臺灣博碩士論文加值系統

本篇研究主要在探討初次公開發行的股票，第一天的初始報酬、買賣單不平衡與波動性之間的關係。根據先前的研究，發現當日買賣單不平衡與當日股價報酬率存在著正向關係，尤以投機型股票為甚，而買賣單不平衡又反應著私屬資訊的存在，因此，本篇以資訊不對稱最明顯的市場—IPO股票為研究對象。
　　實證結果發現，IPO 首日日內買賣單不對稱與股價報酬率間確有顯著關係存在，再加入波動性的因子，亦發現買賣單不對稱與波動性的變化呈正相關。我們進一步以回歸模型來探討同期與前幾期的買賣單不平衡和股價報酬率之間的關係，發現同期的買賣單不平衡對當期股價報酬率有顯著的影響力，而前幾期的買賣單不平衡中，卻只有前一期的買賣單不平衡與股價報酬率有顯著的負向關係。
　　此外，我們以另一個代表著資訊不對稱的變數─公司的資本規模，來探討其與買賣單不平衡之間的關係。結果發現，在IPO當天的股價報酬變化有小型股效果的存在。最後，我們試著以觀察IPO首日的買賣單不平衡，建構出幾個交易策略，可惜結果均顯示，觀察買賣單不平衡無法帶來比初始報酬更高的超額報酬。

In this paper, we investigate the relationship among initial return, volatility and order imbalances of IPOs. Consistent with theory, the result of GARCH (1,1) model shows that order imbalances also have significant impact on initial return of IPO stocks. Further, the GARCH (1,1) model testing the relation between volatility and order imbalance suggests that volatility will arise as long as there comes in a large order imbalance order and vice versa.
In the further study of time-series regression to test the relation between order imbalances and return, we find that contemporaneous order imbalance has a good explanatory power to return. As for lagged order imbalances, only lag-one imbalances are significant negative related to return. We also have the same result in another regression test of lag-one effect. At last, we use market capitalization as the proxy of private information to investigate the relation between market capitalizations and order imbalances. The result shows that the small size effect indeed exists in IPO stocks. In the end, we build four trading strategies and compare their returns to initial return. Unfortunately, we conclude that observing order imbalance as a trading rule cannot contribute higher returns than the average initial return of IPO.

CONTENTS
Chapter 1 Introduction - 1 -
1.1 Motives and Purposes - 1 -
Chapter 2 Literature Review - 4 -
Chapter 3 Data - 8 -
3.1 Data Sources - 8 -
3.2 Data Statistics - 10 -
Chapter 4 Methodology - 12 -
4.1 GARCH(1,1) model - 12 -
─Testing the relation between return and order imbalance - 12 -
4.2 GARCH(1,1) model - 15 -
─Testing the relation between volatility and order imbalance - 15 -
4.3 Contemporaneous order imbalance-return test - 16 -
4.4 Lagged order imbalance-return test - 17 -
4.5 Small firm effect test - 17 -
4.6 Trading strategy - 19 -
Chapter 5 Empirical Results - 20 -
5.1 Dynamic relation between return and order imbalance - 20 -
5.2 Dynamic relation between volatility and order imbalance - 21 -
5.3 Time-series Regression testing the relation between contemporaneous return and order imbalance - 23 -
5.3.1 Contemporaneous imbalances Effect - 24 -
5.3.2 Lagged imbalances Effect - 24 -
5.4 Small size effect - 27 -
5.5 Trading strategies - 28 -
Chapter 6 Conclusions - 30 -
6.1 Summary of our findings in this article - 30 -
6.2 Suggestions for further researches - 31 -
References - 66 -



FIGURES
Figure I NASDAQ Index - 33 -
Figure II Distribution of Mean Order Imbalances - 33 -
Figure III Distribution of market capitalization - 34 -
Figure IV Distribution of β coefficient in the GARCH(1,1) model
【Return- order imbalance relation】 - 34 -
Figure V Distribution of β coefficient in the GARCH(1,1) model
【Volatility- order imbalance relation】 - 35 -
Figure VI Distribution of , the contemporaneous coefficient of time-series regression model - 35 -
Figure VII Distribution of , the lag-one period coefficient of time-series regression model - 36 -




TABLES
Table I Descriptive Statistics of Data - 37 -
Table II Estimators of GARCH(1,1) model - 38 -
Table III Significance of estimator - 39 -
Table IV Estimators of GARCH(1,1) model - 40 -
Table V Significance of estimator - 41 -
Table VI Results of order imbalance regressions—Lagged 0 to 4 - 42 -
Table VII Results of order imbalance regressions—Lagged 1 to 5 - 43 -
Table VIII Estimates of coefficient-firm size relation - 44 -
Table IX Returns gained by different strategies - 45 -



APPENDIX
Appendix A. The Basic information for Sample Data - 46 -
Appendix B. The Summary Statistics of Order Imbalances of Sample Data - 48 -
Appendix C. Coefficients Estimated By Garch(1,1) model - 50 -
Appendix D. Coefficients Estimated By Garch(1,1) model in testing volatility - 54 -
Appendix E. Coefficients Estimated by Contemporaneous Time-series Regression Model - 58 -
Appendix F. Coefficients Estimated By lag-one time-series regression model - 62 -

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