本文使用 1981 年 1 月 5 日至 1997 年 5 月 31 日台灣加權股價指數以及交易股數的資料探討台灣股市的時間序列特性，並且針對政府對股市的干預政策檢定政策干預的有效性。本文採用的實證方法包含 Augmented Dickey-Fuller(ADF)單根檢定，Perron 結構性改變檢定， ARCH 效果檢定，干預分析(Intervention Analysis)以及 Granger 因果關係檢定。實證檢定的結果如下： 1、在單根檢定方面，股價指數、交易股數和股價指數變異數三個時間序列都是一階穩定序列。 2、在 Parron 結構性改變檢定方面，股價指數、交易股數和股價指數變異數三個時間序列在 1990 年 5 月到 10 月之間曾經發生明顯的結構性改變。 3、在 ARCH 效果檢定方面，股價指數和交易股數二個時間序列的殘差項都有 ARCH(1)效果存在，而股價指數變異數的殘差項不存在 ARCH(1)效果。 4、在干預分析方面，穩定基金對股價指數的干預效果不顯著。 在漲跌幅限制方面，漲跌幅限制的變動對股價指數、交易股數及股價指數變異數的干預效果都不明顯。 在證卷交易稅稅率改變的干預分析方面，證卷交易稅稅率改變對交易股數和股價指數變異數沒有影響，但是證交稅稅率變動和股價指數呈現正向的關係。 5、在 Granger 因果關係檢定方面，本研究發現漲跌幅限制改變和股價指數漲跌二者互為因果，但是股價指數對漲跌幅的影響較大。 在證卷交易稅稅率改變與股市的因果關係方面，本研究發現股價指數的漲跌是證交稅稅率改變之因，顯示主管機關的證交稅稅率政策是受股市的市場狀況所左右。 / In this paper, I examine the effectiveness of official intervention in Taiwan's equity market. I consider the security transaction tax, price limit and stabilization funds as examples. The nonstationarity and structural changes of equity index time-series process were first detected and detrended. The Autoregressive Conditional Heteroskedasticity (ARCH) model is employed to examine the intervention effectiveness, since it allows for a formal test of changes in the index mean level, index conditional variance or both, in response to the changes of security transaction tax and price limit. The results implies that policy authority adjusted security transaction tax and price limit in accordance to the change of equity index level. I also find that the imposition of security transaction tax and price limit have no significant effect on reducing the equity index volatility.

由於住宅價格變動毫無預警制度，人民往往憑著個人主觀的判斷而決定何時購屋或售屋，而此種主觀判斷住宅市場利多及利空的觀念，對住宅市場的供需會產生失衡現象，因此是否可從經濟面的訊息找到住宅價格變動的答案，使住宅價格在尚未變動前，政府即已掌握資訊，提前做好穩定住宅價格的因應對策，使民眾依其需要而購屋，則是本研究之主要目的。 　　本研究從文獻中整理出影響住宅價格變動的七個總體經濟變數，這些總體經濟變數包含工資、物價、所得、貨幣供給額、股價、匯率及利率等，並利用向量自我迴歸模式(VAR)進行實證，以便較客觀的獲得變數間的落後期數及暸解變數間雙向、單向及領先、同步、落後情形，且進一步探討住宅價格與每一個總體經濟變數間影響程度大小及影響情形，以釐清各變數之間的關係。 　　本研究利用VAR模型進行住宅價格與總體經濟變數關係的研究，經由實證，得到下列的結論： 　　一、實證結果方面 　　本研究之實證主要有因果關係檢定與分析、變異數分解之分析及衝擊反應之分析三方面，其實證結果如下所述。 　　（一）因果關係檢定與分析 　　由因果關係檢定與分析中，得到股價、物價、匯率、貨幣供給額及利率均能做為住宅價格變動的領先指標。 　　（二）變異數分解之分析 　　由住宅價格之變異數分解中，得知住宅價格自身的解釋程度僅占三分之一，另三分之二被其他的總體經濟變數所解釋，顯示住宅價格受總體經濟變數的影響相當大；而從其他總體經濟變數之變異數分解中，得知住宅價格變動會干擾到總體經濟變數，而使總體經濟變數受干擾而變動變動。 　　（三）衝擊反應之分析 　　從總體經濟變數對住宅價格的衝擊反應分析圖中可以明顯看出除工資外，其餘總體經濟變數變動對住宅價格造成的衝擊均相當明顯，但匯率及利率對住宅價格的衝擊是負向的。 　　住宅價格對所得、股價、匯率及利率的衝擊相當明顯，而其對匯率的衝擊是負向。 　　二、政策應用方面 政府的決策過程中常會有時間落後的現象，而本研究實證的目的則是要使政府能事先掌握住宅價格的變動，並提前做好穩定住宅價格的因應對策，減少政府決策過程的時間落後現象，而實證結果應用至政策方面的內容則由以下說明之。 　　（一）藉由因果關係檢定與分析的實證內容，可以縮短政府對住宅價格不合理變動問題認定落後的時間。 　　（二）從變異數分解之分析的實證內容中，可以使決策者在解決住宅價格問題時，將行動落後的時間減少。 　　（三）由衝擊反應之分析中，可以使政府在執行穩定住宅價格政策時，將衝擊落後的時間縮小。 / Since there is no alarm system in the change of housing prices, people often decide when to buy or when to sell based on personal and subjective judgement. Such concept to judge subjectively whether the housing market is bull or bear will cause unequilibrium in the supply and demend of the housing market. There it is possible to find out the answers to the change of housing prices from economic side so that the government can have enough information and can be prepared in the reaction to stabilizing the housing prices, and so that the public can buy house according to their needs is the main purpose of this project. 　　Seven variables in macroeconomics influencing the change of housing prices have been taken from reative literature, including wage, commodity price, income, money supply, stock price, exchange rate, and interest rate. VAR has been employed to verify so that the more objective lagging period among variable can be known, and the bi-directional, uni-directional, leading, contemporaneous, and lagging situation among variables can be understood. Furthermore, the degree and the status of influence of each macroeconomic variable to the housing price will be investigated to clarify the relations among the variables. 　　The present project investigate the relations between housing price and macroeconomic variables. We have the following findings: 　　I、In Empirical Study: 　　The empirical study in this project includes causal relation test and analysis, the analysis of variable decompositon, and the analysis of impact response. The results are shown in the following: 　　(I) Causality Test and Analysis 　　In the causality test and analysis, we find out that stock price, commodity price, exchange rate, money supply and interest rate all can be the leading indicators in the change of housing prices. 　　(II) The Analysis of Variable Decomposition 　　It is learned from the variable decomposition of housing prices that housing price can only explain one third of the cause in its change, the other two thirds are explained by other macroeconomic variables. It shows that housing prices are subject to the influence of macroeconomic variables greatly. 　　From the variable decomposition of other macroeconomic variables, we know that the change in housing prices will affect macroeconomic variables so that the macroeconomic variables will change. 　　(III) The Analysis of Impact Response 　　It can be obviously seen from the analysis figure of the impact response of the macroeconomics to housing prices, all macroeconomic variables will cause obvious impact to housing prices expect for wage. However, both exchange rate and interest rate have negative impact to housing prices. 　　Housing prices' impact to income, stock prices, exchange rate and interest rate is quite obvious, among which, the impact to exchange rate is negative. 　　II、Policy Application 　　It is a common phenomenon that there often will be lagging in time in government's decision making. The purise of the empirical study in this project is to let the government to know in advance the change of housing prices and to let the government to know in advance the change of housing prices and to let the government be prepared in the reaction of stabilizing the housing prices to minimize the lagging in the decision making process. The contents of application of the empirical study to policy are explained in the following: 　　(I) With the empirical results of the change of the causality test and analysis, the time for the government to recognize the unreasonable changes in housing prices can be shortened. 　　(II) With the empirical results of the analysis of variable decomposition, the decision makers' lagging in the action responding to housing pricescan be minimized. 　　(III) With the analysis in impact response, the lagging in impact will be minimized when the government executing her housing price stabilizing policy.

為了瞭解台灣地區貨幣總計數與經濟活動（如物價、所得）間，是會受到 金融自由化、國際化之影響，故在研究體系中，納入傳統貨幣需求函數中 ，所未放入之變數－－匯率，藉以進一步了解變數間的互動。本文採用 Johansen and Juselius (1990,1992) 發展之共整合分析，以最大概似法 估計共整合向量; 並利用概似比檢定法導出共整合向量個數之檢定統計量 ，及其極限分配；再利用 Johansen 法對匯率進行「弱外生性」檢定； 最後仍利用Granger(1969,1980,1988) 所提出之Granger Causality之觀 念，來探究何種貨幣總計數對GNP 平減指數具有較佳之解釋能力。依據本 文之實證結果，在選擇作為貨幣政策中間目標之指標變數時， M1B 或M1 C 較 M2 及 M1A 為佳。 / The relationships between money aggregates, price, income, interest rate and exchange rate in Taiwan has been investigated in this paper. The Johansen procedure is adopted to estimate cointegration vectors between these variables. Further, weak ex- ogeneity of variables is also tested by way of Johansen procedu- re. Finally, the Granger causality of money and price is invest- igated fo the sake of understanding of predictibility. Main res- ults of this paper can be summarized as follows: First, the nar- row money aggregates, say M1A, M1B and M1C, are closer related to price than M2; M2 is closer related to real GNP than narrow money aggregates. Second, the inclusion of exchange rate and in- terest rate facilitates cointegration relationships between var- iables. Third, the statement "money Granger cause price" is more adequate than "price Granger cause money" in Taiwan. According to above conclusions, it is reasonable to say that M1B and M1C could be better intermediary indicators than M2 for monetary po- licies of stablizing domestic price.

本文利用晚近發展出來的單根檢定法以及共積檢定法，實証分析美、日兩國二次大戰以後企業購併與總體經濟變數間之關係。其實証方法與實証結果如下：運用ADF 檢定方法對購併、股價、國民生產毛額、利率，作單根檢定，發現美日兩國之購併、股價與國民生產毛額呈一階差分恆定狀態。 此外，本文應用Engle and Granger(1987) 的共積模型分析，將同樣為一 階差分恆定的變數做共積檢定，發現美日兩國之購併與股價、國民生產之間，皆具有長期共同移動的趨勢，因此可以建立一包含長、短期關係之誤差修正模型。本文之實証結果顯示：美國的企業購併與股價水準有正向且顯著之長期穩定關係，而與國民生產毛額則有負向且顯著的長期穩定關係；日本的企業購併與股價及國民生產毛額也有長期穩定之關係，惟影響方向與美國相反。另外，因果關係檢定結果顯示，美國之股價與利率對購併呈單向因果關係，而日本之股價與購併則呈雙向因果關係。由這些實証結果可知，購併風潮之形成，實肇因於總體經濟之波動，而不同國家之企業，由於法令規章、經濟結構、社會制度之不同，因而會有不同之反應。

本研究的目的是針對退休金的長期負債以資產負債管理的方式提出有效的投資避險策略建議。在過去，傳統精算的資產負債管理大多採用確定投資模型（Deterministic Model），即以過去的經驗設立「精算假設」，但是這樣的假設無法精確的呈現未來的趨勢，所以本文的第一部份，便是根據過去的台灣總體經濟資料，建構一個退休基金的隨機投資模型（Stochastic Investment Model）。首先，我們以ECM（Error Correlation Model）模式建構出第一個投資模型，之後在精簡參數的考量下，建構第二個以因果關係為基礎的Causality投資模型，再以模型配適能力與預測能力比較兩模型，結果顯示Causality投資模型優於ECM投資模型。 　　有了投資模型，我們設定不同的退休金負債形式，如固定成長型負債MF、隨通貨膨脹成長M^R負債及隨max{固定成長比例，通貨膨脹}而成長的退休金負債M^L，以靜態避險的方式去求得各資產的最適配適比例。從模擬的結果中發現隨著到期日的增長，投資在風險性高報酬率佳的投資標的物上的比例也越來越高。另外，隨著負債固定成長比例f的增加，其M^L負債之期初資產配置額便越接近M^F負債之期初資產配置額。整體而言，我們由模擬中可得出，使用投資組合的投資方式優於單一資產投資的結論。 / In this study, we investigate the hedging strategies for pension liabilities by using Asset-Liability Management method. In the past, the traditional actuarial valuation usually does not take account of market value for both assets and liabilities. Most of the traditional actuarial valuation adopted the Deterministic Model, that is, setting the assumptions based on the experiences. However, it can not exactly show the trend in the future. In part one of this study, we build a stochastic investment model for the pension funds based on Taiwan Market data. First, we apply the first model : ECM( Error Correlation Model ). And then, we apply the second model : Causality Model under considering parsimonious parameterization. Finally, we compare the results of ECM with Causality Model on fitting and forecasting efficiency, and we find that Causality Model is better than ECM. With the investment model, we set some formulas of pension liabilities calculated to obtain the best fit proportion of each valuation by the static hedging. This involves finding optimal static hedging strategies to minimize riskiness of the investment portfolio relative to the liability. Overall, from the simulation results, for static hedging in these kinds of liabilities, investing in all three assets is a better strategy than investing in a single asset class. This confirms that the more assets we use, the more effectively we can hedge.

本研究之樣本取自1991年7月1日至2010年3月之月資料，探討各總體經濟變數包括：利率、匯率(美元對新台幣)、M1B、出口、GDP、領先指標綜合指數與大陸及美國兩股市，對台股指數之影響。實證結果顯示，道瓊工業指數為影響台股加權指數最具代表性與領先的指標，大陸股市則非如一般所預期對台股指數變動有重要解釋能力。且道瓊工業指數、利率、M1b、GDP對台股具有領先的單向因果關係。 在衝擊反應函數及變異數分解中，除了道瓊工業指數為判斷台股指數變動最重要因素外，利率與貨幣供給則扮演著解釋台股變動另一重要的角色，利率調升對台股指數之影響為先正後負，當利率調升前，投資者會事先反應，但調升後便會開始調節，反而對台股造成負向影響；而GDP及出口在變異數分解中占台股變異數比例是相對次高的比重，說明台股的變動反應了經濟的基本面因素，台股的變動亦會受其影響，惟此二項變數屬於落後指標，只能用在事後分析。而(美元兌新台幣)匯率及領先指標綜合指數則對台股變動無顯著解釋能力。

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.

過去文獻對於房價的研究，不管是應用橫斷面分析探討個體層面影響房價之因素，或是應用時間數列分析房價的長期勢，抑或是在分析房價與總體經濟變數間的關係時，多忽略不同次級市場間的互動關係，然而不同次級市場的房價常因為替代性或者是互補性而產生波及效果。 因此本研究將次級市場以行政區域來劃分，以北部地區的四個行政區（台北市、台北縣、基隆市、桃園縣）為研究範圍，利用時空數列分析方法，首先以單根檢定與共整合方法分析四個次級區域的房價時間數列是否有穩定特性，區域房價間在長期是否具有一種穩定的線性組合關係，以說明四個次級區域間房價的異質性與相依性。其次，應用具有誤差修正機制的向量自我相關模型，亦即VECM（Vector Autoregression in Error Correction Model），利用誤差修正模型探討區域房價在次級區域短期失衡時的調整速率，並以Granger因果檢測其間的互動關係及區域房價在時間上、空間上的領先、落後關係。最後對於影響區域房價的重要總體變數納入考量，分析重要區域總體變數在空間上與時間上的相關性與互動性。

本研究係探討匯率與總體經濟之關聯性，以中國大陸1996第一季至 2013年第一季之總體經濟變數，共計樣本數為69筆季資料。先以1996第一季至 2013年第一季全期數據進行實證分析。再以2005年7月為分界點，分為1996年第一季至2005年第二季及2005年第三季至2013年第一季數據分別進行實證分析。 本論文就REER、GDP、CPI、M2、UNEMP、CHIBOR、FDI、OPEN等總體經濟變數，以單根檢定及建構向量自我迴歸模型進行實證分析，並以Granger因果關係檢定、衝擊反應分析及預測誤差變異數分解，以了解匯率與總體經濟相互間之關係。 實證結果發現，中國大陸匯率與總體經濟間的關係自2005年7月21日匯率改革後逐漸增強，但整體言之匯率與總體經濟間之傳導能力仍然不大，人民幣匯率的變動主要受其自身影響較多，受總體經濟變數的相互影響較小，顯示其外匯市場的開放程度與一個真正開放的經濟體還是有些許差距。 / This research examines the correlation between foreign exchange rates and macroeconomics by using the data of economic variables of China from the 1st quarter of 1996 to the 1st quarter of 2013. The sample contains 69 quarterly data during the entire period, while the reform of Chinese exchange rate on 21st July 2005 is a crucial division. In order to find the correlation between foreign exchange rates and macroeconomics, the research examines the economic variables such as REER, GDP, CPI, M2, UNEMP, CHIBOR, FDI, and OPEN by using unit root test, vector autoregression model, Granger causality test, impulse response function and variance decomposition impulse response function. The result of the tests indicates that after the reform of Chinese exchange rate on 21st July 2005, the correlation between exchange rates and macroeconomics has been enhanced, but the connection is not prominent. In other words, the fluctuation of Renminbi is mainly affected by the nation’s policy instead of its macroeconomic factors. Hence, the openness of the Chinese foreign exchange market is still distant from a real open economy.

本篇探討在2010年4月16日滬深300股指期貨正式上市到2012年9月18日止的連續近月每日收盤日資料，進行區域內金融期貨市場連動關係的研究，試圖發現兩岸三地之股價指數期貨市場在亞太地區的金融主導地位，以作為國內外投資者在區域內的投資決策參考。 實證結果顯示，從共整合及向量誤差修正模型檢定發現，兩岸三地股指期貨具有長期均衡及短期的互動關係，因此可以視此三地為單一區域市場。在Granger因果檢定上，台股指數期貨雖無法預測恆生指數期貨，但仍明顯領先滬深300股指期貨且程度大於恆生指數期貨，或可推測兩岸因ECFA的簽訂使實體經濟的關聯性更為緊密，至於恆生指數期貨大多以金融、地產股為其主要成分，與大陸主要以實體經濟為主的金融市場，其Granger預測滬深300股指期貨的能力因此相對較弱。另由衝擊反應檢定得知恆生指數期貨為一獨立的市場，不受台灣及大陸指數期貨市場衝擊的影響；滬深300指數期貨因大陸金融市場逐漸開放，也會受到香港及台灣金融期貨市場之衝擊而產生影響；至於台股指數期貨則在兩岸三地，最易受到其他市場影響。最後由預測變異數分解檢定發現，台股指數期貨及滬深300股指期貨的波動皆易受到恆生股價指數期貨變異的影響，而恆生指數期貨在兩岸三地間之解釋能力最強，於兩岸三地間具金融主導地位。至於台股指數期貨對大陸金融期貨的影響也有突出的表現，因此若政府有心推展亞太金融中心之營運，勢必得加強區域間整合的力度，提出有利吸引外資之最政策，以增加台灣股市於國際間之競爭力。 / This study conducts analysis of regional linkage between financial futures market by examining consecutive daily closing information from April 16, 2010 (the official list date of CSI 300 index futures) to September 18, 2012. This study tries to find the financial dominance of these index futures market in the Asia Pacific region and hopefully it may be used as an investment decision reference for domestic and foreign investors. The empirical results show that from the total integration and vector error correction model tests and three places all indicate long-run equilibrium stock index futures and short-term interaction. Therefore, these three places can be viewed as a single regional market. In the Granger causality test on the TAIEX futures and Hang Seng Index futures, in spite of TAIEX futures can’t predict Hang Seng Index futures, it is significantly ahead of the CSI 300 index futures. TAIEX futures on the CSI 300 index futures even more impact than the Hang Seng Index Futures. It can explain that the ECFA has been signed and results show closely-related economy. Since the Hang Seng Index futures are mainly from financial and real estate stocks while the mainland-based financial market is mainly from the real economy, Granger predicts ability of CSI 300 index futures is relatively weak. Another test on the impulse response shows that (1) Hang Seng Index Futures is an independent market and is not affected by shocks from Taiwan and the mainland index futures markets, (2) CSI 300 index futures is affected by shocks from Hong Kong and Taiwan because of the gradually open financial markets, and (3) TAIEX futures can be seen as a potential Taiwanese dish economy because it is most vulnerable to other market influences among the three places. To sum up, the forecast variance decomposition tests show that TAIEX futures and the CSI 300 stock index futures are vulnerable to fluctuations in the Hang Seng index futures. In order words, the Hang Seng Index futures have the strongest explanatory power among the three places and shows financial dominance. The TAIEX futures also show its significant impact on the mainland China financial futures index. If the Government decides to promote the operation of the Asia-Pacific financial center and to increase competitiveness of Taiwan stock market, it will inevitably have to strengthen inter-regional integration efforts and make the most favorable policies to attract foreign investment.