The information environment and the ability of logit-based financial statement analysis to predict abnormal returns

Holthausen and Larcker (1992) show that logit-based financial statement analysis can predict abnormal returns on investments in equity securities. We argue that if this success of financial statement analysis is due to market inefficiency, then the procedure should work better for small firms than larger firms, where firm-size proxies for the amount of information processing in the firm's information environment. We do not find greater predictable hedge portfolio returns associated with the analysis of small-firm financial statements. Thus, our results conflict with the market inefficiency explanation. Our results are more consistent with financial statement analysis providing summary information about expected returns not subsumed by other risk proxies and not accounted for in the researcher's definition of abnormal returns.     

Investor attention,aggregate limit-hits,and stock returns

We develop a simple measure of investor attention by aggregating the number of days that a stock hits the upper or lower limit on a monthly basis. This attention proxy describes investor trading behavior and contains information of future stock returns. Using data from the Chinese equity market from 2002 to 2017, we provide extensive evidence that the investor attention captured by our measure negatively predicts cross-sectional stock returns, and the long–short trading strategy based on this attention measure produces significant economic value. We argue that the attention-motivated trading is the main cause behind the return predictability of aggregate limit-hits.     

Can financial statement analysis beat consensus analysts’ recommendations?

We examine whether investors can exploit financial statement information to identify companies with a greater likelihood of future earnings increases and whether stocks of those companies generate 1-year abnormal returns that exceed the abnormal returns from following analysts’ consensus recommendations. Our approach summarizes financial statement information into a “predicted earnings increase score,” which captures the likelihood of 1-year-ahead earnings increases. We find that, within our sample of consensus recommendations, stocks with high scores are much more likely to experience future earnings increases than stocks with low scores. A hedge portfolio strategy that utilizes our approach within each consensus recommendation level generates average annual abnormal returns of 10.9 percent over our 12-year sample period, after controlling for previously identified risk factors. These abnormal returns exceed those available from following analysts’ consensus recommendations. Our results show that share prices and consensus recommendations fail to impound financial statement information that helps predict future earnings changes.     

A Structured Financial Statement Analysis and the Direct Prediction of Stock Prices in Korea

Using a large sample of firms listed on the Korea Stock Exchange, this paper evaluates the usefulness of a structured, programmable financial statement analysis for investment decisions. In doing so, we develop a firm valuation model which links a firm's market value with fundamental variables such as the ability of a firm to generate cash flows, growth potentials, and risk. We predict a firm's intrinsic value directly from an extensive set of financial statement variables which proxy for the theoretical variables implied by the model. We then construct a series of trading strategies with zero net investment (called D-strategies) on the basis of D-values which measure percentage differences between predicted intrinsic values and observed market values. We observe that the market-adjusted and size-adjusted (hedge-portfolio) returns to the most conservative D-strategy turn out to be in the order of 16.92% and 11.44%, respectively,for the 12-month holding period. When our sample is stratified into two sub-samples based on firm size, the D-strategy yields higher excess return for the small-firm sub-sample than for the large-firm sub-sample. The above evidence, taken as a whole, strongly indicates that one can construct a profitable trading strategy by directly predicting intrinsic values through a structured financial statement analysis such as ours.     

Communication and Comovement: Evidence from Online Stock Forums

We study investor communication and stock comovement using a novel data set from an active online stock forum in China. We find substantial comovement among the returns of a stock and its “related stocks,” which are frequently discussed in the subforum dedicated to the given stock. Comovement is greater when the discussion of related stocks is more intensive. Further, the effect of communication on comovement is stronger for stocks associated with higher information uncertainty. Codiscussed stocks are more actively traded and experience more correlated trading. A trading strategy that exploits communication‐driven comovement generates abnormal returns. Our findings highlight the impact of investor communication on asset comovement.     

Developing a Trading Rule from the FTSE-100 Stock Index Futures Contract: Evidence in Support of the EMH

An extensive literature documents the predictability of both short and long horizon returns, over a wide range of sample periods, frequencies and markets. This predictability may represent weak form inefficiency, or it may be caused by a failure to account for a time-variation in risk. We develop statistically reliable ex ante models of the returns on the FTSE-100 stock index futures contract and test a simple trading rule based on the out-of-sample predictions from these models. We interpret the failure of our ex ante model to produce abnormal returns for a risk neutral investor as evidence in favour of the EMH. Our trading rule results clearly suggest that we should be careful in interpreting such ex ante models as evidence of financial market inefficiency.     

An encyclopedia for stock markets? Wikipedia searches and stock returns

We present empirical evidence that collective investor behavior can be inferred from large-scale Wikipedia search data for individual-level stocks. Drawing upon Shannon transfer entropy, a model-free measure that considers any kind of statistical dependence between two time series, we quantify the statistical information flow between daily company-specific Wikipedia searches and stock returns for a sample of 447 stocks from 2008 to 2017. The resulting stock-wise measures on information transmission are then used as a signal within a hypothetical trading strategy. The results evidence the predictive power of Wikipedia searches and are in line with the previously documented notion of buying pressure revealed by online investor attention and the trading patterns of retail investors.     

Long-run returns following open market share repurchases

Past studies find abnormal returns to buying after repurchase program announcements. We analyze the profitability of trading after both program announcements and individual repurchase trade publication using different trading strategies – market and limit orders. The analysis of trades is possible because of a unique Canadian data set. The highest abnormal returns are earned by companies on their own repurchase trades which benefits the non-tendering shareholders. For the public investor, we find no strategies that, in practice, would earn abnormal returns to buying after program announcements. However, there is qualified evidence of abnormal returns to a limit order strategy following publication of individual repurchase trades.     

Abnormal trading volume,news and market efficiency: Evidence from the Jamaica Stock Exchange

This paper investigates market efficiency of the Jamaica Stock Exchange (JSE). Together, weak and semi-strong form efficiency claim that historical and newly released public information do not predict future stock price movement. We test both forms of market efficiency by analyzing stock price behavior during times of abnormal trading volume and around the release dates of earnings information. Abnormal trading volume may be driven by liquidity demand or reflect new or private information flow to the market. Using JSE data over the period 2000 to 2021, we find price dynamics consistent with price pressure as firms experience negative abnormal returns on the day of abnormal trading activity but offsetting positive abnormal stock returns on the following day. Further findings show post earnings announcement drift on the JSE. Taken as a whole, the evidence suggests violations of market efficiency and has implications for capital allocation in this emerging market.     

Valuation Effects of Listing on a More Prominent Segment of the Stock Market: Evidence from France

We examine the behaviour of stock prices during the period around the transfer to the Marchéà Règlement Mensuel . First, we discuss the financial reasons, which can justify abnormal returns around the transfer. Second, an event study based on a sample of 71 firms is set up to test the existence of the exchange listing effect on the French market. Third, we explore three hypotheses in order to explain the impact on stock returns: the informative content of the transfer, the increase in the relative size of the firm's investor base, and the reduction of trading costs (immediacy and adverse selection). Cross–sectional regressions show that the increase in the relative size of the firm's investor base is the only variable, which helps to explain the valuation effect.     

Individuals’ Trading Prior to Earnings Announcements

This paper investigates the relationship between individuals’ net trading and stock price movements before and after annual earnings announcements for the Taiwan Stock Exchange. We conduct an event study on the effects of pre‐event individual trade imbalances on pre‐ and post‐announcement abnormal returns. With a unique and comprehensive dataset, we accurately classify executed orders by aggressiveness of order price. The evidence indicates that while individuals, as a group, are not informed about impending earnings announcements, individuals who place aggressive orders are informed as their net trading coincides with contemporaneous and future stock returns. Aggressive individuals lose their edge during the financial crisis. More importantly, the advantage (disadvantage) for individuals who adopt aggressive (passive) orders weakens when foreign institutions own concentrated equity in firms. We also find that net individual trading contains information about abnormal returns that either past returns or volume does not subsume. Controlling for past returns, trading volume and volatility, or using an alternative measure of net individual trading does not change our conclusions.     

Return predictability following large price changes and information releases

We examine return behavior following large price change events. Unconditional post-event abnormal returns are found to be unimportant. As we condition on other criteria related to the quality of information like volume and public announcements, the abnormal returns become large. The type of news provides further refinement. If the news relates to earnings or analyst recommendations then the 20-day abnormal returns become much larger ranging from 3% to 4% for positive events and about −2.25% for negative events. Finally, an out-of-sample trading strategy confirms investor under-reaction and generates significant abnormal annualized returns of the order of 12–18%.     

Does the Pricing of Financial Reporting Quality Change Around Dividend Changes?

We examine whether accrual earnings quality is a priced information risk factor in a dividend change setting. We define information risk as the probability that firm‐specific financial statement information pertinent to investor pricing decisions is of low precision, and use the factor‐mimicking portfolio returns formed on the Dechow‐Dichev [2002] accrual quality (AQ) metric to proxy for the information risk (IR) factor returns. We augment the Fama‐French three‐factor model with this IR factor, and find that dividend initiation and increase firms exhibit a decrease in the factor loadings on the IR factor while dividend decrease firms exhibit an increase in the corresponding factor loadings, but such changes in the factor loadings occur months prior to the dividend change announcements. The results are robust to further controls for operating risk and using an alternative measure of information risk. Further analysis on changes in information characteristics such as AQ, the probability of informed trading score (PIN), forecast dispersion, and return volatility surrounding dividend change events are consistent with the asset pricing results. Overall, we interpret our results as being consistent with investors treating the information risk associated with the precision of financial statement information as a priced risk factor, with both the precision and pricing changing in predictable directions around dividend changes. However, while we attempt to control for operating risk changes in additional tests, we cannot completely rule out changes in operating risk as a competing alternative explanation for our observed results.     

Individual Investor Trading and Return Patterns around Earnings Announcements

This paper provides evidence of informed trading by individual investors around earnings announcements using a unique data set of NYSE stocks. We show that intense aggregate individual investor buying (selling) predicts large positive (negative) abnormal returns on and after earnings announcement dates. We decompose abnormal returns following the event into information and liquidity provision components, and show that about half of the returns can be attributed to private information. We also find that individuals trade in both return‐contrarian and news‐contrarian manners after earnings announcements. The latter behavior has the potential to slow the adjustment of prices to earnings news.     

线上销售与未来股票收益

本文通过分析相关上市公司在电商平台的线上销售数据,发现线上销售增长可以预测未来股票收益。根据线上销售增长率构建投资组合可以获得月均1.27%的超额收益,经三因子、五因子模型调整后收益率分别为1.40%和1.35%,并且该超额收益在较长时间内不会逆转。横截面回归结果显示,线上销售增长与未来股票收益显著正相关,并在控制其他市场异象因子后仍然显著。此外,本文还发现线上销售数据的预测能力主要集中在投资者关注有限、线上销售占比高以及套利成本高的公司,其投资价值来源于对公司未来基本面信息的预测能力。进一步研究表明,同时利用线上销售指标和营业收入指标进行投资可以获得更高的超额收益。在考虑业绩预告和业绩快报对线上销售指标预测能力的潜在影响后,结果依然稳健。     

Loss persistence and returns in the UK

In this study, we examine whether estimated loss reversal probabilities are fully reflected in UK stock market prices. Overall, we provide evidence of varying degrees and types of loss firm mispricing with respect to estimated loss reversal probabilities. In particular, a significant and positive relationship between loss reversal probability and annual returns is found only for firms with higher trading costs. When looking at monthly returns, however, especially for the financial statement release month subsequent to the loss year, a significant and positive relationship is found for all firms. Thus, the evidence is consistent with UK market participants not fully incorporating relevant information into the pricing of loss firms and, as a consequence, being surprised by the content of the earnings for many or all UK loss firms.     

Institutional trading and information processing: Evidence from complicated firms and easy-to-analyze firms

In this article, I examine institutional trading within two groups of firms with different demands on investor information processing: conglomerate firms and stand-alone firms. On average, institutional trading in conglomerate firm stocks yields significantly lower returns than institutional trading in stand-alone firm stocks. Inferior returns following institutional trading in conglomerate firm stocks persist across small and large firms. Moreover, financial institutions with a low concentration of conglomerate firms in their portfolios are more profitable in their trading. This study provides evidence that skilled institutional investors intentionally focus their information-processing efforts on easy-to-analyze firms.     

重大突发公共卫生事件下的金融市场反应

本文旨在评估金融市场对重大突发公共卫生事件的反应,尤其是上市公司所在地的公共治理能力是否会影响上市公司股票收益率。其中,城市公共治理能力以基于实时数据计算的防疫能力和复工复产能力指标来刻画。主要发现如下:第一,防疫能力会影响投资者情绪,但不会直接影响股票收益率;第二,所在地复工复产能力对股票收益率存在正向影响;第三,机制分析表明,经营基本面更容易受疫情影响的企业,如小企业、成长型企业、所在地数字金融基础设施较差的企业,其股票收益率对当地复工复产能力的反应更敏感。本文结论表明,在全国一盘棋的抗疫努力下,投资者对于战胜疫情有信心,短期内复工复产能力对金融市场更重要。从应对措施来看,短期内可对比较脆弱的企业实施精准果断的帮扶,长期内可考虑加强地区防疫能力建设和数字基础设施建设。     

Economic and financial crises and the predictability of U.S. stock returns

We argue that the use of publicly available and easily accessible information on economic and financial crises to detect structural breaks in the link between stock returns and macroeconomic predictor variables improves the performance of simple trading rules in real time. In particular, our results suggest that accounting for structural breaks and regime shifts in forecasting regressions caused by economic and financial crises has the potential to increase the out-of-sample predictability of stock returns, the performance of simple trading rules, and the market-timing ability of an investor trading in the U.S. stock market.     

Disclosure of GAAP line items in earnings announcements

We provide new evidence on the disclosure in earnings announcements of financial statement line items prepared under Generally Accepted Accounting Principles (GAAP). First, we investigate the circumstances that might provide disincentives generally for GAAP line item disclosures. We find that managers who regularly intervene in the earnings reporting process limit disclosures at the aggregate level and in each of the financial statements so as to more effectively guide investor attention to summary financial information. Specifically, this disclosure behavior obtains when managers habitually cater to market expectations, engage in income smoothing, or use discretionary accruals to improve earnings informativeness. Second, we predict and find that the specific GAAP line items that firms choose to disclose are determined by the differential informational demands of their economic environment, consistent with incentives to facilitate investor valuation. However, these valuation-related disclosure incentives are muted when managers habitually intervene in the earnings reporting process.