中国股市正反馈交易涨强不对称的定价能力
|
摘要
中国市场存在显著的正反馈交易,且追涨程度远超过杀跌程度.这种现象本文称之为正反馈交易的涨强不对称.本文旨在研究这种涨强不对称是否具有定价能力.本文在Fama-French三因子模型的基础上构建了反转因子、正反馈因子和涨强不对称因子,对2010年以前上市的全部A股从1998年1月至2016年10月的数据进行实证检验.本文发现,涨强不对称因子的表现显著区别于正反馈因子和反转因子;尽管单一来看正反馈因子、反转因子和涨强不对称因子都有一定的定价能力,但在多因子模型中正反馈因子和反转因子的定价能力很弱,只有涨强不对称因子有显著的定价效果;且这种定价能力不是因为追涨、杀跌、流动性溢价或投资者情绪造成的.总之,涨强不对称是一个有别于传统因子的新定价因子,且其定价能力可能源于市场补偿非理性投机带来的风险.
The positive feedback trading phenomenon is significant in Chinese market, and,buying-winners effect is much stronger than selling-losers effect. We call it rise-favor asymmetry of positive feedback trading. This paper studies if this rise-favor asymmetry has asset pricing power. This paper constructs reversal factor, positive feedback factor, and rise-favor asymmetry factor based on Fama-French three factor,and uses a sample that spans from Jan 1998 to Oct 2016 and contains daily data of all A shares that become a listed company before 2010 to do empirical tests. The paper finds that, the performance of rise-favor asymmetry factor is quite different from that of positive feedback factor and reversal factor; Although these three factors all have some pricing power individually, the pricing power of positive feedback factor and reversal factor is weak in the multi-factor pricing model, and only rise-favor asymmetry factor can significantly promote the pricing power of multi-factor model; The pricing power of rise-favor asymmetry factor does not result from price-rising chasing behavior, price-dropping chasing behavior, liquidity risk premium, or investor sentiment. In sum, rise-favor asymmetry is a new pricing factor that different from traditional factors, and its pricing power may relate to the market's compensation on the risk of irrational speculation.
The positive feedback trading phenomenon is significant in Chinese market, and,buying-winners effect is much stronger than selling-losers effect. We call it rise-favor asymmetry of positive feedback trading. This paper studies if this rise-favor asymmetry has asset pricing power. This paper constructs reversal factor, positive feedback factor, and rise-favor asymmetry factor based on Fama-French three factor,and uses a sample that spans from Jan 1998 to Oct 2016 and contains daily data of all A shares that become a listed company before 2010 to do empirical tests. The paper finds that, the performance of rise-favor asymmetry factor is quite different from that of positive feedback factor and reversal factor; Although these three factors all have some pricing power individually, the pricing power of positive feedback factor and reversal factor is weak in the multi-factor pricing model, and only rise-favor asymmetry factor can significantly promote the pricing power of multi-factor model; The pricing power of rise-favor asymmetry factor does not result from price-rising chasing behavior, price-dropping chasing behavior, liquidity risk premium, or investor sentiment. In sum, rise-favor asymmetry is a new pricing factor that different from traditional factors, and its pricing power may relate to the market's compensation on the risk of irrational speculation.
引文
[1] DeLong J B, Shleifer A, Summers L H, et al. Positive feedback investment strategies and destabilizing rational speculation[J]. The Journal of Finance, 1990, 45(2):379-395.
[2] Wan D, Liu W, Wang J, et al. Asymmetries of positive feedback trading in individual stocks:Evidences from China[J]. Journal of Management Science and Engineering, 2016, 1(1):3-27.
[3] Sentana E, Wadhwani S. Feedback traders and stock return autocorrelations:Evidence from a century of daily data[J]. The Economic Journal, 1992, 102(411):415-425.
[4] Wan D, Yang X. High-frequency positive feedback trading and market quality:Evidence from China's stock market[J]. International Review of Finance, 2017, 17(4):493-523.
[5] Shefrin H, Statman M. The disposition to sell winners too early and ride losers too long:Theory and evidence[J].The Journal of Finance, 1985, 40(3):777-790.
[6] Odean T. Are investors reluctant to realize their losses?[J]. The Journal of Finance, 1998, 53(5):1775-1798.
[7]池丽旭,庄新田.投资者的非理性行为偏差与止损策略——处置效应,参考价格角度的实证研究[J].管理科学学报,2011,14(10):54-66.Chi L X, Zhuang X T. Investors'behavioural biases and stop-loss strategy:Empirical study based on disposition effect and reference point[J]. Journal of Management Sciences in China, 2011, 14(10):54-66.
[8]任德平,龚旭,文凤华,等.中国股票投资者的处置效应检验和参考价格选择[J].中国管理科学,2013, 21(3):1-10.Ren D P, Gong X, Wen F H, et al. Chinese stock investors'disposition effect testing and reference price choosing[J]. Chinese Journal of Management Science, 2013, 21(3):1-10.
[9] Kahneman D, Tversky A. Prospect theory:An analysis of decision under risk[J]. Econometrica:Journal of the Econometric Society, 1979:263-291.
[10] Fama E F, French K R. Size, value, and momentum in international stock returns[J]. Journal of Financial Economics, 2012, 105(3):457-472.
[11] Fama E F, French K R. A five-factor asset pricing model[J]. Journal of Financial Economics, 2015, 116(1):1-22.
[12] Scheinkman J A, Xiong W. Overconfidence and speculative bubbles[J]. Journal of Political Economy, 2003,111(6):1183-1219.
[13] Shleifer A, Vishny R W. The limits of arbitrage[J]. The Journal of Finance, 1997, 52(1):35-55.
[14] Jegadeesh N, Titman S. Momentum[J]. Annual Review of Financial Economics, 2011, 3(1):493-509.
[15] Jegadeesh N, Titman S. Returns to buying winners and selling losers:Implications for stock market efficiency[J].The Journal of Finance, 1993, 48(1):65-91.
[16] Rouwenhorst K G. International momentum strategies[J]. The Journal of Finance, 1998, 53(1):267-284.
[17] Chan K, Hameed A, Tong W. Profitability of momentum strategies in the international equity markets[J]. Journal of Financial and Quantitative Analysis, 2000, 35(2):153-172.
[18] Carhart M M. On persistence in mutual fund performance[J]. The Journal of Finance, 1997, 52(1):57-82.
[19]潘莉,徐建国.A股个股回报率的惯性与反转[J].金融研究,2011,1(11):149-166.Pan L, Xu J G. Price continuation and reversal in China's A-share market:A comprehensive examination[J].Journal of Financial Research, 2011, 1(11):149-166.
[20]许年行,洪涛,吴世农,等.信息传递模式、投资者心理偏差与股价“同涨同跌”现象[J].经济研究,2011(4):135-146.Xu N H, Hong T, Wu S N, et al. Information flow model, investor psychological bias and stock price comovement[J]. Economic Research Journal, 2011(4):135-146.
[21]何诚颖,陈锐,蓝海平,等.投资者非持续性过度自信与股市反转效应[J].管理世界,2014(8):44-54.He C Y, Chen R, Lan H P, et al. Investor non-durable overconfidence and stock market reversal effect[J].Management World, 2014(8):44-54.
[22]田利辉,王冠英,谭德凯.反转效应与资产定价:历史收益率如何影响现在[J].金融研究,2014(10):177-192.Tian L H, Wang G Y, Tan D K. Reversal effects and asset pricing in China:How do historical returns influence stock performance[J]. Journal of Financial Research, 2014(10):177-192.
[23] Fama E F, French K R. Common risk factors in the returns on stocks and bonds[J]. Journal of Financial Economics, 1993, 33(1):3-56.
[24] Fama E F, French K R. Multifactor explanations of asset pricing anomalies[J]. The Journal of Finance, 1996,51(1):55-84.
[25] Merton R C. An intertemporal capital asset pricing model[J]. Econometrica:Journal of the Econometric Society,1973:867-887.
[26] Ross S A. The arbitrage theory of capital asset pricing[J]. Journal of Economic Theory, 1976, 13(3):341-360.
[27] Cochrane J H. Production-based asset pricing and the link between stock returns and economic fluctuations[J].The Journal of Finance, 1991, 46(1):209-237.
[28] Cochrane J H. A cross-sectional test of an investment-based asset pricing model[J]. Journal of Political Economy,1996, 104(3):572-621.
[29] Liu L X, Whited T M, Zhang L. Investment-based expected stock returns[J]. Journal of Political Economy, 2009,117(6):1105-1139.
[30] Hou K, Xue C, Zhang L. Digesting anomalies:An investment approach[J]. The Review of Financial Studies,2015, 28(3):650-705.
[31] Daniel K, Hirshleifer D, Subrahmanyam A. Investor psychology and security market under-and overreactions[J].The Journal of Finance, 1998, 53(6):1839-1885.
[32] L'Her J F, Masmoudi T,Suret J M. Evidence to support the four-factor pricing model from the Canadian stock market[J]. Journal of International Financial Markets Institutions&Money, 2004, 14(4):313-328.
[33] Campbell J Y, Hentschel L. No news is good news:An asymmetric model of changing volatility in stock returns[J].Journal of Financial Economics, 1992, 31(3):281-318.
[34] Fama E F, French K R. The cross-section of expected stock returns[J]. The Journal of Finance, 1992, 47(2):427-465.
[35] Novy-Marx R. Is momentum really momentum?[J]. Journal of Financial Economics, 2012, 103(3):429-453.
[36]刘京军,徐浩萍.机构投资者:长期投资者还是短期机会主义者?[J].金融研究,2012(9):141-154.Liu J J, Xu H P. Institutional investors:Are they long-term or short-term investor?[J]. Journal of Financial Research, 2012(9):141-154.
[37] Kelley E K, Tetlock P C. How wise are crowds? Insights from retail orders and stock returns[J]. The Journal of Finance, 2013, 68(3):1229-1265.
[38] Fama E F, Macbeth J D. Risk, return, and equilibrium:Empirical tests[J]. Journal of Political Economy, 1973,81(3):607-636.
[39] Newey W K, West K D. A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix[J]. Econometrica, 1987, 55(3):703-708.
[40] Thompson S B. Simple formulas for standard errors that cluster by both firm and time[J]. Journal of Financial Economics, 2011, 99(1):1-10.
[41] Florackis C, Gregoriou A, Kostakis A. Trading frequency and asset pricing on the London Stock Exchange:Evidence from a new price impact ratio[J]. Journal of Banking Finance, 2011, 35(12):3335-3350.
[42] Amihud Y. Illiquidity and stock returns:Cross-section and time-series effects[J]. Journal of Financial Markets,2002, 5(1):31-56.
[43] Pastor L, Stambaugh R F. Liquidity risk and expected stock returns[J]. Journal of Political Economy, 2003,111(3):642-685.
[44] Acharya V V, Pedersen L H. Asset pricing with liquidity risk[J]. Journal of Financial Economics, 2005, 77(2):375-410.
[45]李进芳.带信息的情绪资产定价研究[J].系统工程理论与实践,2016, 36(5):1156-1168.Li J F. Research on the sentiment asset pricing with information[J]. Systems Engineering—Theory&Practice,2016, 36(5):1156-1168.
[46] Baker M, Wurgler J. Investor sentiment and the cross-section of stock returns[J]. The Journal of Finance, 2006,61(4):1645-1680.
[47] Stambaugh R F, Yu J, Yuan Y. The short of it:Investor sentiment and anomalies[J]. Journal of Financial Economics, 2012, 104(2):288-302.
[48]宋泽芳,李元.投资者情绪与股票特征关系[J].系统工程理论与实践,2012, 32(1):27-33.Song Z F, Li Y. Relationship between investor sentiment and stock characteristic[J]. Systems Engineering—Theory&Practice, 2012, 32(1):27-33.
[49]易志高,茅宁.中国股市投资者情绪测量研究:CICSI的构建[J].金融研究,2009(11):174-184.Yi Z G, Mao N. Research on the measurement of investor sentiment in Chinese stock market:The CICSI's construction[J]. Journal of Financial Research, 2009(11):174-184.
[50]鲁臻,邹恒甫.中国股市的惯性与反转效应研究[J].经济研究,2007(9):145-155.Lu Z, Zou H P. Momentum and reversal in China stock market[J]. Economic Research Journal, 2007(9):145-155.
1.处置效应指的是散户倾向于卖出获利的股票,而不愿卖出下跌的股票,从而导致上涨时流动性提供充足,而下跌时交易萎缩~([5,6]).中国市场也有显著的处置效应证据~([7,8]).
2.注意,动量策略与正反馈交易有较大的区别:正反馈交易不需要通过历史收益率排序,也没有策略相关的股票池的概念,只要价格上涨或下跌就会有买入或卖出;动量需要构建赢家多头组合和输家空头组合,只有在股票池中排名靠前和靠后的股票才会在动量交易中买入或卖出.
3.采用之前5天和22天来代表上周和上月是实证中常用的方法,这样就可以滚动地为每一个交易日的交易量配对出上周和上月的收益率.
4.剔除最近一个月的收益率是为了减少持买卖价差的持续影响,是动量效应研究中的标准做法~([15,16,32]).而去掉去年当月是为了剔除季节效应的影响~([10]).
5. Fama和French~([10])的投资组合是每年7月按照去年年报的数据构建,然后持有一年,但国内股市年份太短,且股票数量增加较快,故本文中采取的是每月更新组合,这样的更新频率也与常用的动量或反转策略的频率保持了一致.此外,附录中的稳健性测试也发现,每年7月构建市值和估值组合并持有一年的方法并不影响结论的稳健性.
6.股票的分类都是按照变量去年均值(剔除最近一个月)进行排序的,组合都是每月构建一次并持有一个月.选择上下20%,25%的股票并不影响结果的稳健性(见附录).
7. HML显著为负与Fama和French~([23])并不矛盾,因为他们使用的账面市值比(BM),而这里是市值账面比(MB).在后续的定价模型中,HML的系数大都显著为正,也与Fama和French~([23])中HML系数为负的结果一致.
8.中国市场中反转的存在原因并不是本文的研究目的,我们的结果只证实正反馈会阻碍反转策略赢利,但并不能找出反转的原因.何诚颖等~([21])指出,中国股市的投资者的过度自信难以持续,且面临的信息质量较差,倾向于采用高换手率的交易策略~([36]),从而导致中期反转.
9.如果采用Fama和Macbeth~([38])回归并采用Newey和West~([39])稳健方法,或者采取固定效应模型回归,都没有办法消除不同时点的公司相关性,而本文的公司数量有1669家,远远大于样本期限211,故直接用这两种传统方法的结果稳健性较差.事实上,我们采用这两种方法得到的结果中,所有因子都高度显著,包括一些单变量没有定价能力的因子,比如流动性因子(平均日收益率绝对值除以换手率~([41])).
10.可能的原因是多重共线性,即PFCLMH、NFCLMH与FCLMH相关性太强,我们同时估计了剔除FCLMH后同时加入PFCLMH和NFCLMH结果,此时NFCLMH在95%的置信水平下显著,但PFCLMH在99%置信水平下显著.
11. Florackis等~([41])正是为了剔除ILQ与公司规模间的高度相关性而构建了RtTR,并验证了其在香港市场的优良定价效果,但其在中国A股市场中却不显著.
12.澎湃新闻2017年9月11日报道,作为投资者教育的工作内容之一,证监会正在推动将投资者教育纳入国民教育体系试点.证监会推动上海、广东、四川、青岛、宁夏等20余个省、市、自治区开展试点工作,将投资者教育纳入中小学、高等院校、职业学校等各级各类学校的课程设置中,编制了中小学普及金融知识教材,培训了近万人的师资队伍,各类课程已覆盖数百万人.
[2] Wan D, Liu W, Wang J, et al. Asymmetries of positive feedback trading in individual stocks:Evidences from China[J]. Journal of Management Science and Engineering, 2016, 1(1):3-27.
[3] Sentana E, Wadhwani S. Feedback traders and stock return autocorrelations:Evidence from a century of daily data[J]. The Economic Journal, 1992, 102(411):415-425.
[4] Wan D, Yang X. High-frequency positive feedback trading and market quality:Evidence from China's stock market[J]. International Review of Finance, 2017, 17(4):493-523.
[5] Shefrin H, Statman M. The disposition to sell winners too early and ride losers too long:Theory and evidence[J].The Journal of Finance, 1985, 40(3):777-790.
[6] Odean T. Are investors reluctant to realize their losses?[J]. The Journal of Finance, 1998, 53(5):1775-1798.
[7]池丽旭,庄新田.投资者的非理性行为偏差与止损策略——处置效应,参考价格角度的实证研究[J].管理科学学报,2011,14(10):54-66.Chi L X, Zhuang X T. Investors'behavioural biases and stop-loss strategy:Empirical study based on disposition effect and reference point[J]. Journal of Management Sciences in China, 2011, 14(10):54-66.
[8]任德平,龚旭,文凤华,等.中国股票投资者的处置效应检验和参考价格选择[J].中国管理科学,2013, 21(3):1-10.Ren D P, Gong X, Wen F H, et al. Chinese stock investors'disposition effect testing and reference price choosing[J]. Chinese Journal of Management Science, 2013, 21(3):1-10.
[9] Kahneman D, Tversky A. Prospect theory:An analysis of decision under risk[J]. Econometrica:Journal of the Econometric Society, 1979:263-291.
[10] Fama E F, French K R. Size, value, and momentum in international stock returns[J]. Journal of Financial Economics, 2012, 105(3):457-472.
[11] Fama E F, French K R. A five-factor asset pricing model[J]. Journal of Financial Economics, 2015, 116(1):1-22.
[12] Scheinkman J A, Xiong W. Overconfidence and speculative bubbles[J]. Journal of Political Economy, 2003,111(6):1183-1219.
[13] Shleifer A, Vishny R W. The limits of arbitrage[J]. The Journal of Finance, 1997, 52(1):35-55.
[14] Jegadeesh N, Titman S. Momentum[J]. Annual Review of Financial Economics, 2011, 3(1):493-509.
[15] Jegadeesh N, Titman S. Returns to buying winners and selling losers:Implications for stock market efficiency[J].The Journal of Finance, 1993, 48(1):65-91.
[16] Rouwenhorst K G. International momentum strategies[J]. The Journal of Finance, 1998, 53(1):267-284.
[17] Chan K, Hameed A, Tong W. Profitability of momentum strategies in the international equity markets[J]. Journal of Financial and Quantitative Analysis, 2000, 35(2):153-172.
[18] Carhart M M. On persistence in mutual fund performance[J]. The Journal of Finance, 1997, 52(1):57-82.
[19]潘莉,徐建国.A股个股回报率的惯性与反转[J].金融研究,2011,1(11):149-166.Pan L, Xu J G. Price continuation and reversal in China's A-share market:A comprehensive examination[J].Journal of Financial Research, 2011, 1(11):149-166.
[20]许年行,洪涛,吴世农,等.信息传递模式、投资者心理偏差与股价“同涨同跌”现象[J].经济研究,2011(4):135-146.Xu N H, Hong T, Wu S N, et al. Information flow model, investor psychological bias and stock price comovement[J]. Economic Research Journal, 2011(4):135-146.
[21]何诚颖,陈锐,蓝海平,等.投资者非持续性过度自信与股市反转效应[J].管理世界,2014(8):44-54.He C Y, Chen R, Lan H P, et al. Investor non-durable overconfidence and stock market reversal effect[J].Management World, 2014(8):44-54.
[22]田利辉,王冠英,谭德凯.反转效应与资产定价:历史收益率如何影响现在[J].金融研究,2014(10):177-192.Tian L H, Wang G Y, Tan D K. Reversal effects and asset pricing in China:How do historical returns influence stock performance[J]. Journal of Financial Research, 2014(10):177-192.
[23] Fama E F, French K R. Common risk factors in the returns on stocks and bonds[J]. Journal of Financial Economics, 1993, 33(1):3-56.
[24] Fama E F, French K R. Multifactor explanations of asset pricing anomalies[J]. The Journal of Finance, 1996,51(1):55-84.
[25] Merton R C. An intertemporal capital asset pricing model[J]. Econometrica:Journal of the Econometric Society,1973:867-887.
[26] Ross S A. The arbitrage theory of capital asset pricing[J]. Journal of Economic Theory, 1976, 13(3):341-360.
[27] Cochrane J H. Production-based asset pricing and the link between stock returns and economic fluctuations[J].The Journal of Finance, 1991, 46(1):209-237.
[28] Cochrane J H. A cross-sectional test of an investment-based asset pricing model[J]. Journal of Political Economy,1996, 104(3):572-621.
[29] Liu L X, Whited T M, Zhang L. Investment-based expected stock returns[J]. Journal of Political Economy, 2009,117(6):1105-1139.
[30] Hou K, Xue C, Zhang L. Digesting anomalies:An investment approach[J]. The Review of Financial Studies,2015, 28(3):650-705.
[31] Daniel K, Hirshleifer D, Subrahmanyam A. Investor psychology and security market under-and overreactions[J].The Journal of Finance, 1998, 53(6):1839-1885.
[32] L'Her J F, Masmoudi T,Suret J M. Evidence to support the four-factor pricing model from the Canadian stock market[J]. Journal of International Financial Markets Institutions&Money, 2004, 14(4):313-328.
[33] Campbell J Y, Hentschel L. No news is good news:An asymmetric model of changing volatility in stock returns[J].Journal of Financial Economics, 1992, 31(3):281-318.
[34] Fama E F, French K R. The cross-section of expected stock returns[J]. The Journal of Finance, 1992, 47(2):427-465.
[35] Novy-Marx R. Is momentum really momentum?[J]. Journal of Financial Economics, 2012, 103(3):429-453.
[36]刘京军,徐浩萍.机构投资者:长期投资者还是短期机会主义者?[J].金融研究,2012(9):141-154.Liu J J, Xu H P. Institutional investors:Are they long-term or short-term investor?[J]. Journal of Financial Research, 2012(9):141-154.
[37] Kelley E K, Tetlock P C. How wise are crowds? Insights from retail orders and stock returns[J]. The Journal of Finance, 2013, 68(3):1229-1265.
[38] Fama E F, Macbeth J D. Risk, return, and equilibrium:Empirical tests[J]. Journal of Political Economy, 1973,81(3):607-636.
[39] Newey W K, West K D. A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix[J]. Econometrica, 1987, 55(3):703-708.
[40] Thompson S B. Simple formulas for standard errors that cluster by both firm and time[J]. Journal of Financial Economics, 2011, 99(1):1-10.
[41] Florackis C, Gregoriou A, Kostakis A. Trading frequency and asset pricing on the London Stock Exchange:Evidence from a new price impact ratio[J]. Journal of Banking Finance, 2011, 35(12):3335-3350.
[42] Amihud Y. Illiquidity and stock returns:Cross-section and time-series effects[J]. Journal of Financial Markets,2002, 5(1):31-56.
[43] Pastor L, Stambaugh R F. Liquidity risk and expected stock returns[J]. Journal of Political Economy, 2003,111(3):642-685.
[44] Acharya V V, Pedersen L H. Asset pricing with liquidity risk[J]. Journal of Financial Economics, 2005, 77(2):375-410.
[45]李进芳.带信息的情绪资产定价研究[J].系统工程理论与实践,2016, 36(5):1156-1168.Li J F. Research on the sentiment asset pricing with information[J]. Systems Engineering—Theory&Practice,2016, 36(5):1156-1168.
[46] Baker M, Wurgler J. Investor sentiment and the cross-section of stock returns[J]. The Journal of Finance, 2006,61(4):1645-1680.
[47] Stambaugh R F, Yu J, Yuan Y. The short of it:Investor sentiment and anomalies[J]. Journal of Financial Economics, 2012, 104(2):288-302.
[48]宋泽芳,李元.投资者情绪与股票特征关系[J].系统工程理论与实践,2012, 32(1):27-33.Song Z F, Li Y. Relationship between investor sentiment and stock characteristic[J]. Systems Engineering—Theory&Practice, 2012, 32(1):27-33.
[49]易志高,茅宁.中国股市投资者情绪测量研究:CICSI的构建[J].金融研究,2009(11):174-184.Yi Z G, Mao N. Research on the measurement of investor sentiment in Chinese stock market:The CICSI's construction[J]. Journal of Financial Research, 2009(11):174-184.
[50]鲁臻,邹恒甫.中国股市的惯性与反转效应研究[J].经济研究,2007(9):145-155.Lu Z, Zou H P. Momentum and reversal in China stock market[J]. Economic Research Journal, 2007(9):145-155.
1.处置效应指的是散户倾向于卖出获利的股票,而不愿卖出下跌的股票,从而导致上涨时流动性提供充足,而下跌时交易萎缩~([5,6]).中国市场也有显著的处置效应证据~([7,8]).
2.注意,动量策略与正反馈交易有较大的区别:正反馈交易不需要通过历史收益率排序,也没有策略相关的股票池的概念,只要价格上涨或下跌就会有买入或卖出;动量需要构建赢家多头组合和输家空头组合,只有在股票池中排名靠前和靠后的股票才会在动量交易中买入或卖出.
3.采用之前5天和22天来代表上周和上月是实证中常用的方法,这样就可以滚动地为每一个交易日的交易量配对出上周和上月的收益率.
4.剔除最近一个月的收益率是为了减少持买卖价差的持续影响,是动量效应研究中的标准做法~([15,16,32]).而去掉去年当月是为了剔除季节效应的影响~([10]).
5. Fama和French~([10])的投资组合是每年7月按照去年年报的数据构建,然后持有一年,但国内股市年份太短,且股票数量增加较快,故本文中采取的是每月更新组合,这样的更新频率也与常用的动量或反转策略的频率保持了一致.此外,附录中的稳健性测试也发现,每年7月构建市值和估值组合并持有一年的方法并不影响结论的稳健性.
6.股票的分类都是按照变量去年均值(剔除最近一个月)进行排序的,组合都是每月构建一次并持有一个月.选择上下20%,25%的股票并不影响结果的稳健性(见附录).
7. HML显著为负与Fama和French~([23])并不矛盾,因为他们使用的账面市值比(BM),而这里是市值账面比(MB).在后续的定价模型中,HML的系数大都显著为正,也与Fama和French~([23])中HML系数为负的结果一致.
8.中国市场中反转的存在原因并不是本文的研究目的,我们的结果只证实正反馈会阻碍反转策略赢利,但并不能找出反转的原因.何诚颖等~([21])指出,中国股市的投资者的过度自信难以持续,且面临的信息质量较差,倾向于采用高换手率的交易策略~([36]),从而导致中期反转.
9.如果采用Fama和Macbeth~([38])回归并采用Newey和West~([39])稳健方法,或者采取固定效应模型回归,都没有办法消除不同时点的公司相关性,而本文的公司数量有1669家,远远大于样本期限211,故直接用这两种传统方法的结果稳健性较差.事实上,我们采用这两种方法得到的结果中,所有因子都高度显著,包括一些单变量没有定价能力的因子,比如流动性因子(平均日收益率绝对值除以换手率~([41])).
10.可能的原因是多重共线性,即PFCLMH、NFCLMH与FCLMH相关性太强,我们同时估计了剔除FCLMH后同时加入PFCLMH和NFCLMH结果,此时NFCLMH在95%的置信水平下显著,但PFCLMH在99%置信水平下显著.
11. Florackis等~([41])正是为了剔除ILQ与公司规模间的高度相关性而构建了RtTR,并验证了其在香港市场的优良定价效果,但其在中国A股市场中却不显著.
12.澎湃新闻2017年9月11日报道,作为投资者教育的工作内容之一,证监会正在推动将投资者教育纳入国民教育体系试点.证监会推动上海、广东、四川、青岛、宁夏等20余个省、市、自治区开展试点工作,将投资者教育纳入中小学、高等院校、职业学校等各级各类学校的课程设置中,编制了中小学普及金融知识教材,培训了近万人的师资队伍,各类课程已覆盖数百万人.