| 2,876 | 95 | 321 |
| 下载次数 | 被引频次 | 阅读次数 |
本文在我国股票市场检验了有限关注对特质波动率定价的影响。研究发现,特质波动率-收益负相关关系在高关注度股票组合中更显著,而在低关注度组中,特质波动率-收益关系变弱甚至不再显著;Fama和MacBeth(1973)回归结果显示,关注度显著降低了特质波动率的定价作用;另外,通过Hou和Loh(2016)拆分方法发现,有限关注对特质波动率之谜具有最强的解释力度。进一步研究发现,传统的解释不能消除关注度在特质波动率定价中的作用。因而,本文的研究揭示,投资者的有限关注可能是造成一些市场异象的主要原因。
Abstract：This paper tests how the limited attention affects the pricing of idiosyncratic volatility in the Chinese share market. It is found that the negative correlation between idiosyncratic volatility and returns is significant in stock portfolio with high attention, while in stock with low attention, the correlation is weakening and even insignificant. In Fama and MacBeth(1973) regression, it shows the attention sharply reduces the pricing role of idiosyncratic volatility. By the Hou and Loh(2016) decomposition method, it is found that the limited attention is best explained for the idiosyncratic volatility riddle. A further study unravel that the traditional explanation cannot remove the role of limited attention in the pricing of idiosyncratic volatility. Hence, this paper reveals that the limited attention by investors may be the main reason causing the share market anomalies.
[1]R C Merton.A Simple Model of Capital Market Equilibrium with Incomplete Information[J].Journal of Finance,1987(3):483-510.
[2]A Ang,R J Hodrick,Y H Xing,et al.The Cross-Section of Volatility and Expected Returns[J].The Journal of Finance,2006(1):259-299.
[3]A Ang,R J Hodrick,Y H Xing,et al.High Idiosyncratic Volatility and Low Returns:International and Further U.S.Evidence[J].Journal of Financial Economics,2009(1):1-23.
[4]杨华蔚,韩立岩.中国股票市场特质波动率与横截面收益研究[J].北京航空航天大学学报(社会科学版),2009(1):6-10.
[5]左浩苗,郑鸣,张翼.股票特质波动率与横截面收益:对中国股市“特质波动率之谜”的解释[J].世界经济,2011(5):117-135.
[6]B M Barber,T Odean.All That Glitters:The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors[J].The Review of Financial Studies,2008(2):785-818.
[7]冯旭南.注意力影响投资者的股票交易行为吗?——来自“股票交易龙虎榜”的证据[J].经济学(季刊),2017(1):255-274.
[8]E F Fama,J D MacBeth.Risk,Return and Equilibrium:Empirical Tests[J].Journal of Political Economy,1973(3):607-636.
[9]K Hou,R K Loh.Have We Solved the Idiosyncratic Volatility Puzzle?[J].Journal of Financial Economics,2016(2):167-194.
[10]L Fang,J Peress.Media Coverage and the Cross-section of Stock Returns[J].The Journal of Finance,2009(5):2023-2052.
[11]Z Da,J Engelberg,P J Gao.In Search of Attention[J].The Journal of Finance,2011(5):1461-1499.
[12]俞庆进,张兵.投资者有限关注与股票收益——以百度指数作为关注度的一项实证研究[J].金融研究,2012(8):152-165.
[13]黄波,李湛,顾孟迪.基于风险偏好资产定价模型的公司特质风险研究[J].管理世界,2006(11):119-127.
[14]郑振龙,王磊,王路跖.特质偏度是否被定价?[J].管理科学学报,2013(5):1-12.
[15]林金官,郝红霞,汪红霞.基于拟似然方法的股票收益与波动率关系及其应用研究[J].统计研究,2018(5):99-109.
[16]尹玉刚,谭滨,陈威.套利非对称性、误定价与股票特质波动[J].经济学(季刊),2018(3):1235-1258.
[17]A Kumar,S Ruenzi,M Ungeheuer.Daily Winners and Losers[R].Working Paper,Aalto University,2017.
[18]M S Seasholes,G J Wu.Predictable Behavior,Profits,and Attention[J].Journal of Empirical Finance,2007(5):590-610.
[19]J Francis,L Soffer.The Relative Informativeness of Analysts Stock Recommendations and Earnings Forecasts Revisions[J].Journal of Accounting Research,1997(2):193-212.
[20]W Huang,Q Liu,G S Rhee,et al.Return Reversals,Idiosyncratic Risk and Expected Returns[J].The Review of Financial Studies,2010(1):147-168.
[21]T G Bali,N Cakici,R F Whitelaw.Maxing Out:Stocks as Lotteries and the Cross-section of Expected Returns[J].Journal of Financial Economics,2011(2):427-446.
[22]Y F Han,D Lesmond.Liquidity Biases and the Pricing of Cross-sectional Idiosyncratic Volatility[J].The Review of Financial Studies,2011(5):1590-1629.
[23]M Gu,W J Kang,B Xu.Limits of Arbitrage and Idiosyncratic Volatility:Evidence from China Stock Market[J].Journal of Banking Finance,2018(2):240-258.
[24]Y Amihud.Illiquidity and Stock Returns:Cross-section and Time-series Effects[J].Journal of Financial Markets,2002(1):31-56.
(1)由于篇幅有限,附表1见《统计研究》网站所列附件,下同。
(2)表6中关注度使用的是极端日度收益关注度指标,其他两个指标的结果见附表2。
基本信息:
DOI：10.19343/j.cnki.11-1302/c.2019.06.005
中图分类号:F832.51
引用信息:
[1]陆蓉,杨康.有限关注与特质波动率之谜:来自行为金融学新证据[J].统计研究,2019,36(06):54-67.DOI:10.19343/j.cnki.11-1302/c.2019.06.005.
基金信息:
国家自然科学基金“交易传染与非理性价格形成:基于投资者画像的精准识别”(71773072)的资助
2019-06-25
2019-06-25