交易量週轉率之市場異常現象

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姓名

楊鴻傑(Hung-Chieh Yang) 查詢紙本館藏

畢業系所

財務金融學系

論文名稱

交易量週轉率之市場異常現象
(The Turnover Anomaly)

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摘要(中)

本研究發現持有交易量週轉率低的股票，並放空交易量週轉率高的股票，在未來五年內可獲得顯著的報酬，且此報酬不能經由風險因子或公司特徵因子所解釋。我們探究低週轉率溢酬持續存在的原因，發現當股票在報酬波動大、交易成本高及市場上投資人成熟度較低時，呈現較大的低週轉率溢酬，此說明低交易量溢酬持續存在的市場異常現象，乃是股票系統性訂價誤差所致。理論上市場中專業的套利者會挖掘套利機會，使得股票訂價誤差迅速消除。然而持續存在低週轉率溢酬的市場異常，暗示了套利者因某些因素而不願進入市場進行套利活動，使得股價長期偏離基本面價值。我們利用套利風險、交易成本及投資人成熟度三個指標來探討何者較能有效嚇阻套利者進行套利活動。本研究發現當股票有較高的報酬波動及股票被投資機構持有的家數越少，低週轉率溢酬是最大的。此外，股票報酬波動高相較於股票報酬波動低的低週轉率溢酬，在樣本期間36年裡，有31年較大；被機構投資人持有家數少相較於被機構投資人持有家數多的股票，低交易量溢酬亦在樣本期間25年裡，有22年是較大的。我們也證明了在控制其他套利風險、交易成本及投資人成熟度的指標後，報酬波動和投資人持有家數會加深低週轉率效應，使得低週轉率溢酬更為顯著。以上結果顯示出，套利風險及投資人成熟度是套利者是否執行套利活動最重要的考量因素。

摘要(英)

We find that stocks with lower (higher) trading turnover have higher (lower) future returns over five years, and the low turnover premium is less likely associated with compensation for risk or liquidity hypothesis. If the turnover effect presents mispricing due to systematic expectation bias, then professional arbitrageurs should exploit this opportunity and eliminate the mispricing quickly. However, the existence of low turnover premium implies that some reasons let arbitrageurs are not willing to execute arbitrage activities. We show that the low turnover premium is greater for stocks with higher idiosyncratic volatility, higher transaction costs, and lower investor sophistication, corresponding with the market-mispricing explanation for the turnover anomaly. And the stocks with high idiosyncratic volatility (Ivolatility) and stocks with low number of institutional owners (Inst#) have the greatest low turnover premium. Furthermore, the turnover effects for high Ivolatility stocks exceeds low Ivolatility stocks in 31 of the 36 sample years, and for low Inst# stocks surpasses high Inst# stocks in 22 of the 25 sample years. We also show that high Ivolatility and low Inst# will strengthen the turnover effect, beyond the other arbitrage risk, transaction costs and investor sophistication measures. This evidence suggests that high idiosyncratic volatility and low investor sophistication will deter arbitrage activities.

關鍵字(中)

★ 市場異常
★ 週轉率
★ 交易量
★ 套利風險
★ 投資人成熟度

關鍵字(英)

★ anomaly
★ turnover
★ volume
★ investor sophistication
★ arbitrage risk

論文目次

中文摘要 i
ABSTRACT ii
致謝 iii
Table of Contents iv
List of Tables v
List of Charts vi
1.Introduction 1
2.Sample, turnover-based portfolio strategies and empirical results 4
2.1 Sample 4
2.2 Turnover-based portfolio strategies 4
2.3 Return to turnover-based portfolio strategy 5
3.Could the low turnover premium be explained by compensation risk, liquidity risk or firm’s characteristics? 7
3.1 Fama-French three-factor model 7
3.3 Characteristic-base risk adjustment 9
4.Alternative explanations of the low turnover premium anomalies 11
4.1 Arbitrage risk 11
4.2 Transaction costs 12
4.3 Investor sophistication 13
4.4 Definitions of the measures of arbitrage risk, transaction costs, investor sophistication and introduce the measures sources. 14
4.5 Portfolio tests 15
4.6 Incremental role of arbitrage risk and investor sophistication 20
5.Conclusion 23
6.References 25
7.Appendix 45

參考文獻

Admati, Anat R.,and Paul Pfleiderer, 1988, “A Theory of Intraday Patterns: Volume and Price Variability,” Review of Financial Studies 1, 3-40.
Amihud, Yakov, and Haim Mendelson, 1986, “Asset Pricing and the Bid-Ask Spread,” Journal of Financial Economics 17, 223-249.
Ajinkya, Bipin B., Rowland K. Atiase, and Michael J. Gift, 1991, “Volume of Trading and the Dispersion in Financial Analysts’ Earnings Forecasts,” The Accounting Review, 66, 389-401.
Ali, Ashiq, Lee S. Hwang, and Mark A. Trombley, 2003, “Arbitrage Risk and the Book-to-Market Anomaly,” Journal of Financial Economics, 69, 355-373
Bnz, Rolf W., 1981, “The Relationship between Return and Market Value of
Common Stocks,” Journal of Financial Economics 9, 3-18.
Bartov, Eli, Suresh Radhakrishnan, and Itzak Krinsky, 2000, “Investor Sophistication and Patterms in Stock Returns after Earnings Announcements,” The Accounting Review”, 75, 43-64.
Bessembinder, Hendrik, Kalok Chan, and Paul J. Seguin, 1996, “An Empirical Examination of Information, Differences of Opinion, and Trading Activity,” Journal of financial Economics, 40, 105-134.
Bessembinder, Hendrik, and Paul J. Seguin, 1993, “Price Volatility, Trading Volume, and Market Depth: Evidence from the Futures Markets,” Journal of Financial and Quantitative Analysis, 28, 21-39.
Bhardwaj, Ravinder K., and Leroy D. Brooks, 1992, “The January Anomaly: Effects of Low Share Price, Transaction Costs and Bid-Ask Bias,” Journal of Finance, 47, 553-575.
Bhushun, Ravi, 1992, “Trading Costs, Liquidity and Asset Holdings,” Review of Financial Studies,” 4, 343-360.
Bhushun, Ravi, 1994, “An Informational Efficiency Perspective on the Post-Earnings Announcement Drift,” Journal of Accounting and Economics, 18, 45-65.
Blume, Marshall E., and Michael A. Goldstein, 1992, “Displayed and Effective Spreads by Market,” Unpublished Working Paper. Wharton School, University of Pennsylvania.
Brennan, Michael J., Narasimhan Jagadeesh, and Bhaskaran Swaminathan, 1993, “Investment Analysis and the Adjustment of Stock Prices to Common Information,” Review of Financial studies, 6, 799-824.
Chen, Joseph, Harrison Hong, and Jeremy C. Stein, 2002, “Breadth of Ownership and Stock Returns,” Journal of Financial Economics, 66, 171-205.
Chordia, Tarun, and Bhaskaran Swaminathan, 2000, “Trading Volume and Cross-Autocorrelation in Stock Returns,” The Journal of Finance, 55, 913-935.
Comiskey, Eugene E., Ralph A. Walkling, and Michael A. Weeks. 1987, “Dispersion of expectations and trading volume,” Journal of Business Financial & Accounting 14 (Summer): 229-239.
Cooper, Michael, 1999, “Filter Rules Based on Price and Volume in Individual Security Overreaction,” Review of Financial Studies, 12, 901-935.
Datar, Vinay T., Naik Y. Narayan, and Robert Radcliffe, 1998, “Liquidity and Asset Returns: An Alternate Test,” Journal of Financial Market 1, 203-219.
Daniel, Kent, and Sheridan Titman, 1997,”Evidence on the Characteristics of
Cross-Sectional Variation in Common Stock Returns,” Journal of Finance
52, 1-33.
Dechow, Patricia M., Amy P. Hutton, Lisa Meulbroek, and Richard G. Sloan, 2001, “Short-Sellers, Fundamental Analysis and Stock Returns,” Journal of Financial Economics, 61, 77-106
Fama, Eugene F., and Kenneth R. French, 1992, “The Cross-Section of Expected Stock Returns,” Journal of Finance, 46, 427-466.
Fama, Eugene F., and Kenneth R. French, 1993, “Common Risk Factors in the Returns on Stocks and Bonds,” Journal of Financial Economics, 33, 3-56.
Fama, Eugene F., and Kenneth R. French, 1996, “Multifactor Explanations of Asset Pricing Anomalies,” Journal of Finance, 51, 55-84.
Fama, Eugene F., and James D. MacBeth, 1973, “Risk, Return and Equilibrium: Empirical Tests,” Journal of Political Economy, 81, 607-636.
Foster, F.D., and S. Viswanathan, 1990, “A Theory of the Interday Variations in Volume, Variance and Trading Costs in Securities,” Review of Financial Studies, 3,593-624.
Hong, Herrison, Terence Lim, and Jeremy Stein, 2000, “Bad News Travels Slowly: Size, Analyst Coverage, and the Profitability of Momentum Strategies,” Journal of Finance, 55, 265-295.
Gervais, Simon, Ron Kaniel, and Dan H. Mingelgrin, 2001, “The High-Volume Return Premium,” The Journal of Finance, 56, 877-919.
Ippoloto, Richard A., 1992, “Consumer Reaction to Measures of Poor Quality: Evidence from the Mutual Fund Industry,” Journal of Law and Economics, 35, 45-70.
Jegadeesh, Narasimhan, and Sheridan Titman, 1993, “Returns to Buying Winners and Selling Losers; Implications for Stock Market Efficiency,” Journal of Finance, 48, 65-91.
Karpoff, Jonathan M., 1987, “The Relation Between Price Changes and Trading Volume: A Survey,” Journal of Financial and Quantitative Analysis, 22, 109-126.
Kyle, Albert S., 1985, “Continues Auctions and Insider Trading,” Econometrica, 53, 1315-1335.
Lakonishik, Josef, Andrei Shleifer, and Robert W. Vishny, 1994, “Contrarian Investment, Extrapolation and Risk,” Journal of Finance, 49, 1541-1578.
Lee, Charles M.C., and Bhaskaran Swaminathan, 2000, “Price Momentum and Trading Volume,” The Journal of Finance, 55, 2017-2069.
Lesmond, D.A., J.P. Ogden, and C.A. Trzcinka, 1999, “A New Estimate of Transaction Costs,” Review of Financial Studies, 12, 1113-1141.
Llorente, Guillermo, Roni Michaely, Gideon Saar, and Jiang Wang, 2002, “Dynamic Volume-Return Relation of Individual Stocks,” Review of Financial Studies, 15, 1005-1047.
Lo, Andrew W., and Jiang Wang, 2000, “Trading Volume: Definitions, Data Analysis, and Implications of Portfolio Theory,” The Review of Financial Studies, 13, 257-300.
Newey, Whitney K., and Kenneth D. West, 1987, “Hypothesis Testing with Efficient Method of Moments Estimation,” International Economic Review, 28, 777-787.
Rosenberg, Barr, Kenneth Reid, and Ronald Lanstein, 1985,”Persuasive Evidence of Market Inefficiency,” Journal of Portfolio Management 11,9-17.
Shleifer, Andrei, Robert W. Vishny, 1997, “The Limits of Arbitrage,” Journal of Finance, 52, 35-55.
Stoll, Hans R., and Robert E. Whaley, 1987, “Program Trading and Expiration Day Effects,” Financial Analysts Journal, 43, 16-28.
Warther, Vincent A., 1995, “Aggregate Mutual Fund Flows and Security Returns,” Journal of Financial Economics, 39, 209-236.

指導教授

周賓凰(Pin-Huang Chou)

審核日期

2010-7-20

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