This study separates trading volume into buyer- and seller-initiated activities and examines the directional volume reaction in small and large trades to different types of earnings news. ‘Good’ (‘bad’) news triggers brief, but intense, buying (selling) in the large trades. However, a persistent period of unusually high buying activity is observed in the small trades irrespective of the news. This anomalous proclivity of small traders to buy is robust across firm size, trading volume, and different earnings expectation models. Several explanations are discussed, although the behavior does not seem fully explained by existing theories.

This article investigates predictors and benefits of corporate adaptation to crisis, adding a new dimension to studies of flexibility and resilience based on ex ante characteristics. We produce a unique sample of work-from-home announcements scraped from company websites during Covid-19. The announcers’ valuations increased by 3%–5% and risk declined versus matches, consistent with real-options theory under asymmetric information. We estimate characteristics, including subtle textual topics from 10-Ks, that predicted adaptation, show faster price response following Bloomberg coverage, and real advantages in subsequent operating performance. Corporate adaptation to crisis adds value and reduces risk, beyond information in firm characteristics.

This study examines the usefulness of an analyst-based valuation model in predicting cross-sectional stock returns. We estimate firms' fundamental values (V) using I/B/E/S consensus forecasts and a residual income model. We find that V is highly correlated with contemporaneous stock price, and that the V/P ratio is a good predictor of long-term cross-sectional returns. This effect is not explained by a firm's market beta, B/P ratio, or total market capitalization. In addition, we find errors in consensus analyst earnings forecasts are predictable, and that the predictive power of V/P can be improved by incorporating these errors.

We show that analyst coverage proxies contain information about expected returns. We decompose analyst coverage into abnormal and expected components using a simple characteristic-based model and show that firms with abnormally high analyst coverage subsequently outperform firms with abnormally low coverage by approximately 80 basis points per month. We also show abnormal coverage rises following exogenous shocks to underpricing and predicts improvements in firms’ fundamental performance, suggesting that return predictability stems from analysts more heavily covering underpriced stocks. Our findings highlight the usefulness of analysts’ actions in expected return estimations, and a potential inference problem when coverage proxies are used to study information asymmetry and dissemination.

This study presents a general approach for selecting comparable firms in market‐based research and equity valuation. Guided by valuation theory, we develop a “warranted multiple” for each firm, and identify peer firms as those having the closest warranted multiple. We test this approach by examining the efficacy of the selected comparable firms in predicting future (one‐ to three‐year‐ahead) enterprise‐value‐to‐sales and price‐to‐book ratios. Our tests encompass the general universe of stocks as well as a sub‐population of so‐called “new economy” stocks. We conclude that comparable firms selected in this manner offer sharp improvements over comparable firms selected on the basis of other techniques.

From 2007 to 2020, unlisted Chinese firms paid an average of over US $500 million to listed firms for their shell value in reverse merger transactions. We show that this large shadow price for a public listing sheds light on other features of Chinese markets, including (i) near-zero mortality rates, (ii) frequent major-asset restructurings (MARs), (iii) insensitivity of small-firm prices to corporate earnings, and (iv) a large size effect. A firm-level measure of expected shell probability (ESP) predicts stock returns, MARs, earnings-to-price sensitivity, and short-window returns to initial public offering-related regulatory news. Furthermore, adding ESP to existing pricing models for Chinese stocks significantly improves model performance.

ABSTRACT This paper evaluates alternative methods for classifying individual trades as market buy or market sell orders using intraday trade and quote data. We document two potential problems with quote-based methods of trade classification: quotes may be recorded ahead of trades that triggered them, and trades inside the spread are not readily classifiable. These problems are analyzed in the context of the interaction between exchange floor agents. We then propose and test relatively simple procedures for improving trade classifications.

Abstract We introduce a parsimonious framework for choosing among alternative expected-return proxies (ERPs) when estimating treatment effects. By comparing ERPs’ measurement error variances in the cross-section and in the time series, we provide new evidence on the relative performance of firm-level ERPs nominated by recent studies. Generally, “implied-costs-of-capital” metrics perform best in the time series, whereas “characteristic-based” proxies perform best in the cross-section. Factor-based ERPs, even the latest renditions, perform poorly. We revisit four prior studies that use ex ante ERPs and illustrate how this framework can potentially alter either the sign or the magnitude of prior inferences.

ABSTRACT This paper examines the proposition that fluctuations in discounts of closed‐end funds are driven by changes in individual investor sentiment. The theory implies that discounts on various funds move together, that new funds get started when seasoned funds sell at a premium or a small discount, and that discounts are correlated with prices of other securities affected by the same investor sentiment. The evidence supports these predictions. In particular, we find that both closed‐end funds and small stocks tend to be held by individual investors, and that the discounts on closed‐end funds narrow when small stocks do well.

This paper examines the proposition that fluctuations in discounts on closed end funds are driven by changes in individual investor sentiment toward closed end funds and other securities. The theory implies that discounts on various funds must move together, that new funds get started when seasoned funds sell at a premium or a small discount, and that discounts on the funds fluctuate together with prices of securities affected by the same investor sentiment. The evidence supports these predictions. In particular, we find that discounts on closed end funds narrow when small stocks do well, as would be expected if closed end funds were subject to the same sentiment as small stocks, whim tern. also to be held by individual investors. The evidence thus suggests that investor sentiment affects security returns.