English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113656/144643 (79%)
Visitors : 51739775      Online Users : 497
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    政大機構典藏 > 商學院 > 金融學系 > 學位論文 >  Item 140.119/98854
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/98854


    Title: 基於流動性風險衡量下之Beta套利交易策略
    A Liquidity Based Betting-Against-Beta Strategy
    Authors: 黃書安
    Huang, Shu An
    Contributors: 江彌修
    Chiang, Mi Hsiu
    黃書安
    Huang, Shu An
    Keywords: 低風險異常報酬
    Beta套利交易策略
    流動性指標
    Low Risk Anomalies
    Betting-Against-Beta
    Liquidity Indicator
    Date: 2016
    Issue Date: 2016-07-11 17:04:18 (UTC+8)
    Abstract: 低風險異常報酬(Low Risk Anomalies)於近年來被廣泛探討,許多研究紛紛提出造成該現象的原因,其中Frazzini and Pedersen (2014)更是提出Beta套利交易策略並從該異常現象中獲利。故本文之研究目的在於探討該策略於近年的美國股票市場是否仍有效,同時,亦探討流動性指標的加入是否能改良原始的Beta套利交易策略。本研究以1996年至2015年美國股票市場所有的股票為研究樣本,資料來源為CRSP資料庫以及WRDS資料庫。實證結果顯示該異常現象仍存在於美國股票市場,且Beta套利交易策略仍能獲利。此外,加入Zhou (2014)所使用的流動性指標於該策略中,發現流動性指標的加入的確能提高傳統Beta套利交易策略的獲利,然而該策略於足以造成系統性風險並影響市場流動性的金融危機時,流動性指標的加入則無法有效提高傳統Beta套利交易策略的獲利。
    Empirical shows that low volatility stocks have consistently delivered higher average returns than high volatility stocks. Several explanations of this “low risk anomalies” have been advanced, but the topic remains open. The most prominent study is Frazzini and Pedersen (2014), which constructs a beta arbitrage trading strategy – “betting-against-beta strategy”. This trading strategy is a portfolio that holds low beta stocks and shorts high beta stocks, which empirically shows that investors could take advantage of the outperformance of low volatility stocks. Hence, this paper seeks to examine two practical questions. First, we ascertain whether the low risk anomalies still exist in recent period and determine the profitability of betting-against-beta strategy. Second, we add a liquidity indicator to the traditional betting-against-beta strategy, discussing whether the liquidity based betting-against-beta strategy could enhance the magnitude of abnormal return. All available US common stocks data, ranging from January 1996 to December 2015, are obtained from the CRSP and WRDS. Strong evidence shows that low risk anomalies still exist and betting-against-beta strategy but generates positive returns. Last but not least, although this new liquidity based betting-against-beta strategy does not work during the severe economic downturn, it could significantly boost the magnitude of the profitability under normal economic status.
    Reference: Amihud, Y. (2002). Illiquidity and Stock Returns: Cross-Section and Time-Series Effects. Journal of Financial Markets, 5(1), pp. 31-56.
    Amihud, Y. and H. Mendelson. (1986). Asset Pricing and the Bid-Ask Spread. Journal of Financial Economics, 17(2), pp. 223-249.
    Ang, A., R.J. Hodrick, Y. Xing and X. Zhang. (2006). The Cross-Section of Volatility and Expected Returns. The Journal of Finance, 61(1), pp. 259-299.
    Ang, A., R.J. Hodrick, Y. Xing and X. Zhang. (2009). High Idiosyncratic Volatility and Low Returns: International and Further U.S. Evidence. Journal of Financial Economic, 91(1), pp. 1-23.
    Auer, B.R. and F. Schuhmacher. (2015). Liquid Betting against Beta in Dow Jones Industrial Average Stocks. Financial Analysts Journal, 71(6), pp. 30-43.
    Avramov, D., T. Chordia, G. Jostova and A. Philipov . (2007). Momentum and Credit Rating. Journal of Finance, 62(5), pp. 2503–2520.
    Baker, M. and J. Stein. (2004). Market Liquidity as a Sentiment Indicator. Journal of Financial Market, 7, pp. 271-299.
    Baker, M., B. Bradley and J. Wurgler. (2011). Benchmarks as Limits to Arbitrage:Understanding the Low-Volatility Anomaly. Financial Analysts Journal, 67(1), pp. 40-54.
    Baker, M., B. Bradley and R. Taliaferro. (2014). The Low-Risk Anomaly: A Decomposition into Micro and Macro Effects. Financial Analysts Journal, 70(2).
    Bali, T.G., N. Cakici and R.F. Whitelaw. (2011). Maxing Out: Stocks as Lotteries and the Cross-section of Expected Returns. Journal of Financial Economics, 99, pp. 427-446.
    Barberis, H. and M. Huang. (2008). Stocks as Lotteries: The Implications of Probability Weighting for Security Prices. American Economic Review, 98(5), pp. 2066-2100.
    Black, F. (1972). Capital Market Equilibrium with Restricted Borrowing. The Journal of Business, 45(3), pp. 444-455.
    Black, F., M.C. Jensen and M.Scholes. (1972). The Capital Asset Pricing Model: Some Empirical Tests. In M. Jensen, Studies in the Theory of Capital Markets. New York: Praeger.
    Blitz, D., J. Pang and P. van Vliet. (2013). The Volatility Effect in Emerging Markets. Emerging Markets Review, 16, pp. 31-45.
    Blitz, D., P. van Vliet. (2007). The Volatility Effect: Lower Risk Without Lower Return. Journal of Portfolio Management, 34(1), pp. 102-113.
    Blume, L., D. Easley and M. O`Hara. (1994). Market Statistics and Technical Analysis: The Role of Volume. Journal of Finance, 49(1), pp. 153-181.
    Blume, M. (1975). Betas and Their Regression Tendencies. Journal of Finance, 30(3), pp. 785-795.
    Bouchaud, J., S. Ciliberti, A. Landier, G. Simon and D. Thesmar. (2016). The Excess Returns of"Quality" Stocks:A Behavioral Anomaly. Research Paper, HEC Paris.
    Bradley, D.J., J.W. Cooney, S.D. Dolvin and B.D. Jordan. (2006). Penny Stock IPOs. Financial Management, 35(1), pp. 5-29.
    Brunnermeier, M.K., C. Gollier, J.A. Parker. (2007). Optimal Beliefs, Asset Prices, and the Preference for Skewed Returns. American Economic Review, 97(2), pp. 159-165.
    Carhart, M. (1997). On Persistence in Mutual Fund Performance. Journal of Finance, 52(1), pp. 57-82.
    Chordia, T., A. Subrahmanyam and Q. Tong. (2014). Have Capital Market Anomalies Attenuated in the Recent Era of High Liquidity and Trading Activity? Journal of Accounting and Economics, 58(1), pp. 41-58.
    Chow, T., J. Hsu, L. Kuo and F. Li. (2014). A Study of Low Volatility Portfolio Construction Methods. Journal of Portfolio Management, 40(4), pp. 89-105.
    Clarka, E. and K. Kassimatis. (2014). Exploiting Stochastic Dominance to Generate Abnormal Stock Returns. Journal of Financial Markets, 20, pp. 20-38.
    Clarke, R., H. de Silva and S. Thorley. (2006). Minimum-Variance Portfolios in the U.S. Equity Market. Journal of Portfolio Management, 33(1), pp. 10-24.
    Cornell, B., R. Roll. (2009). The Pricing of Volatility and Skewness: A New Interpretation. The Journal of Investing, 18(3), pp. 27-30.
    Datar, V.T., N.Y. Naik and R. Radcliffe. (1998). Liquidity and Stock Returns: An Alternative Test. Journal of Financial Markets, 1(2), pp. 203-219.
    De Santis, G. and B. Gérard. (1997). International Asset Pricing and Portfolio Diversification with Time-Varying Risk. Journal of Finance, 52(5), pp. 1881-1912.
    DeLong, J.B. and K. Magin. (2006). A Short Note on the Size of the Dot-Com Bubble. Working Paper, NBER.
    Dimson, E. (1979). Risk measurement when shares are subject to infrequent trading. Journal of Financial Economics, 7(2), pp. 197-226.
    Fabozzi, F. and J. Francis. (1978). Beta as a Random Coefficient. Journal of Financial and Quantitative Analysis, 1, pp. 101-116.
    Fama, E.F. and K.R. French. (1992). The Cross-Section of Expected Stock Returns. Journal of Finance, 47(2), pp. 427–465.
    Fama, E.F. and K.R. French. (1996). Multifactor Explanations of Asset Pricing Anomalies. Journal of Finance, 51(1), pp. 55-84.
    Frazzini, A. and L.H. Pedersen. (2014). Betting Against Beta. Journal of Financial Economics, 111(1), pp. 1-25.
    García-Feijóo, L., CFA, CIPM, L. Kochard, CFA, R.N. Sullivan, CFA, and Peng Wang, CFA. (2014). Low-Volatility Cycles: The Influence of Valuation and Momentum on Low-Volatility Portfolios. Financial Analysts Journal, 71(3), pp. 47-60.
    Glosten, L.R., R. Jagannathan and D.E. Runkle. (1993). On the Relation between the Expected Value and the Volatility of the Nominal Excess Return. Journal of Finance, 48(5), pp. 1779-1801.
    Harris, L. (1990). Estimation of Stock Price Variances and Serial Covariances from Discrete Observations. Journal of Financial and Quantitative Analysis, pp. 291-306.
    Harvey, C.R. and A. Siddique. (2000). Conditional Skewness in Asset Pricing Tests. Journal of Finance, 55, pp. 1263–1295.
    Hasbrouck, J. (2009). Trading Costs and Returns for US Equities: Estimating Effective Costs from Daily Data. Journal of Finance, 64(3), pp. 1445-1477.
    Haugen, R.A. and A.J. Heins. (1975). Risk and the Rate of Return on Financial Assets: Some Old Wine in New Bottles. Journal of Financial and Quantitative Analysis, 10(5), pp. 775-784.
    Hsu, J.C., H. Kudoh and T. Yamada . (2013). When Sell-Side Analysts Meet High-Volatility Stocks: An Alternative Explanation for the Low-Volatility Puzzle. Journal of Investment Management, 11(2), pp. 28-46.
    Jegadeesh, N. and S. Titman. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), pp. 65-91.
    Kraus, A. and R.H. Litzenberger. (1976). Skewness Preference and the Valuation of Risk Assets. Journal of Finance, 31, pp. 1085-1100.
    Kumar, A. (2009). Who Gambles in the Stock Market? Journal of Finance, 64(4), pp. 1889–1933.
    Lee, C.M.C. and B. Swaminathan. (2000). Price Momentum and Trading Volume. Journal of Finance, 55(5), pp. 2017–2069.
    Lesmond, D.A., M.J. Schill and C. Zhou. (2004). The illusory nature of momentum profits. Journal of Financial Economics, 71(2), pp. 349-380.
    Li, X., R.N. Sullivan, CFA, and L. Garcia-Feijóo, CFA, CIPM. (2016). The Low-Volatility Anomaly: Market Evidence on Systematic Risk vs. Mispricing. Financial Analysts Journal, 72(1), pp. 36-47.
    Lintner, J. (1965). The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets. The Review of Economics and Statistics, pp. 13-37.
    Merton, R.C. (1980). On Estimating the Expected Return on the Market: An Exploratory Investigation. Journal of Financial Economics, 8(4), pp. 321-361.
    Mossin, J. (1966). Equilibrium in a Capital Asset Market. Econometrica, 34(4), pp. 768-783.
    Nishizaki, K., A. Tsuchikawa and T. Yagi. (2013). Indicators Related to Liquidity in JGB Markets. Bank of Japan Review Series.
    Novy-Marx, R. (2014). Understanding Defensive Equity. NBER Working Paper 20591.
    Pastor, L. and R. Stambaugh. (2003). Liquidity Risk and Expected Stock Returns. Journal of Political Economy, 111(3), pp. 642-685.
    Patton, A., and A. Timmermann. (2010). Monotonicity in Asset Returns: New Tests with Applications to the Term Structure, the CAPM, and Portfolio Sorts. Journal of Financial Economics, 98(3).
    Schneider, P., C. Wagner and J. Zechner. (2015). Low Risk Anomalies? Working Paper.
    Sharpe, W. (1964). Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk. Journal of Finance, 19(3), pp. 425-442.
    Shiller, R. (2001). Irrational Exuberance. New York: Broadway Books.
    Vasicek, O. (1973). A Note on Using Cross-Sectional Information in Bayesian Estimation of Security Betas. Journal of Finance, 28(5), pp. 1233–1239.
    Zhou, C. (2014). Liquidity Based Momentum Strategies on Dutch Stock Market. Erasmus University Rotterdam, Economics.
    Description: 碩士
    國立政治大學
    金融學系
    103352023
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0103352023
    Data Type: thesis
    Appears in Collections:[金融學系] 學位論文

    Files in This Item:

    File SizeFormat
    202301.pdf913KbAdobe PDF2117View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback