沪市A股过度反应和反应不足的实证研究

在对股票超额收益率采用两种不同的计算方法后发现,在投资组合的形成期内表现最好的赢者组合和表现最差的输者组合,绝大多数在持有期内的收益率都不能高于市场平均收益率,而且随着持有期的延长,赢者组合和输者组合负的超额收益率开始变得显著,这说明前者存在过度反应而后者存在反应不足.此外,两个组合之间收益率的差距却始终不显著,无论是在赢者组合表现得比输者组合好的情况下还是输者组合表现得比赢者组合好的情况下,两者的差异在统计上全都不显著.这样,利用两组合收益上差距的动量策略和反转策略无法获得显著的收益,这两种策略在沪市A股中基本是不可行的.     

价值性投资还是博彩性投机？——中国A股市场的MAX异象研究

本文利用1995—2017年中国A股上市公司公开数据实证检验了A股市场中的MAX异象,并从博彩性投机和有限套利视角深入探讨了异象的形成持续机制。结果显示:中国A股市场存在显著的MAX异象,个股当月MAX越小下月收益率就越高,构造多空组合可实现年化15.72%的收益。在投资者博彩性投机心理作用下,短期内MAX有惯性传递特征,投机性特征越强、内在价值越低的股票异象越显著。进一步实证分析发现:套利限制对MAX异象具有正向强化作用,套利限制越强异象越显著,多空策略组合获得的收益越高。本文的研究不仅有助于更好地理解中国股市中MAX异象,也对提升市场有效性、减小异象的影响有实践意义。     

大连商品交易所大豆压榨利润套利的实证研究

本文首次利用大连商品交易所大豆压榨利润,对大商所大豆、豆粕和豆油之间的跨品种套利交易进行了实证研究,研究结果显示,三者之间存在套利机会:利用压榨利润20日移动平均线的交易策略多头套利和空头套利收益显著为正,但利用5日移动平均线的交易策略只有空头套利交易收益显著为正,两种情形下,空头套利交易收益平均大于多头套利交易。     

中国A股市场动量效应与“动量崩盘”现象研究

动量效应作为一种金融异象,广泛存在于各个市场。然而在丰厚收益的背后却存在着巨大的风险,学术界称之为"动量崩盘"。本文在确定中国A股证券市场动量效应的基础上,进一步研究了动量组合的风险性质。结果表明:A股市场存在周度的动量效应;且该周度效应无法被CAPM和Fama-French三因子模型所解释;A股的周度动量效应没有出现普遍存在于其他动量市场的"动量崩盘"现象,表明在A股市场实施动量策略,不仅收益比美国市场更丰厚,而且风险更小;而动量组合在牛熊市中不对称的收益表现,使得动量收益可以和股票期权一样被市场预计波动率所解释。     

高频数据下基于组合预测思想的统计套利策略创新设计与实证研究

采用两只股票的日数据和5种高频数据,借鉴组合预测思想,综合利用协整模型和新卡尔曼滤波模型,与统计套利策略具体目标相结合,设计出新统计套利组合策略,实证分析数据频率、策略选择对统计套利效果的影响。结果表明：运用高频数据及引入卡尔曼滤波模型均有效,但卡尔曼滤波模型与协整模型不存在明显优劣之分,选择组合策略是必要的;组合策略收益性显著优于采取单一模型的套利策略;组合策略下的套利组合随数据频率提高,收益率波动性更小、更稳定;组合策略接近市场中性,能很好地免疫市场风险。     

不同市场状态下动量策略盈利性研究

A股股票数据,以周为单位对2014年10月31日到2015年12月31日的数据分牛、熊市进行实证分析,认为中国股市短期存在明显的动量效应、在一个较短的投资期限中采用动量交易策略将获得较高的超额收益率,但在牛市、熊市中持有收益最高的股票组合当市场态势转换时并不能获得显著的超额收益率。动量投资策略的关键在于短线操作,将持有期控制在一个月以内。     

卖空限制与收益可预测性——A股融资融券制度的证据

基于A股市场融资和融券余额的巨大差距,本文拓展了Hong et al.(2016)的理论模型,在融券端和融资端分别找到了影响股票收益率的变量:融券比率(融券余额/流通市值)和融资回补天数(融资比率/日均换手率)。进一步,本文利用组合价差法和Fama-MacBeth横截面回归法,实证检验了A股市场中融券比率与融资回补天数解释和预测股票收益率的能力。实证结果表明,在存在融券限制条件下,融券比率相比融券回补天数(融券比率/日均换手率)能更好地代表套利者对股票价格高估程度的看法,根据融券比率构建的等权重多空组合能带来月均1.58%的显著收益;而由于融资约束相对较少,融资回补天数相比融资比率(融资余额/流通市值)能更好地代表套利者对股票价格低估程度的看法,根据融资回补天数构建的等权重多空组合能带来月均1.28%的显著收益。实证结果与本文存在融券数量限制下的理论模型相符,且该收益率不能被多因子模型和常规股票特征所解释。     

卖空限制与收益可预测性——A股融资融券制度的证据

基于A股市场融资和融券余额的巨大差距,本文拓展了Hong et al.(2016)的理论模型,在融券端和融资端分别找到了影响股票收益率的变量:融券比率(融券余额/流通市值)和融资回补天数(融资比率/日均换手率)。进一步,本文利用组合价差法和Fama-MacBeth横截面回归法,实证检验了A股市场中融券比率与融资回补天数解释和预测股票收益率的能力。实证结果表明,在存在融券限制条件下,融券比率相比融券回补天数(融券比率/日均换手率)能更好地代表套利者对股票价格高估程度的看法,根据融券比率构建的等权重多空组合能带来月均1.58%的显著收益;而由于融资约束相对较少,融资回补天数相比融资比率(融资余额/流通市值)能更好地代表套利者对股票价格低估程度的看法,根据融资回补天数构建的等权重多空组合能带来月均1.28%的显著收益。实证结果与本文存在融券数量限制下的理论模型相符,且该收益率不能被多因子模型和常规股票特征所解释。     

基于中国股市的动量策略和反转策略盈利性研究

本文测试了中国股票市场中A股的反转策略和动量策略的盈利性,实证结果证明了短期内的动量收益,而反转收益存在于中长期和长期。在对两类收益的原因探析中,本文证明反转收益部分归因于规模效应。Beta因素对两类收益都没有解释力。本文同时还测试了Fama-French三因素模型,发现包含市场风险、规模差异和账面市场价值比在内的三类公共因素均不能有效解释反转收益和动量收益。     

全流通背景下A股IPO抑价研究

中国A股IPO抑价率远远高于国外成熟市场平均水平,也大大高于其他新兴市场的IPO抑价水平。本文以2005年6月至2008年8月中国A股市场发行的259家新股为研究对象,实证分析了"赢者诅咒"假说和"投资者情绪假说"解释A股IPO抑价的适用性。本文研究发现,经典文献中关于IPO抑价的"赢者诅咒"假说基本上不能解释中国A股IPO抑价现象,而二级市场的乐观情绪和新股投机是决定IPO抑价的重要因素。     

Momentum in Residential Real Estate

This paper examines whether there is return momentum in residential real estate in the U.S. Case and Shiller (American economic review 79(1):128–137, 1989) document evidence of positive return correlation in four U.S. cities. Similar to Jegadeesh and Titman’s (Journal of finance 56:699–720, 1993) stock market momentum paper, we construct long-short zero cost investment portfolios from more than 380 metropolitan areas based on their lagged returns. Our results show that momentum of returns in the U.S. residential housing is statistically significant and economically meaningful during our 1983 to 2008 sample period. On average, zero cost investment portfolios that buy past winning housing markets and short sell past losing markets earn up to 8.92% annually. Our results are robust to different sub-periods and more pronounced in the Northeast and West regions. While zero cost portfolios of residential real estate indices is not a tradable strategy, the implications of our results can be useful for builders, potential home owners, mortgage originators and traders of real estate options.     

Momentum strategies based on reward–risk stock selection criteria

In this paper, we analyze momentum strategies that are based on reward–risk stock selection criteria in contrast to ordinary momentum strategies based on a cumulative return criterion. Reward–risk stock selection criteria include the standard Sharpe ratio with variance as a risk measure, and alternative reward–risk ratios with the expected shortfall as a risk measure. We investigate momentum strategies using 517 stocks in the S&P 500 universe in the period 1996–2003. Although the cumulative return criterion provides the highest average monthly momentum profits of 1.3% compared to the monthly profit of 0.86% for the best alternative criterion, the alternative ratios provide better risk-adjusted returns measured on an independent risk-adjusted performance measure. We also provide evidence on unique distributional properties of extreme momentum portfolios analyzed within the framework of general non-normal stable Paretian distributions. Specifically, for every stock selection criterion, loser portfolios have the lowest tail index and tail index of winner portfolios is lower than that of middle deciles. The lower tail index is associated with a lower mean strategy. The lowest tail index is obtained for the cumulative return strategy. Given our data-set, these findings indicate that the cumulative return strategy obtains higher profits with the acceptance of higher tail risk, while strategies based on reward–risk criteria obtain better risk-adjusted performance with the acceptance of the lower tail risk.     

Industry momentum strategies and autocorrelations in stock returns

In this study, we examine the sources of profits to momentum strategies of buying past winner industry portfolios and selling short past loser industry portfolios. We decompose the profit into (1) own-autocovariances in industry portfolio returns, (2) cross-autocovariances among industry portfolio returns, and (3) cross-sectional dispersion in mean portfolio returns. Our empirical results show that the industry momentum effect is mainly driven by the own-autocorrelation in industry portfolio returns, not by return cross-autocorrelations or by cross-sectional differences in mean returns. Indeed, the industry momentum strategy generates statistically significant profits only when own-autocorrelations are positive and statistically significant. The evidence is consistent with several behavioral models (e.g. Journal of Financial Economics 45 (1998) 307; Journal of Finance 53 (1998) 1839; Journal of Finance 54 (1999) 2143) that suggest positive own-autocorrelations in stock returns and hence the price momentum.     

Noise Momentum Around the World

We argue that arbitrageurs will strategically limit their initial investment in an arbitrage opportunity in anticipation of further mispricing caused by the deepening of noise traders' misperceptions. Such ‘noise momentum’ is an important determinant of the overall arbitrage process. We design an empirical strategy to capture noise momentum in a two‐period generalized error correction model. Applying it to a wide range of international spot‐futures market pairs, we document pervasive evidence of noise momentum around the world.     

Momentum in Australian style portfolios: risk or inefficiency?

Momentum strategies have been reported to be successful across a range of different markets and asset classes. Three possible explanations for momentum have been hypothesised: risk, return continuation and excessive co‐movement of stock returns compared with dividends. Lewellen (2002) adds to this literature by providing evidence of strong momentum returns in style portfolios that can be explained by negative cross‐serial correlation, a result which supports the excess co‐movement hypothesis. We report robust evidence of style momentum in the Australian market and use the Jegadeesh and Titman (1995) return decomposition to show that this momentum strategy is predominately explained by positive autocorrelation. Our results support the return continuation hypothesis and confirm Chen and Hong's (2002) assertion that Lewellen's (2002) explanation of style momentum returns does not stand up out‐of‐sample.     

Profitable predictability in the cross section of stock returns

Haugen and Baker (1996) report that a long-short stock selection strategy based on more than 50 measures of accounting information and past return behavior would have generated excess returns of approximately 3% per month. We find that the Haugen and Baker strategies do not provide attractive returns after transaction costs if an investor already has access to strategy portfolios based on book-to-market and momentum. We also provide an extensive analysis of transaction costs over a long sample and we report results of independent interest to researchers in market microstructure.     

Do Industries Explain Momentum?

This paper documents a strong and prevalent momentum effect in industry components of stock returns which accounts for much of the individual stock momentum anomaly. Specifically, momentum investment strategies, which buy past winning stocks and sell past losing stocks, are significantly less profitable once we control for industry momentum. By contrast, industry momentum investment strategies, which buy stocks from past winning industries and sell stocks from past losing industries, appear highly profitable, even after controlling for size, book-to-market equity, individual stock momentum, the cross-sectional dispersion in mean returns, and potential microstructure influences.     

The coskewness puzzle

We propose a novel approach to testing non-linear stochastic discount factor (SDF) specifications that arise in rational representative investor models. Our approach does not require overly-restrictive assumptions about the shape of investors’ preferences, typically imposed by the extant literature, and is based instead on restrictions that rule out “good deals”, i.e., arbitrage opportunities as well as unduly large Sharpe ratios. We apply this framework to test the empirical admissibility of 3 and 4-moment versions of the CAPM. We find that, while coskewness and cokurtosis risk help price a number of stock strategies and portfolios, including static strategies based on a fine industry-level diversification, momentum strategies and portfolios managed on the basis of available information, the CAPM and its 3 and 4-moment versions cannot provide an exhaustive account of observed asset returns.     

明星基金溢价效应:“高技术”还是“好运气”?

本文研究我国股票型、偏股型开放式基金的评级与未来业绩的关系。根据晨星公司的基金评级数据,每月构造1星级至5星级的基金投资组合,并采用Carhart四因子模型对组合收益进行风险调整,研究发现5星级基金每年能获得2%的超额收益率,5星级与1星级基金的套利组合年超额收益为6%。此外,采用自助法对超额收益率的进一步检验,本文发现,明星基金溢价与基金经理的选股能力无关,与基金经理的好运气有关。     

Risk and return in convertible arbitrage: Evidence from the convertible bond market

In this paper, we identify and document the empirical characteristics of the key drivers of convertible arbitrage as a strategy and how they impact the performance of convertible arbitrage hedge funds. We show that the returns of a buy-and-hedge strategy involving taking a long position in convertible bonds (“CBs”) while hedging the equity risk alone explains a substantial amount of these funds' return dynamics. In addition, we highlight the importance of non-price variables such as extreme market-wide events and the supply of CBs on performance. Out-of-sample tests provide corroborative evidence on our model's predictions. At a more micro level, larger funds appear to be less dependent on directional exposure to CBs and more active in shorting stocks to hedge their exposure than smaller funds. They are also more vulnerable to supply shocks in the CB market. These findings are consistent with economies of scale that large funds enjoy in accessing the stock loan market. However, the friction involved in adjusting the stock of risk capital managed by a large fund can negatively impact performance when the supply of CBs declines. Taken together, our findings are consistent with convertible arbitrageurs collectively being rewarded for playing an intermediation role of funding CB issuers whilst distributing part of the equity risk of CBs to the equity market.