 31 第三節　單根檢定 32 第四節　共整合檢定 33 第五節　向量誤差修正模型(VECM) 33 第六節　複迴歸模型 35 第五章　結果分析與建議 38 第一節　結果分析 38 第二節　建議 39 參考文獻 40 附錄一　巨大工業股份有限公司沿革 43 附錄二　美利達股份有限公司沿革 47 附錄三　愛地雅股份有限公司沿革 57 圖目錄 圖1-6 研究架構 8 圖4-1-1 台灣自行車業總出口產值(百萬元，美金) 27 圖4-1-2 台灣股價大盤指數(TWII，當日收盤價) 27 圖4-1-3 巨大股價(9921，當日收盤價) 28 圖4-1-4 美利達股價(9914，當日收盤價) 28 圖4-1-5 愛地雅股價(8933，當日收盤價) 29 圖4-1-6 國際原油價格(西德州，美元) 29 圖4-1-7 台灣工業生產指數 30 表目錄 表1-3 巨大公司基本資料 4 表1-4 美利達公司基本資料 5 表1-5 愛地雅公司基本資料 6 表2-3 國內外相關文獻整理 12 表4-1 資料來源一覽表 26 表4-3-1 ADF 單根檢定 32 表4-3-2 單根檢定-一階差分 32 表4-4-1 共整合檢定 33 表4-5-1 Giant & Merida　向量誤差修正模型 34 表4-5-2 Giant & Ideal　向量誤差修正模型 34 表4-5-3 Merida & Ideal　向量誤差修正模型 34 表4-6-1 自行車產業與景氣循環對巨大股價之影響 37 表4-6-2 自行車產業與景氣循環對美利達股價之影響 37 表4-6-3 自行車產業與景氣循環對愛地雅股價之影響 37

過去許多學術文獻針對租稅優惠吸引投資之效果進行實證分析，但實證結論並不一致。我國自1950年即開始實施一連串的租稅獎勵政策，時至今日，租稅減免仍是我國政府推動重大經濟政策慣用的誘因手段。為探討了解臺灣實施租稅優惠措施對投資變化之影響，本研究針對我國自民國50年代後期以來涉及租稅減免之相關法令進行整理，另為了充分量化這些租稅優惠措施，則參考國外相關實證文獻作法，建構了兩項租稅誘因指標作為虛擬變數，來追蹤自民國61年以來我國不同階段之減免稅狀態，並作為虛擬變數納入後續實證模型分析。 本研究利用相關變數之時間序列資料來探討租稅優惠對我國外人直接投資與國內私人投資之互動變化關係。研究步驟有三，首先，針對個別變數進行單根檢定，藉以確認變數的屬性，了解時間序列資料是否為衡定後，再利用Johansen共整合檢定法來估計和檢定多個變數，確認各變數間是否存在共整合關係後，以誤差修正模型來說明各變數間關係與整個變數脫離均衡關係後之動態調整情形。 實證結果顯示，就長期趨勢而言，我國實施之租稅優惠措施對吸引外人直接投資呈現負向且顯著之不良影響，另長期而言，租稅優惠誘因對刺激我國國內投資之變化確有顯著且正面助益，但影響效果之幅度不大。因此，本研究建議政府與其提供效果不明確之租稅誘因，不如致力於針對國家自身不完善的基礎建設或不穩定的總體經濟環境進行改善。 / Tax incentives have been in existence in Taiwan since 1950, and they are still very much on the agenda of the government. There is no agreement about the efficacy of incentives. Indeed there have been doubts about whether incentives have any effect on the economy since the 1950s. This has made some economists wonder why incentives are so popular despite the fact that their effects are either slight or unknow. This study conducts an empirical investigation of the impact of tax incentives on investment in Taiwan. We constructed two indexs of tax incentives which track the different types of incentives embarked upon by the government, and these indexes are then included in both foreign direct investment and private investment equations. Our testing procedure involves three steps. The first step involves tasting for the properties of the variables by conducting unit root teste. The second step involves testing for the long-run relationship between the variables using Johansen cointegration tests. And the third step involves estimating the long-run parameters and associated loading factors. The empirical results shows a significant negative impact of tax incentives on FDI, and a significant positive impact of tax incentives on private investment but the impact is slight. We suggest that rather than focusing on tax incentives, the country should concentrate on removing the factors that discourage investors such as poor infrastructural and institutions or macroeconomic instability.

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.

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.

本研究目的在於探討投資等級債券信用價差是否存在外溢效果。信用價差是建構各種信用衍生性金融商品的基礎，惟目前學術界及業界都著眼在信用價差的拆解。信用價差可拆解成預期違約損失、稅的溢酬及信用風險溢酬。投資等級債券的信用價差來自於預期違約損失、稅的溢酬的部分較少，絕大多數來自於信用風險溢酬。信用風險溢酬係系統性影響信用價差的因素，此因素造成不同投資等級債券的信用價差間具有共整合的現象，進而引發外溢效果。然而並無人對於信用價差外溢效果作一深入探討。本研究利用目前學術界盛行的Panel模型的研究方法，對各種投資等級的債券的信用價差進行Panel Unit Root Tests、Panel Cointegration Tests及Panel Spillover Effect Tests，以求發現債券信用價差外溢效果存在與否的證據。 本文以iBoxx Index成份債券作為研究標的，利用Panel研究方法得到以下結論: 1.根據研究結果顯示，各種信評等級的債券的信用價差存在單根問題。 2.不同投資等級信評債券的信用價差擁有共整合關係。 3.不同投資等級信用評等的債券間信用價差外溢效果存在。且愈是相 鄰信評等級債券的外溢效果愈為顯著，例如BBB等級信用價差發生變動引發信評AAA等級信用價差變動的幅度便沒有AA等級信用價差變動引發AAA等級信用價差變動來得強烈。外溢效果係不對稱，當最高投資等級信評發生變動時，最低投資等級債券變動最為激烈;而最低投資等級信評發生波動時，最高投資等級債券發生變動的幅度就較小。 4.本研究支持不同債信評等的債券存在同向的外溢效果。 / This paper investigates the spillover effect in the investment grade bonds using the recently developed Panel Unit Root Tests, Panel Cointegrations Tests, Panel FMOLS and Panel DOLS techniques. Investment grade bonds’ credit spreads are found to be nonstationary and to be cointegrated in panels. This paper finds evidence of spillover effects.

台灣不動產投資信託（T-REITs）自2005年發行至今已逾六年，然其市場表現仍不如發行之初所預期。過去國內已有許多研究針對T-REITs市場發展進行探討，然而目前就T-REITs與直接不動產投資市場價格表現間之相關研究尚付之闕如。有鑑於此，本研究藉由共整合與Granger因果關係檢定，檢視REITs與直接不動產市場間之關聯性，了解台灣與美國之REITs市場表現差異及其影響因素，進而作為改進T-REITs運作機制或架構之參考依據。 實證結果發現，美國之REITs與直接不動產市場之間存在共整合關係。此結果表示，長期而言，這兩者可能具有相似之風險分散效益。此外，透過Granger因果關係檢定發現REITs領先於直接不動產，乃因前者市場較具效率。另一方面，台灣之REITs與直接不動產市場之間則不具有共整合以及領先或落後關係，然直接不動產當期價格仍會受到本身與REITs之前期價格影響。 本研究進一步分析台、美兩國實證結果之差異原因如下：資料的樣本期間、REITs市場規模、存在於T-REITs市場之集中性風險以及潛在的代理問題。其中，針對T-REITs潛在代理問題，本研究藉由分析股票與T-REIT報酬率之波動性，發現T-REIT之不動產管理機構若與母集團相關者，則其市場表現較差。因此，我們得出T-REITs市場發展主要是受限於代理問題之結論。本研究成果不僅有助於改善T-REITs市場效率，亦可提供學術與實務之參考。 / The mechanism of Real Estate Investment Trusts in Taiwan (or T-REITs) was launched in 2005, however, T-REITs market did not perform as expected. What caused the limited development of T-REITs market? Current literature on the performance between T-REITs and direct real estate investment is limited. Through the cointegration and Granger causality tests, the purpose of this study is hence to explore the short-term and long-term dynamics between REITs and direct real estate markets in the U.S. and Taiwan, respectively. This study presents evidence of the cointegration relationship between REITs and direct real estate in the U.S. It implies that the diversification properties of these two assets are likely to be similar over the long horizon. According to the Granger causality test, REITs leads direct real estate due to the market information efficiency. These findings are consistent with those of previous studies. On the other hand, we find no cointegration and lead-lag relation between T-REITs and commercial real estate. Moreover, the current commercial transaction price is affected by both its and T-REIT previous price. By comparing the difference between the results of these two countries, there are several possible explanations for the different results between the U.S. and Taiwan, including difference in sample period, market capitalization, concentrated risk, and most importantly, the potential agency problem existing in T-REITs market. Finally, the underperformance of parent-related management T-REIT is verified through the volatilities of stock and T-REIT returns. Therefore, we conclude that the limited development of T-REITs is caused by the agency problem in REITs market. Results of this study may provide T-REITs market for improving its efficiency, as well as for the reference for both academics and real practices.