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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 蘇永成(Yong-Chern Su) | |
dc.contributor.author | Chia-Li Lin | en |
dc.contributor.author | 林佳莉 | zh_TW |
dc.date.accessioned | 2021-06-08T04:17:18Z | - |
dc.date.copyright | 2010-08-06 | |
dc.date.issued | 2010 | |
dc.date.submitted | 2010-07-29 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/22415 | - |
dc.description.abstract | 市場效率是金融領域裡最重要的觀念之一,近年來也是個富有爭議性的話題,因為真實世界裡不斷的發生和市場效率矛盾的異常現象,像是一月效應和小公司效應,直覺上,效率不會立即發生,因為資訊的傳播速度不夠快,所以每個人不會在同時間接收到相同的資訊,因此將會有人獲得超額報酬,然而,這種情形不會持續太久,各式各樣投資者的力量將會把市場推向效率。本研究即觀察投資銀行的買賣單不平衡與商業銀行的報酬之關係的市場效率收斂過程。
首先我們以多元線性回歸模型檢驗同期或前期之買賣單不平衡對報酬率的影響,實證結果顯示,同期之買賣單不均衡對報酬率有顯著之正向影響;前一期的買賣單不平衡在考慮當期後,對報酬的影響為負向關係,不考慮當期時,在不同的時間區間顯著水準同為10%的條件下,對報酬的影響呈負向關係的情形相對明顯。接著我們以GARCH(1,1)模型觀察同期買賣單不平衡對報酬率的影響,結果顯示其間有正顯著的關係。不論是線性回歸模型、或是GARCH(1,1)模型,我們都可以觀察到市場效率的收斂過程。 此外,我們也以GARCH(1,1)模型觀察股價波動性與買賣單不平衡之間的關係,結果並不顯著,代表場內專家具有控制存貨的能力。 最後我們以買賣單不平衡為指標建立一個交易策略,結果顯示,此交易策略不僅不能打敗商業銀行的原始每日報酬率,也不能獲得顯著正報酬。 | zh_TW |
dc.description.abstract | Market efficiency, one of the most important concepts in finance field, has been the controversial issue these years. This is because there are a lot of empirical anomalies happening in real world such as small firm effect, and January effect. It is intuitive that efficiency cannot happen instantaneously in the real world. Because the information does not spread so quickly that everyone cannot obtain it at the same time. As a result, one may gain abnormal profits. However, this situation will not persist too long. The strength of various kinds of investors will push the market toward efficiency. Therefore, the goal of our study is to investigate the convergence process toward efficiency of the relation between the order imbalances of investment banks and the returns of commercial banks.
First of all, we examine the relation between returns and contemporaneous as well as lagged order imbalances by a multi-regression model. The empirical result shows that the contemporaneous imbalances have a significantly positive impact on returns, and condition on the contemporaneous imbalances, the impact of the lagged-one imbalances on returns is negative. Disregarding the contemporaneous imbalances, there are obviously large figures of negative and significant coefficients at the 10% significant level for the three time intervals. Besides, we observe a positive relation between contemporaneous imbalances and returns by the use of a GARCH(1,1) model. And both in the multi-regression model and the GARCH(1,1) model, the convergence process toward efficiency is observable. Moreover, we us a GARCH(1,1) model to examine the relation between volatility and order imbalances. The results come out to be not significant. Our explanation is that market makers have great abilities to control inventories. Finally, we build a trading strategy based on the indicator of order imbalances. Our trading strategies cannot neither yield statistically significant positive returns nor outperform original daily returns. | en |
dc.description.provenance | Made available in DSpace on 2021-06-08T04:17:18Z (GMT). No. of bitstreams: 1 ntu-99-R97723036-1.pdf: 3130090 bytes, checksum: bd8567c04cfa8887884419613a25dc38 (MD5) Previous issue date: 2010 | en |
dc.description.tableofcontents | Contents
Chapter 1 Introduction 1 1.1 Motives and Purposes 1 1.2 Framework of the Thesis 6 Chapter 2 Data and Methodology 7 2.1 The Data 7 2.1.1 Data Sources 7 2.1.2 Data Processing Methods 7 2.2 Methodology 9 2.2.1 Unconditional Lagged Return-Order Imbalances OLS Model 9 2.2.2 Conditional Contemporaneous Return-Order Imbalances OLS Model 11 2.2.3 Dynamic Return-Order Imbalance GARCH (1, 1) Model 11 2.2.4 Dynamic Volatility-Order Imbalance GARCH (1, 1) Model 13 Chapter 3 Empirical Results 15 3.1 Unconditional Lagged Return-Order Imbalances Relation 15 3.2 Conditional Contemporaneous Return-Order Imbalances Relation 16 3.3 Dynamic Return-Order Imbalance GARCH (1, 1) Relation 18 3.4 Dynamic Volatility-Order Imbalance GARCH (1, 1) Relation 19 3.5 Trading Strategy under the Basis of Trade Price 21 Chapter 4 Conclusion 24 References 27 FIGURES Figure 1: Comparison of the Impact of Contemporaneous OI on Returns between the OLS Regression Model and the GARCH (1,1) Model....34 TABLES Table3.1 Empirical Results of Unconditional Lagged Return-Order Imbalance Relation..................35 Table3.2 Empirical Results of Conditional Contemporaneous Return-Order Imbalance Relation...............54 Table3.3 Empirical Results of the Dynamic Return-Order Imbalance GARCH (1, 1) Relation................73 Table3.4 Empirical Results of the Dynamic Volatility-Order Imbalance GARCH (1, 1) Relation.................83 Table13.5 Trading Profit under the Basis of “Trade Price”.....93 | |
dc.language.iso | en | |
dc.title | 金融危機之投資銀行與商業銀行間市場效率性 | zh_TW |
dc.title | Market efficiency between Investment Banks and Commercial Banks in Financial Crisis | en |
dc.type | Thesis | |
dc.date.schoolyear | 98-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 黃漢青,胡星陽 | |
dc.subject.keyword | 金融危機,投資銀行,商業銀行,市場效率,買賣單不平衡,報酬率, | zh_TW |
dc.subject.keyword | market efficiency,investment banks,commercial banks,financial crisis,order imbalance,return, | en |
dc.relation.page | 97 | |
dc.rights.note | 未授權 | |
dc.date.accepted | 2010-07-30 | |
dc.contributor.author-college | 管理學院 | zh_TW |
dc.contributor.author-dept | 財務金融學研究所 | zh_TW |
顯示於系所單位: | 財務金融學系 |
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