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兩岸自2008年以來，已舉行四次的江陳會談，究竟其簽署的協議對我國經濟的影響為何，為值得探討的議題。過去關於兩岸經貿互動行為，對我國股市之影響的研究付之闕如，因此本研究將運用事件研究法，探討我國股市是否具市場效率性，以及探討其簽署的協議是否會造成相關類股的異常波動。本研究的實證結果顯示，除第一次江陳會談對台灣的觀光業無異常報酬現象外，其他三次會談皆會造成我國整體股市與相關類股的異常波動，證明我國的股市屬於半強式效率市場。政府應建立完善的協商監督機制、解決股市過度反應之問題、研擬相關政策與作業，讓兩岸能夠在公平對等的原則下進行合作與交流，共同創造更大的利益。

在本篇研究中，我們考慮了未預料到的訊息進而檢定歐元兌美元外匯市場的效率性。並且，我們將資料分為金融海嘯發生前後兩段期間，資料頻率為日資料。有別於之前文獻使用的訊息不完整且可能不為真實的訊息，我們考慮了所有美國及歐盟定期公布的相關經濟數據與指標，並定義未預料到訊息為數據真實質與預期值之間的差距。我們的實證結果指出，在金融海嘯前，是接受市場效率性假說的，雖然此一結果在金融海嘯發生後並不成立，但未預料到訊息的衝擊，確實會影響外匯市場效率性檢定的結果。因此過去文獻無法支持市場效率性假說之原因可能源自於忽略了未預料訊息的考量。另外，我們也發現，美國訊息與歐盟訊息存在不對稱的影響力，且市場傾向於忽略歐盟區的數據。 / In this paper, we examine the hypothesis of market efficiency in euro/dollar with un-anticipated news, which are defined as the difference between actual values and the market’s forecasts. The research data are divided into two periods of time, before and after the beginning of financial crisis. Unlike previous literatures in which the un-anticipated news are incomplete and may be unreal, our paper adopted all macroeconomic announcements and indicators of United States and the European Union. Our results before the financial crisis indicate that the market efficiency hypothesis is accepted, although the result fails to hold after the financial crisis. The result still shows the importance of the un-anticipated news in testing the foreign exchange market efficiency hypothesis. Therefore the rejection of efficiency hypothesis on foreign exchange market in the literature may result from the lack of un-anticipated news in the model. In addition, we found that impacts of U.S. and EU un-anticipated news are asymmetric on the exchange rate. Besides, the market participants tend to ignore the EU news during both periods of time.

財務報表在資本市場扮演何種角色是會計學者長久以來關注的焦點。Ohlson的研究將實證研究的重心從解釋股價的行為轉向至會計資訊與企業價值關聯的研究。本研究以美國市場為背景，加入分析師對盈餘預測因素，測試剩餘淨利模型實證上的有效性，並且用以檢視是否能以此模型建立超越大盤的投資組合。實證結果顯示發現分析師的盈餘預測作為其他資訊之代理變數以及分析師之長期成長預測捕捉企業未來成長潛質，有助於提升模型對股價的解釋能力。本研究認為成長機會對股價具有正向之影響，現時股價表現反映投資人對未來預期的結果。

根據效率市場假說（Efficient-market hypothesis，EMH），倘若市場是具有效率性的，投資者無法預測股票未來的走勢，包括專業的基金經理人員。但是，在許多財經新聞媒體、商業報紙與商業週刊中，發現證劵經理人或分析師在金融市場中大膽的預測股票未來的走向。這些資訊吸引許多投資者紛紛進場投資，期許能獲得更多利潤。然而，投資者卻忽視發佈的資訊時間點的重要性，幾乎很難求證此消息是否真實。本研究希望探討投資機構之研究彙報能否為投資者帶來異常報酬，並印證市場效率性是否存在。本研究資料透過公開的資訊網站Yahoo Finance收集美國道瓊工業30成份股的資料之金融研究機構建議操作方向，利用事件研究法(Event Study Method)來進行分析。實證結果發現事件發生時，不論是推薦買進或賣出，平均異常報酬率（AAR）有顯著的異於零的報酬率，證實金融研究機構所建議的操作方向的確吸引到市場的注意，造成股價異常波動。而累計平均異常報酬率（CAAR）則是顯示事件發生後約4週，建議買進的事件會出現相當利潤。除此之外，本研究亦針對不同金融研究機構的績效分別進行討論，然而並無發現各金融研究機構有顯著的差異。 / According to the Efficient-Market hypothesis (EMH), if the market is to have efficiency, the investor or professional fund managers cannot predict the future trends of a stock. However, in many financial news media, business newspapers and Business Week, we can find securities managers or analysts in the financial markets boldly predicting the future direction of a stock. This information attracts many investors who enter into investments, hoping to gain more profit. However, investors have neglected the importance of published information at a point in time, and in hindsight, it was hard to verify whether or not this news is true. The present study is to investigate that the mechanism of investment research reports can bring abnormal returns for investors, and confirm the existence of market efficiency. The studies suggested actions of directing public information through research institutions news site Yahoo Finance and collected 30 constituent stocks of the Dow Jones Industrial, to analyze the use of the event study method. The empirical results show when the event occurred, whether it was a buy or sell recommendation, the average abnormal return rate（AAR）has a phenomenal rate of return difference from zero, confirming that the proposed research institutions operating direction did attract the market's attention, resulting in abnormal fluctuations of the stock price. The cumulative average abnormal return rate（CAAR） is a show about four weeks after the incident that recommends buying the event will be quite profitable. In addition, this study discussed separately the performance of different research institutions, however, it found no significant differences between various research institutions. / 目錄 摘要.............................................................................................................Ⅰ Abstract........................................................................................................Ⅱ 目錄............................................................................................................Ⅲ 圖目錄..........................................................................................................Ⅴ 表目錄..........................................................................................................Ⅵ 第壹章 緒論....................................................................................................1 第一節 研究動機.................................................................................................1 第二節 研究目的................................................................................................2 第三節 研究架構.................................................................................................3 第四節 研究貢獻.................................................................................................3 第貳章 文獻回顧.................................................................................................3 第一節 效率市場理論..............................................................................................3 第二節 效率市場層面..............................................................................................5 第三節 專家推薦層面..............................................................................................7 第四節 綜合評析..................................................................................................8 第參章 資料來源與研究方法.........................................................................................8 第一節 資料來源..................................................................................................8 第二節 研究方法.................................................................................................10 第肆章 實證分析.................................................................................................11 第一節 資料敘述.................................................................................................11 第二節 模型設計.................................................................................................13 第三節 結果分析.................................................................................................20 第伍章 結論與建議...............................................................................................33 第一節 結論....................................................................................................33 第二節 後續研究建議.............................................................................................35 參考文獻.........................................................................................................36 中文部分.........................................................................................................36 英文部分.........................................................................................................37 附錄.............................................................................................................38 附錄一 道瓊30成分股中之各證劵彙報建議買進(Upgrade)之個股平均異常報酬（AAR）與累計平均異常報酬（CAAR）圖..................38 附錄二 道瓊30成分股中之各證劵彙報建議賣出(Downgrade)之個股平均異常報酬（AAR）與累計平均異常報酬（CAAR）圖................45 附錄三 篩選後，各家金融研究機構發佈彙報之建議買進(Upgrade)之個股平均異常報酬（AAR）與累計平均個股異常報酬（CAAR）圖........52 附錄四 篩選後，各家金融研究機構發佈彙報之建議賣出(Downgrade)之個股平均異常報酬（AAR）與累計平均個股異常報酬（CAAR）圖......57 圖目錄 圖1. Fama et.al.之資本市場效率分成三種假說特性.......................................................................5 圖2. 事件研究法模型的時間線圖.......................................................................................15 圖3. 道瓊30成分股之全部研究彙報建議買進(Upgrade)的平均個股異常報酬（AAR）圖............................................28 圖4. 道瓊30成分股之全部研究彙報建議買進(Upgrade)累計平均個股異常報酬（CAAR）圖..........................................28 圖5. 道瓊30成分股之全部研究彙報建議賣出(Downgrade)的平均個股異常報酬（AAR）圖...........................................29 圖6. 道瓊30成分股之全部研究彙報建議賣出(Downgrade)累計平均個股異常報酬（CAAR）圖........................................29 表目錄 表1. 道瓊30工業指數之成分股（Dow Jones Industrial Index of 30 stocks, ^DJI）.........................................9 表2. 所有金融研究機構有給予道瓊30成分股的總發佈彙報次數................................................................12 表3. 道瓊30篩選後之金融研究機構與彙報發佈次數.........................................................................13 表4. 道瓊30成分股中個別證劵建議買進(Upgrade)的平均個股異常報酬（AAR）...................................................24 表5. 道瓊30成分股中個別證劵建議賣出(Downgrade)的平均個股異常報酬（AAR）.................................................25 表6. 道瓊30成分股中個別證劵建議買進(Upgrade)的累計平均個股異常報酬（CAAR）...............................................26 表7. 道瓊30成分股中個別證劵建議賣出(Downgrade)的累計平均個股異常報酬（CAAR）.............................................27 表8. 篩選後，各家金融研究機構發佈彙報之建議買進(Upgrade)的平均個股異常報酬（AAR）.........................................30 表9. 篩選後，各家金融研究機構發佈彙報之建議賣出(Downgrade)的平均個股異常報酬（AAR）.......................................31 表10. 篩選後，各家金融研究機構發佈彙報之建議買進(Upgrade)的累計平均個股異常報酬（CAAR）...................................32 表11. 篩選後，各家金融研究機構發佈彙報之建議賣出(Downgrade)的累計平均個股異常報酬（CAAR）.................................33

本文有別於傳統效率性的計算方式,改採用 Ito Regression 估計單一市場的效率程度。實證結果發現,在各個單一市場皆看到市場呈現無效率的狀態,因此再用 VAR 的架構檢驗多國市場間的效率程度,結論明顯指出組合市場比單一市場還來的有效率,但同時考慮多個市場的有效率性必須在嚴謹的挑選市場下才能達到效率市場的目標。

過去國內文獻大致指出投資人難以依靠券商的投資建議獲利，此與大部份國外文獻的發現相異。本文參考Barber et al. (2001)，建構一個適用於台灣股票市場的研究方法，再以四因子模型做實證。本文以2007年3月至2015年12月，共48987筆卷商個股報告為研究樣本，來探討券商報告的投資建議能否獲利。本文研究結果發現，台灣的券商報告擁有額外的資訊價值，此與Barber et al. (2001)及其他國外文獻大致相同。 本研究依券商的推薦強度建構四個投資組合。發現推薦程度高的投資組合平均月報酬為正，且高於大盤；而推薦程度低的投資組合平均月報酬顯著低於大盤，且擁有顯著的負超額報酬。本文進一步建構買進賣出策略，即買進推薦股票高的投資組合並賣出推薦程度低的投資組合，發現此策略報酬顯著高於零及大盤，且存在顯著的正超額報酬。另外在台股多頭期間，本研究的實證結果更加顯著，推薦程度高的投資組合平均月報酬增加至顯著高於大盤，且超額報酬顯著為正；推薦程度低的投資組合之大盤調整報酬及負超額報酬的顯著程度提高；而買進賣出策略獲得超額報酬的顯著程度也大幅提高。 / Past Taiwanese literatures generally indicated that it is difficult to obtain profit from Taiwanese stock recommendations of brokerage, which is different from most of foreign literatures. Referring to Barber et al. (2001), we improve and build a research methodology applied to Taiwanese stock market, conducting empirical analysis with four-factor model. From March 2007 to December 2015, we use total 48987 brokers’ stock recommendations as sample to investigate whether inventors could earn profit from the broker recommendations. Our empirical results show that Taiwanese broker reports hold additional information, which is consistent with Barber et al. (2001) and most of foreign literatures. According to the strength of recommendation, we construct four portfolios and find that the return of the most favorable portfolio is higher than market, while the return of the least favorable portfolio is significantly smaller than market and holds significantly negative access return. We further construct a long-short strategy, which buys the most favorable portfolios and shorts the least favorable portfolios. The return of this strategy is significantly higher than market, and excess return is significantly positive. During Taiwanese bull market, the significance of our empirical result improves. The significance level of market-adjusted return and access return for both the most favorable and least favorable portfolio is higher. In addition, the significance level of excess return for long-short strategy also greatly improves.

中國大陸於1979年開始進行經濟改革，廣開經濟之門，大量吸收外資來活 潑各項經濟建設活動，正逐步邁向計劃商品經濟的新體制。其中，成立中 國鄭州市場的構想，乃至於正式開業，是大陸傳統社會主義的大改變，表 徵以市場機能為中心的資本主義在大陸抬頭，是應計劃經濟體制必需與自 由市場互相協調配合之經改政策的具體結果。中國鄭州商品交易所與上海 金屬交易所、深圳有色金屬交易所並稱為大陸三大期貨市場，占大陸期貨 總交易量的80％，深受舉世所矚目，成功與否，對大陸經改及形成亞太經 濟圈都具有重要意義。通常期貨市場加入純現貨市場經濟體系，對於穩定 價格和經濟發展有其正面貢獻。本文將探討中國大陸現階段如何建立期貨 市場？如何對大陸傳統經濟體制造成影響與挑戰？目前發展到甚麼程度？ 如何善加利用自由經濟體制的市場機能來成功的發展期貨市場？本文欲對 大陸目前尚在初級水準的期貨市場提出意見，甚至期待其能發展成全球性 期貨市場。本文對全中國大陸期貨市場將作一全面性的概觀、對幾個主要 的期貨交易所作一重點式的簡介，然後進入本文重點，亦即對中國鄭州商 品交易所作詳細探討，包括其運作狀態、市場效率性等，以下是本文內容 。時間數列的資產價格大多為具有單根的非穩定性變數的特性已廣被接受 ，非穩性變數使傳統的F-統計量或t-統計量會得出不正確的檢定結果及估 計。本文採用 Engle & Granger(1987)的二階段估計法，首先以 Dickey & Fuller (1981) 的單根檢定 (ADF unit root test) 得出鄭州 交易所及芝加哥交易所的期貨價格為具有單根的時間數列，其次以 Engle & Granger (1987) 的共整合檢定方法，得出對於才自1993年5月28 日成立的中國大陸鄭州商品交易所與自1865年即開始期貨交易的美國芝加 哥期貨交易所 ( CBOT) 同種商品之間，包括小麥、玉米及大豆，不具共 整合關係，推論此二市場目前尚沒有長期穩定均衡關係，亦即此二市場為 區隔性 ( seg- mented) ，而非共整合性 (cointegrated) 。反之，對鄭 州交易所內不同商品的期貨價格作兩兩共整合檢定，呈現相當高的共整合 現象，隱含一種商品的期貨價格可以被另一種商品的期貨價格所預測 (predictability)，違反市場效率性的假說，故本文得出結論：中國大陸 鄭州商品交易所成立至今短短十個月 (截至1994年3月底止之資料)，尚不 具市場效率性。 / It is now widely accepted that financial price series are generally not stationary and consequently, conventional statisti- cal procedures like F-statistic and t-statistic are no longer appropriate for testing market efficiency and estimation. Since nonstationary variables have infinite variance that make the F- test or t-test invalid, the standard hypothesis testing does not apply to time series with unit roots. This article adopts Engle and Granger's (1987) two-stage estimation. Firstly, apply augu- mented Dickey & Fuller unit root test (1981) to the argricultur markets are with unit roots which means both time series variables are nonstationary. Secondly, apply Engle & Granger's (1987) Cointegration Test to test whether the cointegration relationship, including wheat, corn and soybean futures market, between CZCE and CBOT exists or not, the former one is established on May 28th, 1993 in Mainland China and the latter one is established since 1865 in the United States. The result is the wheat, corn and soybean futures prices in these two markets are not cointegrated which implys by now these two markets have no longterm equilibrium relationship, also implys CZCE and CBOT are segmented, not cointegrated. On the contrary, applying Engle & Granger's (1987) Cointegration Tests to test the different argriculture futures market in CZCE, cointegration can not be rejected. That implys one argriculture futures price can be predicted by other argriculture futures price and the market efficiency hypothesis is rejected. Therefore this article has the following conclusion : the empirical results by now presented the rejection of the market efficiency hypothesis for three argriculture products -- wheat, corn, and soybean -- traded on China Zhengzhou Commodities Exchange.