ABSTRACT Defining and measuring readability in the context of financial disclosures becomes important with the increasing use of textual analysis and the Securities and Exchange Commission's plain English initiative. We propose defining readability as the effective communication of valuation‐relevant information. The Fog Index—the most commonly applied readability measure—is shown to be poorly specified in financial applications. Of Fog's two components, one is misspecified and the other is difficult to measure. We report that 10‐K document file size provides a simple readability proxy that outperforms the Fog Index, does not require document parsing, facilitates replication, and is correlated with alternative readability constructs.

ABSTRACT Previous research uses negative word counts to measure the tone of a text. We show that word lists developed for other disciplines misclassify common words in financial text. In a large sample of 10‐Ks during 1994 to 2008, almost three‐fourths of the words identified as negative by the widely used Harvard Dictionary are words typically not considered negative in financial contexts. We develop an alternative negative word list, along with five other word lists, that better reflect tone in financial text. We link the word lists to 10‐K filing returns, trading volume, return volatility, fraud, material weakness, and unexpected earnings.

Using 947 acquisitions during 1970-89, this article finds a relationship between the postacquisition returns and the mode of acquisition and form of payment. During a five-year period following the acquisition, on average, firms that complete stock mergers earn significantly negative excess returns of -25.0 percent whereas firms that complete cash tender offers earn significantly positive excess returns of 61.7 percent. Over the combined preacquisition and postacquisition period, target shareholders who hold on to the acquirer stock received as payment in stock mergers do not earn significantly positive excess returns. In the top quartile of target to acquirer size ratio, they earn negative excess returns.

Recent studies have documented that firms conducting seasoned equity offerings have inordinately low stock returns during the five years after the offering, following a sharp run-up in the year prior to the offering. This article documents that the operating performance of issuing firms shows substantial improvement prior to the offering but then deteriorates. The multiples at the time of the offering, however, do not reflect an expectation of deteriorating performance. Issuing firms are disproportionately high-growth firms but issuers have much lower subsequent stock returns than nonissuers with the same growth rate.

Conrad and Kaul (1993) report that most of De Bondt and Thaler's (1985) long-term overreaction findings can be attributed to a combination of bid-ask effects when monthly cumulative average returns (CARs) are used, and price, rather than prior returns. In direct tests, we find little difference in test-period returns whether CARs or buy-and-hold returns are used, and that price has little predictive ability in cross-sectional regressions. The difference in findings between this study and Conrad and Kaul's is primarily due to their statistical methodology. They confound cross-sectional patterns and aggregate time-series mean reversion, and introduce a survivor bias. Their procedures increase the influence of price at the expense of prior returns.

Companies issuing stock during 1970 to 1990, whether an initial public offering or a seasoned equity offering, have been poor long-run investments for investors. During the five years after the issue, investors have received average returns of only 5 percent per year for companies going public and only 7 percent per year for companies conducting a seasoned equity offer. Book-to-market effects account for only a modest portion of the low returns. An investor would have had to invest 44 percent more money in the issuers than in nonissuers of the same size to have the same wealth five years after the offering date.

Using a sample of 986 convertible bond issuers of U.S. operating companies during 1975–1990, we document poor stock and operating performance in the years following the offering. The underperformance of stock returns cannot be explained by new issues activity (recent initial public offerings (IPOs) or seasoned equity offerings (SEOs)) or the level of the proceeds. Concurrent with the low subsequent stock returns, we document a rapid decline in the operating performance of the issuers following the offering. Profit margin and return on assets for the issuers are approximately halved in the four years after the convertible bond issue.

Abstract In business research, firm size is both ubiquitous and readily measured. Complexity, another firm-related construct, is also relevant, but difficult to measure and not well-defined. As a result, complexity is less frequently incorporated in empirical designs. We argue that most extant measures of complexity are one-dimensional, have limited availability, and/or are frequently misspecified. Using both machine learning and an application-specific lexicon, we develop a text solution that uses widely available data and provides an omnibus measure of complexity. Our proposed measure, used in tandem with 10-K file size, provides a useful proxy that dominates traditional measures.

Abstract We document by several methods that trading in Nasdaq stocks is localized, but find little evidence that cloudy weather in the city in which a company is based affects its returns. The first evidence of localized trading is that the time zone of a company's headquarters affects intraday trading patterns in its stock. Second, firms in blizzard-struck cities see a dramatic trading volume drop compared to firms in other cities. Third, the Yom Kippur holiday dampens trading volume in companies located in cities with high Jewish populations. Despite the strong evidence of localized trading, cloudy conditions near the firm's headquarters do not provide profitable trading opportunities.

Our paper examines the impact of geographic location on liquidity for U.S. rural- and urban-based companies. Even after adjusting for size and other factors, rural firms trade much less, are covered by fewer analysts, and are owned by fewer institutions than urban firms. Trading costs are higher for rural Nasdaq firms, and volume that can be attributed to marketwide factors is lower for rural stocks. The findings add to our understanding of the way that access to information and familiarity affect liquidity.