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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 | Ding-Jyun Yuan | en |
dc.contributor.author | 袁鼎鈞 | zh_TW |
dc.date.accessioned | 2021-06-16T16:06:29Z | - |
dc.date.available | 2013-07-03 | |
dc.date.copyright | 2013-07-03 | |
dc.date.issued | 2013 | |
dc.date.submitted | 2013-06-17 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/62648 | - |
dc.description.abstract | 市場效率性長久以來都是財務界學者們關注的焦點。而在判斷市場是否有效率的層面而言,就市場微結構觀點,買賣單不平衡傳達總體基本面之私有資訊,因此許多文獻都針對市場交易量與股票報酬之間的關係進行深入研究。本篇論文以買賣單不均衡來衡量交易量來探討在美國量化寬鬆政策下,國際投資銀行日內買賣單不平衡與股價報酬的關係,以研究在宣布量化寬鬆政策前後市場是否具效率性。
首先我們以多元線性回歸模型分別檢驗三次量化寬鬆宣布期間七家國際投資銀行同期或前、後期之五日內買賣單不平衡對股票報酬率的影響。實證結果顯示,前一期的買賣單不平衡對報酬在不考慮當期時,其影響不如Chordia and Subrahmanyam (2004) 之結果顯著;而在考慮當期後,前期買賣單不平衡對報酬的影響之負向關係及當期買賣單不平衡對報酬的影響之正向關係,其影響也不如Chordia and Subrahmanyam (2004) 之結果顯著。 再來我們以GARCH (1,1) 模型觀察同期買賣單不平衡對報酬率的影響。結果顯示兩者有正顯著之關係。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,研究顯示其關係相較於買賣單不平衡對報酬率之影響顯著程度變小許多,代表造市者對股價波動性的控制良好。 最後,我們以買賣單不平衡為指標來建立日內的交易策略,並測試是否能夠獲得超額報酬。此以買賣單不平衡為指標之交易策略不僅無法獲得超額報酬,也無法打敗市場,故市場在此三次量化寬鬆宣布期間維持有一定效率性。 | zh_TW |
dc.description.abstract | Market efficiency has long been one of the most concerned topics in the financial industry. When it comes to judging whether the market is efficient, in the perspective of the theory of market microstructure, the order imbalance certainly conveys some information contained in the overall market. Thus, many literatures focus on the study of the relation between order imbalances and returns. This thesis uses the order imbalance as an anchor to investigate its relation with the stock returns of the international investment banks under the announcement of U.S. Quantitative Easing policy (QE1, QE2, and Operation Twist) to see whether the level of market efficiency changes regarding the pre- and post- announcement of the policy.
First we use multi-regression model to test the impact of five lagged order imbalances on stock returns of the chosen seven international investment banks during pre- and post- announcement of the policy respectively. The empirical results show that neither the negative relation of the lagged-one order imbalance nor the positive relation of the contemporaneous order imbalance is significant on the return compared with the results of Chordia and Subrahmanyam (2004). Then, we adopt the dynamic return-order imbalance GARCH (1,1) model to see the impact of the order imbalance on the return. The empirical results suggest that there exists a significant relation between these two. Besides, we also use the dynamic volatility-order imbalance GARCH (1,1) model to test the relation between volatility and the return. The empirical results indicate that the relation is not significant compared with that between the order imbalance and the return. Last, we build a trading strategy based on the intraday order imbalance to see whether we can gain abnormal returns. The result shows that we can neither secure abnormal returns nor even beat the simple buy-and-hold market strategy, which implies a certain level of market efficiency during the pre- and post-announcement of the policy. | en |
dc.description.provenance | Made available in DSpace on 2021-06-16T16:06:29Z (GMT). No. of bitstreams: 1 ntu-102-R00723077-1.pdf: 818116 bytes, checksum: 62ac5aaed9659c0431f2bbed750f1a54 (MD5) Previous issue date: 2013 | en |
dc.description.tableofcontents | CHAPTER 1 INTRODUCTION 1
1.1 Motives and Purposes 1 1.2 Literature Review 4 1.3 Framework of the Study 7 CHAPTER 2 DATA AND METHODOLOGY 8 2.1 The Data 8 2.1.1 Data Sources 8 2.1.2 Data Processing Methods 9 2.1.3 Descriptive Statistics 10 2.2 Methodology 12 2.2.1 Unconditional Lagged Return-Order Imbalance OLS Model 12 2.2.2 Conditional Contemporaneous Return-Order Imbalance OLS Model 13 2.2.3 Dynamic Return-Order Imbalance GARCH (1, 1) Model 14 2.2.4 Dynamic Volatility-Order Imbalance GARCH (1, 1) Model 15 CHAPTER 3 EMPIRICAL RESULTS 17 3.1 Unconditional Lagged Return-Order Imbalance Relation 17 3.2 Conditional Contemporaneous Return-Order Imbalance Relation 20 3.3 Dynamic Return-Order Imbalance GARCH (1, 1) Relation 24 3.4 Dynamic Volatility-Order Imbalance GARCH (1, 1) Relation 25 3.5 Trading Strategy 26 CHAPTER 4 CONCLUSION 29 REFERENCES 32 | |
dc.language.iso | en | |
dc.title | 美國量化寬鬆政策對國際投資銀行之市場效率性影響 | zh_TW |
dc.title | U.S. Quantitative Easing Policy on International Investment Bank Market Efficiency | en |
dc.type | Thesis | |
dc.date.schoolyear | 101-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 胡星陽,黃漢青 | |
dc.subject.keyword | 量化寬鬆政策,市場效率性,買賣單不平衡,交易策略,國際投資銀行, | zh_TW |
dc.subject.keyword | QE,Quantitative Easing,Market Efficiency,Order Imbalance,International Investment Bank, | en |
dc.relation.page | 108 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2013-06-17 | |
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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