深度学习能否让失效因子“起死回生”？——基于Transformer模型的中国A股市场月频动量效应挖掘研究

本文使用基于Transformer模型的深度学习算法成功发现了中国A股市场的月频动量效应，并通过分析模型的信息挖掘机制解释了过去A股市场的“月频动量效应消失之谜”。具体而言本文证实Transformer模型能够利用高维嵌入算法与注意力机制成功甄别以彩票型股票偏好和非理性交易行为为代表的市场噪音，在去除相应的干扰因素后中国A股市场存在显著的月频动量效应，多空组合能够获得0.29%的平均月度收益。进一步地本文从行为金融的视角对A股市场动量效应的形成机制进行了相应分析，证实投资者对市场信息的反应不足是动量效应存在的重要原因。本文研究证实深度学习算法可以利用算力优势挖掘增量信息并增强传统因子的定价能力，对提升资本市场定价效率和投资实践具有一定的启示意义。     

投资者结构是中国股票市场定价因子吗？

机构投资者持股比例可能会影响股票的预期收益，本文尝试探究投资者结构是否是中国股票市场定价因子。本文利用A股数据构建投资者结构因子，并将该因子加入Carhart四因子模型中进行实证回归。研究发现：(1)投资者结构是沪深股票市场定价因子，该结论通过了稳健性检验；(2)相对于沪深主板市场，创业板与科创板市场的投资者结构因子溢价更高；(3)新冠疫情提高了沪深股票市场的投资者结构因子溢价。本文补充了A股市场在资产定价方面的研究，为A股市场投资端改革提供了经验证据。     

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。     

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。     

对小公司效应、价值股效应、动量效应以及反转效应的实证研究——基于三因子模型

本文分析了行为金融学中小公司效应、价值股效应、动量效应以及反转效应对于中国股票市场的影响,以A股市场2000-2018年数据为研究样本,基于Fama-French三因子模型,探究结合行为金融因素的多因子模型能否较好地拟合股市。研究发现,A股市场不同板块对于各个因子的偏好与权重不同,而单一股票也很难通过多因子去很好地解释超额收益,而本文希望通过实证分析来展示非理性因素对于金融市场的影响。     

市场流动性风险能解释价值溢价吗?

文章以1997年1月～2017年12月的沪深A股为研究对象,从流动性风险角度检验价值溢价的风险来源,对价值股和成长股的流动性风险与收益进行对比研究,分析中国股票市场中流动性因子对价值因子的解释能力。研究发现:价值股的市场流动性风险大于成长股,价值溢价的成因是价值股承担了更高的市场流动性风险,从风险补偿角度解释了价值溢价;同时发现在中国股票市场中投资因子与盈利因子并不能解释价值因子,而流动性因子可以解释。     

基于贝叶斯CAPM模型的上海股票市场有效性研究

本文采用贝叶斯的方法估计模型参数和检验模型,构建贝叶斯CAPM模型,以上海股票市场为研究对象,分六个行业选取了A股中120支股票进行研究,以一年期定期存款利率为无风险利率,新上证综指作为市场组合收益率,使用时间序列检验模型和股市风险与收益的线性回归模型,实证检验上海股票市场有效性问题。研究结果发现：市场收益对各行业股票收益具有显著影响,其结果符合资本资产定价模型;而收益与风险关系检验中发现系统风险并不是股票组合预期收益率的唯一度量,企业内部因素在股票定价中起着一定的作用,这不符合资本资产定价模型。总的来说,目前资本资产定价模型仍不完全适用于我国上海股票市场。     

分析师修正信息、基本面分析与未来股票收益北大核心CSSCISSCI

本文基于日历时间组合方法检验中国A股市场分析师修正信息的投资价值。研究发现,分析师发布的盈余预测修正和投资评级修正最具信息含量,投资者既未充分意识到两类修正的信息含量,也未充分意识到明星分析师和普通分析师能力的差别。根据分析师盈余预测修正和投资评级修正构建套利组合,能分别获得月均1.34%和0.92%的经三因子模型调整的超额收益。本文进一步指出,分析师修正信息的投资价值来源于其基本面分析的能力。分析师盈余预测修正和投资评级修正能够显著预测公司未来的盈利能力、标准化未预期盈余和盈余公告窗口期超额收益,并且套利组合的超额收益集中在盈余公告窗口期。本文的结论对于理解分析师在资本市场中发挥的作用、提高市场有效性具有重要意义。     

大宗交易对股价波动的羊群效应研究

以2018-2020年沪深A股发生大宗交易的上市公司为样本,实证检验了上市公司大宗交易定价对其二级市场股票价格波动的影响机理。结果表明：投资者羊群效应与股票超额收益显著正相关;大宗交易折溢价率与股票短期超额收益显著正相关;股票市场的伪羊群效应会减弱大宗交易对股票价格的短期影响。获取大宗交易定价信息的投资者理性与否决定了大宗交易定价对二级市场股票价格作用的强弱。进一步研究发现：沪深A股市场短期内伪羊群效应显著,长期内真羊群效应显著;这充分表明中国股票市场的资产定价相对合理,投资者处于有限理性状态。     

基于货币供应周期的股市周期拐点判别与资产配置研究

本文拟以中国A股市场为研究对象,尝试找出中国货币周期转换与股市周期之间的关联,考察货币周期不同阶段中股票市场的表现与行业轮动规律,并在此基础上给出适宜的资产配置策略。     

Does volume help in predicting stock returns? An analysis of the Australian market

This paper presents an analysis of the relationship between trading volume and stock returns in the Australian market. We test this hypothesis by using data from a sample of firms listed on the Australian stock market for a period of 5 years from January 2001 to December 2005. We explore this relationship by focusing on the level of trading volume and thin trading in the market. Our results suggest that trading volume does seem to have some predictive power for high volume firms and in certain industries of the Australian market. However, for smaller firms, trading volume does not seem to have the same predictive power to explain stock returns in Australia.     

The relative informational efficiency of corporate retail bonds: Evidence from the London Stock Exchange

I examine the relative informational efficiency of the London Stock Exchange's newly launched Order book for Retail Bonds (ORB). I find that the daily returns for the stocks of the issuing firms lead the daily returns of the retail bonds born in the ORB. This finding also holds for pre-existing bonds that were transferred to the ORB from the LSE's Main Market and for the bonds with different credit ratings, issue sizes, and maturity times. I also find that bonds have very limited predictive ability for stock returns. Overall, the results provide strong evidence that the underlying stock market is relatively more efficient than the ORB. Further, the relative informational inefficiency of the ORB implies profitable trading opportunities for private investors.     

Credit market shocks and economic fluctuations: Evidence from corporate bond and stock markets

To identify disruptions in credit markets, research on the role of asset prices in economic fluctuations has focused on the information content of various corporate credit spreads. We re-examine this evidence using a broad array of credit spreads constructed directly from the secondary bond prices on outstanding senior unsecured debt issued by a large panel of nonfinancial firms. An advantage of our “ground-up” approach is that we are able to construct matched portfolios of equity returns, which allows us to examine the information content of bond spreads that is orthogonal to the information contained in stock prices of the same set of firms, as well as in macroeconomic variables measuring economic activity, inflation, interest rates, and other financial indicators. Our portfolio-based bond spreads contain substantial predictive power for economic activity and outperform—especially at longer horizons—standard default-risk indicators. Much of the predictive power of bond spreads for economic activity is embedded in securities issued by intermediate-risk rather than high-risk firms. According to impulse responses from a structural factor-augmented vector autoregression, unexpected increases in bond spreads cause large and persistent contractions in economic activity. Indeed, shocks emanating from the corporate bond market account for more than 30 percent of the forecast error variance in economic activity at the two- to four-year horizon. Overall, our results imply that credit market shocks have contributed significantly to US economic fluctuations during the 1990-2008 period.     

Predicting firm stock returns with customer stock returns: Moderating effects of customer characteristics

Based on the multiple regression model, this study examines the potential predictive effect of customer stock returns to firm stock returns and the moderating effect of diverse customer characteristics on the predictability. By using a sample of Chinese A-share manufacturing firms listed on the Shanghai stock exchange and Shenzhen stock exchange between 2009 and 2017, we find that customer stock returns positively predict firm stock returns in the subsequent month. Additional examinations reveal that the positive predictive effect of customer stock returns on firm stock returns is more intense for firm with high proportion of state-owned customers, customer stability, customer bargaining power and customer concentration than for those with low indicators. Overall, this study contributes to the growing literature on supply chain and predictability of stock returns by shedding light on the forecasting effect of customer stock returns on firm stock returns and the predictive heterogeneity owing to customer characteristics.     

Predicting firm level stock returns: Implications for asset pricing and economic links

We examine the predictive ability of stock price ratios, stock return dispersion and distribution measures for firm level returns. Analysis typically focusses on market level returns, however, for the underlying asset pricing model to hold, firm-level predictability should be present. Additionally, we examine the economic content of predictability by considering whether the predictive coefficient has the theoretically correct sign and whether it is related to future output growth. While stock returns reflect investor expectations regarding future economic conditions, they are often too noisy to act as predictor. We use the time-varying predictive coefficient as it reflects investor confidence in the predictive relation. Results suggest that a subset of stock price ratios have predictive power for individual firm stock returns, exhibit the correct coefficient sign and has predictive power for output growth. Each of these ratios has a measure of fundamentals divided by the stock price and has a positive relation with stock returns and output growth. This implies that as investors expect future economic conditions to improve and earnings and dividends to rise, so expected stock returns will increase. This supports the cash flow channel as the avenue through which stock return predictability arises.     

In name only: Information spillovers among Chinese firms with similar stock names during earnings announcements

We examine whether investors' attention on salient firm characteristics affects information spillovers during corporate earnings announcements. For market participants in China, the stock name is a salient feature of listed companies. We find that the market reaction of non-announcing firms to earnings reports of announcing firms is greater across firms with similar stock names. The incremental information spillovers among similarly named stocks are stronger for larger announcing firms and on days with fewer earnings announcements. The incremental information spillovers between similarly named stocks do not fully reverse in the post-announcement period, consistent with persistent investor behavior predicted by the salience theory. There are also significant return comovements among similarly named stocks. Our findings suggest that investors with limited attention are likely to focus on salient stock names and overestimate the economic connections between similarly name stocks. Our study extends the behavioral finance literature by showing how investors' attention on salient firm features can bias their reaction to unrelated peer disclosures.     

The Other January Effect: international evidence

This paper investigates the predictive power of stock market returns in January for the subsequent 11 months’ returns across 19 countries, thereby contributing to the literature on stock market seasonalities. Only 2 out of 19 countries’ stock markets exhibit a robust Other January Effect. In the light of this evidence, we conclude that the Other January Effect is not an international phenomenon.     

预防性监管与公司产能过剩--基于年报问询函的研究证据北大核心

本文研究年报问询函这一预防性监管制度能否推动公司去产能,并探究其作用机制和经济后果。研究发现,相比未被问询的公司,被问询的公司收函后产能过剩水平显著下降;该结果在媒体负面报道较多的公司、地方政府治理水平较高的地区中更为明显,表明年报问询函通过降低市场、政府与公司间的信息不对称,强化市场和政府的治理效应,进而有效促使公司去产能。影响机制检验表明,年报问询函主要通过优化资源配置、减少代理问题作用于去产能。经济后果方面,年报问询函会提升被问询公司的生产效率和经营业绩。     

How Wise Are Crowds? Insights from Retail Orders and Stock Returns

We analyze the role of retail investors in stock pricing using a database uniquely suited for this purpose. The data allow us to address selection bias concerns and to separately examine aggressive (market) and passive (limit) orders. Both aggressive and passive net buying positively predict firms’ monthly stock returns with no evidence of return reversal. Only aggressive orders correctly predict firm news, including earnings surprises, suggesting they convey novel cash flow information. Only passive net buying follows negative returns, consistent with traders providing liquidity and benefiting from the reversal of transitory price movements. These actions contribute to market efficiency.     

Economic policy uncertainty,investor attention and post-earnings announcement drift

How the market incorporates information into stock price is a core issue in finance. This study focuses on the impact of economic policy uncertainty (EPU) on the stock prices information efficiency of China's A-share market and underlying role of investors' attention allocation mechanism. This study analyzes the information efficiency of stock prices using the sensitivity of stock cumulative abnormal return to earnings information across different windows following earnings announcement. Based on the earnings announcement events of listed companies in China's A-share market, this study presents an empirical study of the aforementioned issues using event study and regression analysis methods. The following results are seen: (1) EPU aggravates the underreaction of stock price earnings information and the post-earnings announcement drift in the A-share market. (2) Under highly uncertain economic policies, investors show a limited attention allocation pattern of devoting increasing attention to macroeconomic policies and decreasing attention to earnings information, which leads to a decrease in the information efficiency of stock price. This study also analyzes the heterogeneity of the influence of EPU on stock price information efficiency using the institutional shareholding ratio. The results show that increasing institutional shareholding does not reduce the adverse effects of EPU on the information efficiency of stock prices. This study not only provides empirical evidence for Brunnermeier, Sockin, and Xiong (2022) and rational inattention theory, but also reveals that institutional investors show similar behavioral characteristics to retail investors in China's stock market. The results of this study have policy significance for improving the information efficiency of stock market.