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研究生:方豪
研究生(外文):Hao Fang
論文名稱:臺灣股市三大法人群聚的實證研究
論文名稱(外文):An Empirical Study of Herding for the Three Major Types of Institutional Investors in the Taiwan Stock Market
指導教授:翁振益翁振益引用關係盧陽正盧陽正引用關係
指導教授(外文):Jehn-Yih WongYang-Cheng Lu
學位類別:博士
校院名稱:銘傳大學
系所名稱:管理研究所
學門:商業及管理學門
學類:企業管理學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:英文
論文頁數:98
中文關鍵詞:法人群聚的價格影響群聚回饋交易串流
外文關鍵詞:herdingfeedback tradingcascadesthe price-impact of herdinginstitutional investors.
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本研究檢測臺灣股市三大法人的持股改變與家數及金額的買賣超之群聚衡量,是否會伴隨著群聚效應、回饋交易、串流及群聚的價格影響。本研究釐清在臺灣法人群聚行為,是否導源於資訊串流而非習慣性投資,且其群聚行為發生在那些特質性的股票。本研究建構一個更嚴謹的二維研究設計以釐清法人持股改變與報酬率、盈餘、淨值市價比或公司規模中之何項因子,能有效地解釋股票的超常報酬率,並調查介於持有期間的超常報酬率與相對應法人持股改變之間的橫斷面及時間序列關聯性。最後,本研究使用一個縱橫門檻迴歸模型以探討股市法人群聚對價格的變動是否會受公司規模所影響。
本研究重要的研究結果列示如下:
1. 外資及投信持股改變存在群聚效應,但自營商持股改變並沒有群聚效應。介於外資及投信持股改變與超常報酬率之間的群聚效應,主要源自於”持股改變驅動超常報酬率”。外資及投信持股改變展現正向回饋交易及串流現象;而自營商持股改變呈現負向回饋交易且不具串流現象。
2. QFIIs短期買超群聚衡量及其中長期賣超金額比率的群聚效應,導源於其正向回饋交易;然而QFIIs短中長期賣超群聚衡量,並未產生任何群聚效應。QFIIs短中期買超金額比率有明顯的群聚效應,其主要源自於群聚的價格影響。
3.本研究證實在考量動量交易下相臨兩個月QFIIs買進的比率有顯著的正相關。本研究更發現QFIIs資訊串流著重在過去贏家的股票、高度流動性的股票及成長性的股票。
4.二維研究設計的結果顯示報酬率、盈餘、淨值市價比及公司規模與三大法人持股改變,對不同持有期間超常報酬率都有明顯的影響。 此外,由前述四個變數中的任何一個所驅動的超常報酬率,都可能因為法人群聚程度而有所差異,且其相關性為正向。更重要的是,投資人可視”三大法人在持有期間的持股改變”為一項”短期追隨且反向調整”的訊號。
5.因為在臺灣股市外資傾向於操作臺灣上市公司中較大規模股票的價格,此種股票多被外資大幅買進,因而在後續超常報酬率有明顯的增加。一般投資人若追隨外資買進大規模廠商的股票,尤其是電子及塑膠產業並且持有這些投資組合一個月,將可獲得正向的超常報酬率。
This study examines whether share ownership adjustments and the herding measures of overbought and oversold on numbers and dollar amount by institutional investors in the Taiwan stock market are accompanied by herding effect, feedback trading, cascading and herding impact on price. This study clarifies whether institutional herding behavior in Taiwan results mainly from informational cascades rather than habit investing and on what types of stocks such herding behaviors occur. This study constructs a more rigorous two-dimensional research procedure to clarify which factor, including changes in institutional ownership with past returns, earnings, book-to-market ratio effect, or size effect can effectively interpret abnormal returns on stocks, and investigate the cross-sectional and time-series correlations between abnormal returns during holding periods and corresponding changes in institutional ownership. This study finally uses a panel threshold regression model to explore whether the price impact of institutional herding in this stock market is affected by firm size.
The most important outcomes of this study are listed below:
1.Herding effect was observed in share ownership adjustments of foreign investors and mutual funds, but not in share ownership changes of dealers. The herding effect between changes in share ownership of foreign investors and mutual funds and abnormal returns stems primarily from “changes in their share ownership driving abnormal returns”. Share ownership adjustments of foreign investors and mutual funds exhibit positive feedback trading and cascading, whereas negative feedback trading and no cascading were observed in changes in share ownership of dealers.
2.The short-term overbought herding measure and the mid-to-long-term oversold in dollar ratio by QFIIs are associated with herding effects resulting from positive feedback trading among QFIIs; however, short-to-mid-term and long-term oversold herding measures by QFIIs do not generate any herding effect. The short-to mid-term overbought in dollar ratio by QFIIs is associated with clear herding effects, resulting primarily from the price impact of herding.
3. This study demonstrates that there is a significantly positive relation in the fraction of QFIIs’ buying over the adjacent two months even after taking the momentum trading into account. We find that QFIIs’ informational cascades are focused on past winner stocks, highly-liquid stocks, and glamour stocks.
4. The two-dimensional research design revealed that all of the above variables and changes in share ownership of the three major types of institutional investors have remarkable influences on abnormal returns over various holding periods. In addition, the abnormal returns driven by any of the four variables proposed previously may vary depending on the level of herding; their correlations are positive. Most importantly, investors may regard “changes in shareholding by three major institutional investors during the holding period” as a signal of “short-term following and reverse adjustment.”
5. Since foreign investors in the Taiwan stock market prefer to hold large-size stocks in the TSE-listed firms, there is an apparent increase in the subsequent abnormal returns on such stocks bought in bulk by foreign investors. Other investors could follow foreign investors to purchase stocks of large-size firms in generally electronics and plastics sectors and hold them for one month to obtain positive abnormal returns.
Table of Contents

page
Chinese Abstract Ⅰ
Abstract Ⅲ
Table of Contents Ⅴ
List of Figures Ⅶ
List of Tables Ⅷ
1. Introduction 1
1.1 Background and motivation 1
1.2 Research goals 4
1.3 Brief of contents, contribution and scheme of papers 5
2. Literature Review 9
2.1 Herding effect, feedback trading, cascading and price- impact of herding 9
2.2 The main cause of institutional herding and the characteristics of their herding stocks 10
2.3 Institutional herding premium and persistence 11
2.4 Price impact of institutional herding of small-size stock 12
3. Methodology 14
3.1 Measurements of the variables 14
3.1.1 Measurements of institutional herding 14
3.1.2 Abnormal returns 19
3.1.3 Measurements of other factors affecting stock returns 20
3.2 Herding effect, feedback trading and herding impact on price 22
3.2.1 Herding effect 22
3.2.2 Feedback trading, cascading and herding impact on price 23
3.2.3 Causal direction of herding effect 24
3.2.4 Cross-sectional weighted regression 25
3.3 Model specification of QFIIs’ cascades 26
3.3.1 Basic model of QFIIs’ cascades 26
3.3.2 PSTR model of QFIIs’ cascades 27
3.4 Two-way sorting and influence of changes in institutional ownership on persistence 29
3.5 The price impact of institutional herding of firm size 30
4. Empirical Results 35
4.1 Herding, feedback trading and price impact of overbought and oversold by institutional investors 35
4.1.1 Data scope 35
4.1.2 The herding effects 36
4.1.3 Distinguishing feedback trading from price impact of herding 39
4.1.4 Feedback trading and cascading 42
4.1.5 Momentum and contrarian effects on herding 46
4.2 QFIIs’ cascades 51
4.2.1 Source, scope and analysis of the data 51
4.2.2 Results of basic model 52
4.2.3 Results of PSTR model 54
4.3 Herding premium driven by changes in institutional ownership 59
4.3.1 Types of sampling 59
4.3.2 Results of two-way sorting 60
4.3.3 Influence of changes in institutional ownership on persistence 63
4.4 Price impact of institutional herding of large-size stocks 74
4.4.1 Types of sampling 74
4.4.2 The basic statistics of data and the use of panel unit root 74
4.4.3 Results of test and estimation 75
5. Conclusion 80
5.1 The conclusion of empirical results…………………………………..80
5.2 Managerial content and contribution………………………………..82
Reference 85






List of Figures

Page
Figure 1-1 Research scheme of this study 8
Figure 3-1 The figure of signifying portfolio composition of large increase in share ownership of the three major types of institutional investors 15
Figure 3-2 The figure in signifying test of herding effect 23
Figure 3-3 The figure in signifying test of positive feedback trading and momentum effect of herding 24
Figure 3-4 The figure in signifying test of cascading effect 24
Figure 3-5 Two-way simultaneous sorting procedure 30
Figure 3-6 The mediating influence of subsequent changes in share ownership of the three major types of institutional investors on abnormal returns 30
Figure 4-1 Relation between the logistic transition function and the
transition variable of return. 58
Figure 4-2 Relation between the logistic transition function and the transition variable of turnover. 59
Figure 4-3 Relation between the logistic transition function and transition variable of the book-to-market ratio. 59
Figure 4-4 Confidence interval construction in single threshold model 79
Figure 4-5 Number of firms in small-size and large-size regimes each month 79



List of Tables

Page
Table 4-1 The herding abnormal returns of the change in three major types of institutional investors’ ownership portfolios 38
Table 4-2 The causation between changes in ownership of three major types of institutional investors and abnormal returns—Granger causality test 41
Table 4-3 Momentum effects of three major types of institutional investors 44
Table 4-4 Feedback trading and cascading of changes in ownership portfolios of three major types of institutional investors 49
Table 4-5 Descriptive statistics of QFIIs 51
Table 4-6 Pooled and panel regressions of the fraction of QFIIs’ buying on the lag fraction of QFIIs’ buying and lag return 53
Table 4-7 One-way sorting procedure for QFIIs’ informational cascades and positive feedback trading 53
Table 4-8 Pooled regression within the largest and smallest quintiles based on return, turnover and the book-to-market ratio 54
Table 4-9 Number of regimes using the test for linearity against the PSTR with return as the transition variable 56
Table 4-10 Number of regimes using the test for linearity against the PSTR with turnover as the transition variable 56
Table 4-11 Number of regimes using the test for linearity against the PSTR with book-to-market ratio as the transition variable 56
Table 4-12 Parameter estimates of the PSTR model with return as the transition variable 57
Table 4-13 Parameter estimates of the PSTR model with turnover as the transition variable 57
Table 4-14 Parameter estimates of the PSTR model with the book-to-market ratio as the transition variable 58
Table 4-15 Subsequent returns for stocks sorted by returns and institutional ownership changes 66
Table 4-16 Subsequent returns for stocks sorted by earnings and institutional ownership changes 67
Table 4-17 Subsequent returns for stocks sorted by B/M and institutional ownership changes 68
Table 4-18 Subsequent returns for stocks sorted by size and institutional ownership changes 69
Table 4-19 Performance and persistence of stocks with subsequent biggest increase and decrease in institutional share ownership in returns’ winners and losers 70
Table 4-20 Performance and persistence of stocks with subsequent biggest increase and decrease in institutional share ownership in earnings’ winners and losers 71
Table 4-21 Performance and persistence of stocks with subsequent biggest increase and decrease in institutional share ownership in BE/ME winners and losers 72
Table 4-22 Performance and persistence of stocks with subsequent biggest increase and decrease in institutional share ownership in size’s winners and losers 73
Table 4-23 Summary statistics of variables 75
Table 4-24 Tests for threshold effects and threshold estimates of firm size 77
Table 4-25 Number of firms in each regime by year 77
Table 4-26 Regression estimates: single threshold model of firm size 77
Table 4-27 The basic statistics of market equity in small-and large-sized regimes of different industries 78
Reference:
1.Arbel, A., Carvell, S. and Strebel, P. (1983). Giraffes, Institutions, and Neglected Firms, Financial Analysts Journal, 39(3), 57-63.
2.Banerjee, A. (1992). A Simple Model of Herd Behavior, The Quarterly Journal of Economics, 107(3), 797-817.
3.Bikhchandani, S., and Sharma, S. (2001). Herd Behavior in Financial Markets, Staff Papers, International Monetary Fund, 47(3), 279-310.
4.Bikhchandani, S., Hirshleifer, D., and Welch, I. (1992). A Theory of Fads, Fashion, Custom, and Cultural Change as Informational Cascades, Journal of Political Economy, 100(5), 992-1026.
5.Borensztein, E., and Gelos, R. G. (2003). A Panic-Prone Pack? The Behavior of Emerging Market Mutual Funds, Staff Papers, International Monetary Fund, 50(1), 43-63.
6.Chakravarty, S. (2001). Stealth Trading: Which Traders’ Trades Move Prices? Journal of Financial Economics, 61(3), 289-307.
7.Chan, K. S., (1993). Consistency and Limiting Distribution of the Least Squares Estimator of a Threshold Autoregressive Model, The Annals of Statistics, 21, 520-533.
8.Chan, L. K., Jegadeesh, C. N. and Lakonishok, J. (1996). Momentum Strategies, Journal of Finance, 51(5), 1681-1713.
9.Chari, V. V. and Kehoe, P. (1999). Financial Crises as Herds, Mimeo, Federal Reserve Bank of Minneapolis.
10.Daniel, K. and Titman, S. (1997). Evidence on the Characteristics of Cross Sectional Variation in Stock Returns, Journal of Finance, 52(1), 1-33.
11.Davies, R. B. (1977). Hypothesis Testing When a Nuisance Parameter Is Present Only Under the Alternative, Biometrika, 64(2), 247-254.
12.Davis, R. B. (1987). Hypothesis Testing When a Nuisance Parameter Is Present Only under the Alternative, Biometrika, 74(1), 33-43.
13.De Long, J. B., Shleifer, A., Summers, L. H. and Waldmann, R. J. (1990). Noise Trader Risk in Financial Markets, Journal of Political Economy, 98(4), 703-738.
14.Del Guercio, D. (1996). The Distorting Effect of the Prudent-Man Laws on Institutional Equity Investment, Journal of Financial Economics, 40(1), 31-62.
15.Dennis, P. and Weston J. (2000). Who’s Informed? An Analysis of Stock Ownership and Informed Trading, Working paper, University of Virginia and Rice University.
16.Dissanaike, G. (1994). On Computation of Return in Test of the Stock Market Overreaction Hypothesis, Journal of Banking and Finance, 18(6), 1083-1094.
17.Falkenstein E. G. (1996). Preferences for Stock Characteristics as Revealed by Mutual Fund Portfolio Holdings, The Journal of Finance, 51(1), 111-136.
18.Fama, E. F. and French, K. R. (1993). Common Risk Factors in the Returns on Stocks and Bonds, Journal of Financial Economics, 33(1), 3-56.
19.Fama, E. F. and French, K. R., (1996). Multifactor Explanations of Asset Pricing Anomalies, Journal of Finance, 51(1), 55-84.
20.Fama, E. F. and French, K. R., (1995). Size and Book-to-Market Factors in Ernings and Rturns, Journal of Finance, 50(1), 131-156.
21.Fama, E. F. and French, K. R. (1992). The Cross-Section of Expected Stock Returns, Journal of Finance, 47(2), 427-465.
22.Fama, E. and MacBeth, J. (1973). Risk, Return, and Equilibrium: Empirical Tests, Journal of Political Economy, 81(3), 607-636.
23.Froot, K. A., Scharfstein, D. S. and Stein, J. C. (1992). Herd on the Street Informational Inefficiencies in a Market with Short-term Speculation,” Journal of Finance, 47(4), 1461-1484.
24.Gompers, P. and Metrick, A. (2001). Institutional Investors and Equity Prices, Quarterly Journal of Economics, 116(3), 229-260.
25.Gonzalez, A., Terasvirta, T. and Dijk, D. (2004). Panel Smooth Transition Regression Model and an Application to Investment under Credit Constraints, working paper, Stockholm School of Economics.
26.Granger, C. W. J. and Hall, R.E. (1993). Modeling Nonlinear Economic Relationship, Oxford: Oxford University Press.
27.Granger, C. W. J. (1969). Investigating Causal Relations Using by Econometric Models and Cross-Spectral Methods, Econometrica, 37(3), 424-438.
28.Grinblatt, M. and Keloharju, T. (2000). What Makes Investors Trade? Journal of Finance, 56 (2), 589-616.
29.Grinblatt, M., Titman, S. and Wermer, R. (1995). Momentum Investment Strategies, Portfolio Performance, and Herding: A Study of Mutual Fund Behavior, American Economic Review, 85(5), 1088-1105.
30.Hadri (2001). Testing for Stationarity in Heterogeneous Panel Data, Econometrics Journal, 3(2), 148-161.
31.Hansen, B. E. (1996). Inference when a Nuisance Parameter Is not Identified under the Null Hypothesis, Econometrica, 64(2), 413-430.
32.Hansen, B. E. (1999). Threshold Effects in non-Dynamic Panels: Estimation, Testing and Inference, Journal of Econometrics, 93(2), 345-368.
33.Hessel, C. A., Norman, M., (1992). Financial Characteristics of Neglected and Institutionally Held stocks, Journal of Accounting Auditing & Finance. 7(3), 313-334.
34.Hirshleifer, D., Subrahmanyam, A. and Titman, S. (1994). Security Analysis and Trading Patterns When Some Investors Receive Information before Others, Journal of Finance, 49(5), 1665-1698.
35.Hotchkiss, E. and Strickland, D. (2003). Does Shareholder Composition Matter? Evidence from the Market Reaction to Corporate Earnings announcements, Journal of Finance, 58(4), 1469-1498.
36.Im, K. S., Pesaran, M. H. and Shin, Y. (1997). Testing for Unit Roots in Heterogeneous Panels, working paper, Department of Applied Economics, University of Cambridge.
37.Jang, G. S. (2000). Study on Transmitting Structure between the Three Major Types of Institutional Investors and General Investors in the Taiwan Stock Market- an Example of New-year Effect, Security Financial, 64, 87-105.
38.Jegadeesh, N. and Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency, Journal of Finance, 48(1), 65-91.
39.Jones, S. L. and Winters, D. B. (1999). Delayed Reaction in Stocks with the Characteristics of Past Winners: Implications for Momentum, Value, and Institutional Following, Quarterly journal of Business and Economics, 38(1), 21-39.
40.Lakonishok, J., Shleifer, A. and Vishny, R. W. (1992). The Impact of Institutional Trading on Stock Prices, Journal of Financial Economics, 32(1), 23-43.
41.Lakonishok, J., Shleifer, A. and Vishny, R. W. (1994). Contrarian Investment Extrapolation and Risk, Journal of Finance, 49(5), 1541-1578.
42.Levin, A., Lin, C. F. and Chu, C. S. (2002). Unit Root Tests in Panel Data: Asymptotic and Finite-Sample Properities, Journal of Econometrics, 108(1), 1-24
43.Lin, A. Y., Swanson, P. E. (2003). The Behavior and Performance of Foreign Investor in Emerging Equity Markets: Evidence from Taiwan, International Review of Finance, 4(3-4), 189-210.
44.Lu, Y. C., Wong, J. Y. and Fang, H. (2008). Herding Effect, Feedback Trading, Cascading, and Momentum by Share Ownership Adjustments of Institutional Investors, Journal of Management & System, 15(4), 523-543.
45.Luukkonen, R., Saikkonen, P. and Terasvirta, T. (1988). Testing Linearity against Smooth Transition Autoregressive Models, Biometrika, 75(3), 491-499.
46.Nofsinger, J. R. and Sias, R. W. (1999). Herding and Feedback Trading by Institutional and Individual Investors, Journal of Finance, 54(6), 2263-2295.
47.Shiu, I. P. and Liau, Y. H. (2005). Study on Interaction between the Overbought and Oversold of the Three major Types of Institutional Investors and the Weighted Stock index in Taiwan, The monthly publication of security counter, 114(1), 56-67.
48.Sias, R., Starks, L. and Titman, S. (2002). The Price Impact of Institutional Trading, working paper, Washington State University and University of Texas.
49.Sias, R.W. (2004). Institutional Herding, The Review of Financial Studies, 17(1), 165-206.
50.Wermers, R. (1999). Mutual Fund Herding and the Impact on Stock Prices, Journal of Finance, 54(2), 581-622.
51. Wermers, R. (2000). Mutual Fund Performance: An Empirical Decomposition into Stock-Picking Talent, Style, Transactions Costs, and Expenses, Journal of Finance, 55(5), 1655-1695.
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