本論文分為兩部分，第一部份探討日經225和摩根台指成分股調整的價格變動效果。第二部份則是探討分析師對於股票被納入日經225和摩根台指的盈餘預測反應和絕對預測誤差。 / Two essays are comprised in this dissertation to examine the effects of changes in price and the analyst responses of earnings forecasts to stocks Indices adjustments. Stock markets vary in nature from one country to another and the characteristic of stock index adjustments also alter significantly. The analytical results can provide better information for investors and management to make better decisions. In the first essay, we examine price effects associated with changes in the composition of the Nikkei 225 Index and MSCI Taiwan Index. The analytical results show the price effects on stocks experiencing adjustments in the Nikkei 225 Index are consistent with the price pressure hypothesis. The price effects of composite stocks changed for the MSCI Taiwan Index are consistent with the downward sloping demand curve hypothesis. Based on classifying the characteristics of composite stocks into three categories, we find that large-scale added stocks dominate the price trend of the whole added sample in the Nikkei 225 Index. Also, added stocks with upwards revision earnings forecasts make more abnormal returns than the added stocks with downwards revision earnings forecasts in the Nikkei 225 Index during the post-announcement period. The electronic stocks earn larger abnormal returns than non-electronic stocks in the MSCI Taiwan Index. That can enable investors to profit by buying electronic stocks and added stocks with upwards revision earnings forecasts. The price reactions for the composite stocks in the Nikkei 225 Index and MSCI Taiwan Index around the Internet bubble burst have significantly difference. In the second essay, we study the earnings forecast changes and absolute forecast errors made by analysts of the Nikkei 225 Index and MSCI Taiwan Index. Depending on the properties of brokerage firms that analysts work for, we divide them into local analysts and foreign analysts to separate who are more accurate than one the other. The results show that in comparison with the matching firms in Japan, the magnitudes of mean forecast revisions and absolute forecast errors are smaller made by analysts focusing on firms newly added to the Nikkei 225 Index. For firms newly added to the MSCI Taiwan Index, the magnitude of changes in analysts EPS forecasts do not differ clearly from those of their peer groups. Absolute forecast errors made by analysts focusing on firms newly added to the MSCI Taiwan Index are smaller than those made by analysts focusing on the matching firms. This phenomenon demonstrates firms that are newly added to the Nikkei 225 Index and MSCI Taiwan index exhibit significantly improved performance. In terms of the relative accuracy of local and foreign analysts, the results display that the forecasts of foreign analysts are less accurate than those of local analysts in Japan and the forecasts of foreign analysts are more accurate than those of local analysts in Taiwan.

Because on the method of Harris and Shen (2003), we implement the robust estimator of optimal hedge ratio in Taiwan stock market. By using the Taiwan Stock Index and Taiwan Stock Index Futures, we used the robust estimation of optimal hedge ratio. We use two estimators, the rolling window model and the exponentially weighted moving average (EWMA), to estimate the robust optimal hedge ratio. We also compare the hedging effectiveness of the robust hedge ratios and the traditional least- squared hedge ratios. We find that the volatility of the hedged portfolio using robust optimal hedge ratio is substantially lower than that of the portfolio using the traditional hedge ratios. With the less excessive volatility, the transaction cost decrease substantially, and the cost of rebalancing portfolio is lower as well. / Because on the method of Harris and Shen (2003), we implement the robust estimator of optimal hedge ratio in Taiwan stock market. By using the Taiwan Stock Index and Taiwan Stock Index Futures, we used the robust estimation of optimal hedge ratio. We use two estimators, the rolling window model and the exponentially weighted moving average (EWMA), to estimate the robust optimal hedge ratio. We also compare the hedging effectiveness of the robust hedge ratios and the traditional least- squared hedge ratios. We find that the volatility of the hedged portfolio using robust optimal hedge ratio is substantially lower than that of the portfolio using the traditional hedge ratios. With the less excessive volatility, the transaction cost decrease substantially, and the cost of rebalancing portfolio is lower as well.

本文引用Pagan and Sossounovb（2003）針對Bry and Boschan（1971）景氣循環周期判定法修改後的法則，判定大盤與類股指數的牛市、熊市周期。將判定的周期結果畫成圖表，藉由簡單的圖表分析將可明確得知大盤周期與類股周期領先與落後的關係，並應用計量模型估計，找尋能夠顯著預測大盤周期變動方向的類股，或是檢驗大盤周期是否能夠預測類股周期方向；反之亦然。並且比較圖表分析與計量模型估計結果是否一致。 圖表分析與向量自我迴歸模型的實證結果一致，八大類股中，營建、金融、機電、塑化等四類股周期能夠顯著預測大盤周期走勢，其中以塑化類股最具預測能力；而大盤周期皆無法精準預測類股周期走勢。而羅吉斯迴歸模型結果也發現，營建、金融、機電、塑化等四類股周期能夠增加大盤周期走勢的預測機率；同樣的，大盤周期無法影響類股周期走勢的預測機率。

本文係針對中國大陸各省市地區2000年至2007年之房地產指數進行分析，利用雙因子固定效果模型(two factor fixed effects model)探討中國大陸各省市地區房地產指數之重要影響變數，以及這些變數對於房地產指數影響程度之強弱。本文首先將文獻之檢閱做整理介紹，先概述至今國內外討論房地產價格指數文章之重要觀點，了解這些文章作者的研究時間與空間範圍、所使用分析方法、各學者之論點及其變數設定，希望在最後能與本研究之結論相互比較，觀察文獻與本研究之間是否具有一致性。 由於本論文重視各地區變數之影響，故本研究將使用具地域性之各省市數據資料作為變數，經由資料蒐集，將合適之變數（能夠量化及具有地域性之數據）納入研究考量，參閱文獻資料加上能夠取得之數據資料為考量，本文將討論下列變數：各省市地區居民收入、各省市地區居民消費水平、各省市地區城市建設面積、各省市地區固定資產投資指數、各省市地區交通情況、各地區外資投入金額、各省市地區人口數量、各省市地區人口縝密度、各省市地區衛生機構數以及各省市地區進出口總額等十個變數，對於中國大陸各省市地區房地產指數之關係，觀察其影響程度，了解各地區差異，期能提高對各地房地產價格波動之預測與預警水準，並為政府施政提供方向，當政府需要實施宏觀調控，將能夠較為明確的掌握調控之基本要素。

本研究以Rao(2006)的MMPI為基礎，在距離函數觀念下將MMPI進行拆解，分解成技術效率變動、技術變動、規模變動以及追趕項，再將追趕成份，進一步拆解為「技術追趕」(catch-up in technology, 簡稱CUT) 與「潛在技術變動」(potential technological change, PTC)，其中，CUT又可再分解為變動規模報酬之下的效率追趕(catch-up in efficiency, CUE)及規模追趕 (catch-up in scale, CUS)。實證上，利用1993-2007年間，15個歐洲國家的財務報表資料，運用DEA法分析西歐金融機構之經營效率，並進行生產力的推估與拆解，同時結合共同邊界的分析架構，從事群組國家間比較分析。 實證結果發現，MMPI表現突出的群組，主要來自於技術效率的進步，例如：北歐三國群組和奧地利；其次是規模效率的進步，例如：北歐三國與法國；最後才是技術變動，例如法國。而在十個國家群組中，除了義大利的MMPI退步以及奧地利的規模效率呈現持平外，其餘八個群組的MMPI與其三個構成項目，都呈現同升同降的相同趨勢，不同處僅在於變動幅度大小。例如MMPI都呈現進步的情形，其構成項目，分別表現出技術退步、技術效率進步以及規模效率進步。這樣的結果可能來自於歐洲單一市場的運作方式。 又依MMPI統計差異性檢定的結果，我們可以將原先依MMPI數值大小排序的十個國家群組，重新考慮群組間統計上差異及無差異的情形，合併為五個層次的生產力成長情形，第一層為北歐三國，MMPI成長最快，其次為奧地利、法國、比利時，再次為荷葡西英群組，第四層是盧森堡、瑞士，最末層則為德國、丹麥及義大利。

本研究主要針對 Breidt et al.(1991) 等多位學者所建構的 Mixed causal-noncausal model,探討其假設與可拆解特性,並仔細討論相關資料模擬估計及預測的方法,最後將其實際應用於隱含波動率指數 (Volatility Index)的估計及預測上。根據本研究的實證結果,我們發現隱含波動率指數確實包含非因果的特性,並可進一步對其拆解及預測。另外 , 我們也以移動窗格的方式觀察係數估計結果的變化,發現 Mixed Causal-Noncausal Model 的確能夠捕捉到泡沫或危機正在生成的過程。 / This paper first focuses on Mixed causal-noncausal model constructed by Breidt et al.(1991) and then conducts empirical research on the CBOE Volatility Index. The assumptions, simulation, estimation and prediction methods of Mixed causal-noncausal model are introduced in great detail. Our empirical results show that the CBOE Volatility Index really contains non-causal parts, such that we can filter this part from the index and then further predict it. Moreover, by employing the rolling window estimation scheme the resulting coefficients of Mixed causal-noncausal model really could detect a bubble or a crisis which is going to happen.

根據研究指出 ETF 資產規模近幾年快速成長，元大台灣卓越 50 基金因市場 規模大等優勢受到投資人的青睞，賴以巨量資料的發展使得文字探勘技術成熟， 故本研究希冀提出一套情感分析的價格預測模型，提升投資者的報酬率。 過往學者以文章中的單詞作為文字探勘的分析單位，常會產生同義詞、多義 詞的問題，因此提出情感型態分析的監督式學習方法建立模型。另外為了解決監 督式學習難以取得訓練資料的限制，本研究混合非監督式學習方法進行主題分群 與情緒傾向標注。 本研究建立台灣股市新聞文本資料集，並篩選熱門議題詞詞庫，進行非監督 式的 LDA 主題模型，發現在 2016 年總統選舉期間，媒體對於公司相關議題的注 意力降低，使得相關的文本數量大幅減少;另外在情緒傾向標注階段，因混和了 NTUSD、知網及自行擴充演算法的情感詞庫，能夠將 10%中性詞彙產生極性判 斷、96%的文本標注情緒傾向。 視覺化工具分析結果指出，DIF-MACD 能夠預測台灣卓越 50 基金的長期走 勢，而新聞情緒指數則在短期的價格波動上表現良好，且在主題模型分群中，總 體經濟、公司維運類別的新聞情緒指數具有約 1-2 日領先指標特性，對於後續的 價格預測模型有所助益。 在監督式情感分析方法，為解決上述同義詞、多義詞的問題，本研究採用型 態分類模型於中文文本，並與向量空間模型、支援向量機等方法做比較。實驗結 果指出優化的型態分類模型，並結合台灣加權股價指數，表現相對良好，F1- Measure 可達 85%。進一步討論新聞情緒對於價格預測的重要性，發現在非交易 時間序列中的新聞情緒，能夠對 0050 的價格波動產生影響。 / The past research points out that the scale of ETF assets has been growing rapidly in recent years. Yuanta Taiwan Top 50 ETF is popular with investors because of the advantages of large market scale. Through the development of Big Data, the technology of Text Mining becomes mature. Thus, we analyze the price forecast model to raise the investors' rate of return. The research of Text Mining used to take the document term to analyze, but it often results in the problem with synonym and polysemy. Therefore, this research proposes a supervised learning method of sentiment pattern analysis. In addition, in order to solve the problem with training data about the supervised learning method, we mix the unsupervised learning method to carry out the subject grouping and sentimental tendency. In this study, we establish the news dataset and screen it as popular terms that are used to an unsupervised method of LDA model. The result points out that the number of news about company dropped significantly during the 2016 Taiwan president election because of the change of media sensation. Moreover, we create the sentiment dictionary that can determine the polarity of 10% neutral terms and the emotional tendency of 96% documents by mixing the NTUSD, HowNet knowledge Database and the self-expansion algorithm. Through the data visualization, the result shows that the curve of DIF-MACD is able to predict the long-term trend of 0050, while the sentiment index of the news makes a good showing in the short-term price volatility. Besides, the news sentiment index of the subjects that belong to general economy and company has about 1 to 2 day leading indicators. Eventually, we employ the Sentiment Pattern Taxonomy Model(PTM) in Chinese texts as supervised learning method and compare with VSM and SVM. The experiment result shows that PTM combined with Taiwan Weighted Stock Index is the best when its F1-Measure is up to 85%. Apart from this, we find that the sentiment index of the news in non-trading time can influence the price volatility of 0050.

自從槓桿型指數基金於各股票市場發行後，各國主管機關皆紛紛發出聲明表示，該商品並不適合長期持有；因此，該類型投資商品的公開說明書皆會註明不宜長期投資。然而，本研究實證結果發現，持有期間長短並非主要風險來源。雖然，如大家所知，槓桿型指數基金多是以「日」為單位追蹤指數，而導致複利效果 (Compounding Effect) 使基金長期報酬與槓桿倍數不同。 根據算出上述的報酬差異(Return Difference)可以發現不論是正向2倍或是反向1倍皆與台灣50報酬率的標準差有統計上顯著關係。反向1倍皆與台灣50報酬率的標準差有顯著負相關；反之，正向2倍與台灣50報酬率的標準差有顯著正向相關。然而，從已實現乘數(Realized Multiple)的分佈中可發現，不合理值並不隨投資期間越長而越多。意即儘管投資期間越長，並不一定會導致複利效果越大，而與目標槓桿倍數脫節。再者，隨著投資期間越長，波動度(volatility)的對於報酬差異的解釋力越強；因此，若想長期投資槓桿型指數資金，預測標的波動度的能力更顯為重要。 / When we browse the reports about the inverse and leveraged ETF, most of them emphasize that the LETF is not appropriate to long-term investors. However, in this research, we attempt to demonstrate the main factor of the performance of the leveraged and inverse ETF is not how long the LETF we hold, but the volatility of the underlying index or ETF. Observing the empirical test, no matter how long the investment horizon is, the coefficient of the variance of the Taiwan 50 is statistically significant both in the Taiwan 50 Bear -1X and the Taiwan 50 Bull. However, its effect on the Bear -1X is opposite to that on the Bull 2X. First, the relationship between the volatility and the return difference of Taiwan 50 and the Bear -1X is negative. In contrast, the relationship between the volatility and the return difference of Taiwan 50 and the Bull 2X is positive. However, in accordance with the distribution of the realized multiples, the frequency of either the Bear -1X or Bull 2X was not more and more when the holding period is longer. As a result, our research show the variance has a significant effect on both, no matter how long investors hold. If the volatility is moderate, the return difference may be close to zero; then the LETFs would be a convenient way to investors who desire to magnify the market return. Moreover, due to the increasing explanatory power of the volatility, we may make a further inference that whether the compounding effect is positive or negative depends on the volatility, especially within longer holding period. Therefore, without the great ability to forecast the variance, the LETFs are not recommended to the long-term investors.

系統性信用風險即倒帳風險，是各個企業和銀行都會面臨的問題，當景氣蕭條時，企業或個人可能無法按時支付本金與利息，此時信用風險的程度提高；相對而言，景氣佳時，不論個人或企業的償債能力均提高，信用風險明顯下降，因此這裡所謂的系統性信用風險其實就是景氣循環風險。 本文提出一個相當直覺的觀念來規避系統性的信用風險，既然景氣循環影響了系統性信用風險的高低，我們現在的目的就是要規避景氣循環風險，而股價指數的變化其實就是景氣循環的領先指標，因此我們可以由股價指數或種種總體經濟指標來預測未來的景氣狀態，接著就可以利用買進或賣出股價指數期貨的方式來規避景氣循環風險。 本文以八個國家作實證研究，包括了台灣、美國、英國、法國、日本、瑞士、墨西哥、澳洲等已開發國家及開發中國家，並選取實質GDP成長率以及工業生產指數作為景氣循還的指標，進行OLS簡單迴歸、移動迴歸、二次迴歸、以及Downturn下的OLS簡單迴歸。 實證結果發現：台灣、日本、澳洲與墨西哥的股價指數期貨報酬率與實質GDP成長率呈正向關係，且具預測能力，其t-value均為顯著，故適用本文所提出的避險概念。而美國與英國在大部分的時期，股價指數期貨報酬率與實質GDP成長率呈正向關係，因此股市還算具有預測景氣循環的能力，仍適用本文所提出的避險概念。至於法國與瑞士的股價指數期貨報酬率與實質GDP成長率呈負向關係，股市無法作為景氣循環的領先指標，其t-value均不顯著，故不適用本文所提出的避險概念。 / Systematic credit risk is default risk, which is a problem any enterprises and banks may face. When the economy is in the downturn, enterprises or individuals may not afford to pay the principal and interests on time. At this moment, the probability of the occurrence of the credit risk is very high. In contrast, when the economy is in the upturn, enterprises and individuals’ ability of paying back the debt is lifted. Apparently, the probability of the occurrence of the credit risk is low at this moment. Therefore, the so-called systematic credit risk is business cycle risk. This thesis presents a direct and simple concept to hedge the systematic credit risk. Since the business cycle affects the level of systematic risk, our purpose now is to hedge the business cycle risk. Besides, from the previous surveys, the change of stock market is a leading index of business cycle. As a result, we can predict the economy situation in the future by stock index and hedge the business cycle risk by purchasing or selling stock index futures contracts in advance. This thesis do empirical study depended on the data of eight developed or developing countries, inclusive of Taiwan, U.S.A., England, France, Japan, Switzerland, Mexico, and Australia. We choose real GDP growth rate or industry product index as business cycle index, and then run simple OLS, rolling regression, quadratic regression, and simple OLS under downturn to get the hedge ratio and its t-value. The empirical results are as follows: 1、The relationship between the rate of return of stock index futures and real GDP growth rate in Taiwan, Japan, and Australia is positive. In other words, the rate of return of stock index futures can be a predictor of real GDP growth rate and the t-value of the hedge ratio is significant. Therefore, we can hedge the systematic credit risk in these countries by selling stock index futures contracts in advance. 2、In most periods, the relationship between the rate of return of stock index futures and real GDP growth rate in U.S.A. and England is positive. Therefore, the change of stock market still can predict the business cycle and we can apply the hedge concept in this thesis in the two countries. 3、The relationship between the rate of return of stock index futures and real GDP growth rate in France and Switzerland is negative. In other words, the change of stock market can’t early reflect the phenomenon of business cycle and the t-value of the hedge ratio is not significant. As a result, the hedge concept presented in my thsis is not applicable in these countries.

本研究以在台灣期貨交易所上市之台灣證券交易所加權股價指數期貨、電子類股價指數期貨、金融類股價指數期貨為研究對象，探討從88年7月21日開始至89年4月19日為止，此三種本土指數期貨是否存在著套利機會。研究中將考量實際套利過程中面臨之交易成本，以建構理論價格之無套利區間，並進一步分析期貨價格與理論價格間之價差、套利機會出現頻率及其獲利空間之大小。而在套利交易過程中，由於無法一次的大量買進所有的現貨指數成份股，因此嘗試以模擬投資組合方式，建構套利現貨部位，並同時分析其模擬現貨指數之效果。最後再根據套利機會實證結果，說明國內期貨市場之有效性，並分析套利交易過程中可能面臨的套利風險。 實證研究結果獲致之結論如下： 1.台股、電子、金融指數模擬投資組合之模擬誤差平均分別為0.3335％、0.1620％、0.0730％，能夠有效的複製現貨指數之走勢。特別是電子及金融組合，其組合報酬幾乎與現貨指數同步。 2.台股期貨在考慮交易成本後，其套利機會大幅減少。 3.電子期貨價差套利機會稍多於逆價差，套利機會總共出現了76次，獲利幅度平均達0.72。 4.金融期貨套利機會總共出現了110次，幅度平均為0.75％，其中絕大部分為正價差套利機會，出現次數高達105次。 5.台股期貨較符合市場有效性之條件，電子、金融期貨則由於其套利機會出現頻繁，獲利幅度較大，其期貨市場較不具備有效性。造成此種差異之原因，可能在於從事電子、金融期貨套利交易時，投資者將面臨較大的套利風險。