Abstract Based on the sequential auction model of Kyle (1985) and embedded the formulation of positive feedback traders in De Long et al. (1990), our model formulates a recursive market game of insiders, noise traders, and market makers. In particular, the submitted demands of positive feedback inertial traders are influenced by previous own trading quantities. I prove the existence and uniqueness of a recursive linear equilibrium with positive feedback inertial trades. Further, the equilibrium calibrates that the strategies of insider and market makers are also influenced by positive feedback trades. Finally, we conduct a simulation analysis to get a price-volume pattern with some empirical interesting implications. Finally, this thesis takes trading strategies to trade the individual stock in TSEC. Although the market mechanism of TSEC has no market makers, it is still expected that these trading strategies are useful for traders which implies the information is filtrated by these trading strategies.

傳統探討分析師推薦資訊價值的研究多採用累積超額報酬的方式，近年來研究顯示個別投資人的績效顯著低於機構投資人，因此是否分析師推薦能夠幫助提升個別投資人的福利。本論文的第一個貢獻在檢定是否個別投資人能夠獲取分析師推薦的資訊價值，為區分推薦資訊分別對於個別與機構投資人的價值為何，本研究採用的每種投資人實際的交易利潤作為衡量指標。 研究結果顯示所有投資人都可以透過買入推薦獲取顯著的正報酬，但在賣出推薦上，僅外資與共同基金仍能維持獲取正的報酬。同時發現在推 薦事件期間，專業機構投資人的利潤顯著高於一般散戶的獲利。 進一步，本論文的第二的主題在探討此推薦的資訊價值對於不同投資人的差異，是否肇因於推薦券商所提供的私有資訊，因此進一步將各類投資人分成推薦券商的客戶與非客戶。結果顯示國內機構投資人的利潤在客戶的身上顯著高於非客戶的獲利，顯示推薦券商在對外公佈推薦資訊前的確提供私有資訊給其國內機構客戶，但此現象在賣出推薦並不存在。 第三，本論文進一步分析是否拿到推薦券商所提供私有資訊的客戶也是推薦券商的經紀業務收益的主要貢獻者。在比較推薦券商與非推薦券商在被推薦股票上的相對交易量(金額)中，發現推薦券商的確因為買入推薦股票而增加經紀業務量，但很驚訝的發現貢獻最多交易量的是個別投資人，而非拿到最多好處的機構投資人。 最後，本研究透過迴歸分析探討不同投資人的交易利潤與推薦券商所獲得的經紀業務量的關係。在控制推薦類型、推薦評等與被推薦股票之股票特性後，發現投資人的交易利潤與推薦券商的經紀業務收益成正相關，再次顯示券商推薦與其各項業務收益間的關係。 / Traditionally, information value of analysts’ recommendations has been well-recognized by cumulative abnormal returns. Recent studies show that individuals are underperformed, and therefore, it is a critical issue on if analysts’ recommendations are helpful to individuals’ welfares. The first contribution of this dissertation to the literature is to examine whether individual investors are capable of capturing the information value. To classify the information value of recommendations for individuals and institutions, respectively, I, thus, use a direct measure to calculate the actual trading profits of types of traders. To our best knowledge, this is the first paper that demonstrates the information value for types of investors. Our results indicate that, all investors get positive and significant profits in brokerages’ buy recommendations, no matter what types of investors are measured. As to sell recommendations, only foreign investors and mutual funds have positive returns. We also find that professional institutions earn more profits than retail investors during the recommendation event periods. Further, the second objective of this dissertation is to test whether the information values are caused by private information from brokerages’ houses, we separate the profits of types of investors into customers and non-customers based. The findings are that only domestic institutional customers of recommending brokerages are more beneficial than those of non-recommending brokerages in buy recommendations, which implies that brokerage houses may reveal private information to their own institutional customers before buy recommendations make public. This does not hold for sell recommendations. Third, we are interested in analyzing whether the private information that recommending brokerages provide to their own customers may, indeed, contribute to brokerages’ commission revenues. By comparing the trading volume of recommending brokerages and non-recommending brokerage for the covered stocks, we find that the volumes of covered stocks issued in the recommending brokerages are increased for buy recommendations. Particularly, we find that the main contribution of trading volume is from individuals. Furthermore, we run regressions to study the relationship between trading profits of types of investors and trading volume of recommending brokerages. After controlling recommendation types, consensus rating of recommendations, and stock characteristics, our results indicate that trading profits of all types of investors are positively related to commission revenues of brokerages. This may justify the importance of brokerage recommendations on their business relationships.

近年來由於網際網路的普及，資訊成爆炸性的成長，無論是企業e化、電子商務的應用服務，或是數位家庭的興起，加上網路應用服務的創新，出現如影音部落格等。這些資訊除透過網路傳遞流通外，不管是個人或企業，是使用者或提供服務的業者，都需面對管理如此龐大的資訊儲存服務。 隨著數位資訊的快速成長，檔案的體積與數量日漸增加，雖然資訊科技的進步讓儲存媒體的種類更加多元化且容量越來越大，例如一顆SATA磁碟就有500GB的容量、藍光光碟一片容量達100GB，但根據IDC公佈調查指出，2006年全球資訊量大爆炸，全年的照片、影音檔、電子郵件、網頁、即時通訊與行動電話等數位資料量，高達1610億GB，所以儲存容量的提升似乎永遠趕不上資訊的成長速度。 企業目前分散在各分支機構的IT機房，面臨人員設備的重複投資及分散管理不易，隨著寬頻網路的來臨，企業將IT基礎設施集中化，建置企業的資料中心已成趨勢，我國政府的資訊改造就規劃機房共構成13+1個資料中心，如何建構一個資料中心，應用集中化、虛擬化的趨勢讓儲存系統集中化，同時企業的資訊也集中化，大量的資訊與儲存，更需對資訊做有效的儲存管理。 根據SNIA統計，儲存系統上的資訊，30天內沒有被存取過的大約占80%不常用、不重要的資訊不只造成儲存空間的浪費，也間接影響資訊存取沒有效率，所以在有限的高階線上儲存空間下，將較少用到的資訊搬到較低階的儲存系統，不用的資訊歸檔保存。資訊也有生命週期的演變，本研究將資訊生命週期分四個階段，分別為資訊建立導入新生期、資訊使用黃金成熟期、資訊參考使用衰老期、資訊處置歸檔終老期，透過資訊價值的分類，區分資訊對企業的重要程度，融合資訊生命週期的演進，制定資訊生命週期管理策略，協助企業從資訊的建立、存取、備份、複製、資安、歸檔保存到刪除，使得資訊的儲存保護與存取效率能達到最佳化，確保資訊服務不中斷，獲得最好的儲存投資效益。 / Due to the prevalence of Internet in recent years, information grows explosively. No matter it is e-enable, the service that electronic commerce offers, or the spring up of digital family, in addition to the innovation of the application service that the Internet offers, they all enabled the appearance of products such as Vlog. These information not only circulate through the Internet, no matter it is personal or companies, users or dealers who offer service, all of them have to face the problem of managing such huge information storage service. With the rapid growth of digital information, the volume and the amount of files are getting larger and larger. The advance in information technology makes the type of storage media more various and with larger and larger capacity. For instance, a SATA hard drive has the capacity of 500GB, a Blue-ray disk has the capacity of 100GB, but according to the survey of IDC, the information around the world exploded in year 2006. The total digital information such as pictures, video/audio archive, emails, web sites, messengers, and mobile phones in the year is as much as 161 billion GB. So the storage capacity never seems to catch up with the growth of information. Companies now scatter over the IT control room of each branch. They face the difficulties of repeatedly investing in manual and facilities, and separate management. With the appearance of broadband network, companies consolidate the infrastructure of IT, building companies’ data center has become a current. The information engineering step that our government takes is to draw the control room into 13+1data center. How to build a data center? We use the current of consolidation and virtualization to consolidate storage systems. Mean while, the information of companies should be consolidated. Mass amount of information and storage needs a more efficient way of managing and storing information. According to statistic that SNIA shows, there are about 80% of information in storage system will not be accessed within 30 days. Information that are not often used or are not important can be a waste of capacity, and it can indirectly affect the inefficiency of storing information. So, in the limited high level online storage capacity, we should move the information that are not so often used to lower level storage systems, and we will not have to archive the information. There is also a life cycle within information. This research classify the life cycle of information into 4 stages, which include the introduction/emergence stage in the establishment of information, the decline stage during the reference and usage of information, as well as the final stage in the management and filing of information. Through the classify of information value, we classify the importance of the information to the company, integrate the evolution of information life cycle, establish tactics of information life cycle management, assist companies from the establishment of information, to the storage, backup, copy, information security, archiving and then to the delete of the information. This optimizes the storing, accessing efficiency, assures the continuance of information service and acquires most benefit of storage investment.