Urban companies are located near millions more potential investors and sophisticated money managers than non-urban companies. More investors are familiar with urban companies and have access to informal information about them. The stock of urban companies is also more liquid than the stock of non-urban companies. We hypothesize that these factors lead information to be spread from urban companies to other companies. Urban stock returns lead rural/small city stock returns even controlling for size, industry, and analyst coverage. Closer examination of the lead–lag relation reveals that urgent trades, which are likely to reflect short-lived information, are much more common for urban firms. Information appears to be uncovered through informal means more easily available to people physically near a company. We discuss the corporate finance implications of our findings.

Baginski, Demers, Kausar, and Yu (2018) demonstrate that small, retail investors often misinterpret the linguistic tone contained in managerial forecast announcements during the 1997-2006 time period. This is in contrast to the trading behavior of large, institutional investors. My commentary offers some concerns/suggestions about the measurement of linguistic tone, the separation of small and large traders’ activities, the implications of this type of research for regulatory actions, and includes possible additional research suggested by their paper.

Reinganum (1990) reports that small NYSE securities have average returns about 6% per year higher than those of similarly-sized NASDAQ securities during the 1973–1988 period. He attributes the return differential to market microstructure differences. In contrast, this paper demonstrates that differences in the characteristics of the companies listed on the two exchanges explain much of the disparity. About 60% of the return differential can be attributed to the poor performance of recent initial public offerings, which comprise a large portion of the firms on NASDAQ. On average, IPOs underperform during the six calendar years after going public.

Fama and French (1992) report that size and the book-to-market ratio capture the cross-sectional variation of average stock returns for the universe of NYSE, Amex, and Nasdaq securities. This paper, in providing an exhaustive exploration of book-to-market across the dimensions of firm size, exchange listing, and calendar seasonally, reports that Fama and French's empirical findings are driven by two features of the data: a January seasonal in the book-to-market effect, and exceptionally low returns on small, young, growth stocks. In the largest size quintile of all firms (accounting for 73% of the total market value of all publicly traded firms), book-to-market has no significant explanatory power on the cross-section of realized returns during the 1963–1995 period. Thus, book-to-market as such would have less importance to money managers than the literature would have led us to believe.

ABSTRACT Relative to quantitative methods traditionally used in accounting and finance, textual analysis is substantially less precise. Thus, understanding the art is of equal importance to understanding the science. In this survey, we describe the nuances of the method and, as users of textual analysis, some of the tripwires in implementation. We also review the contemporary textual analysis literature and highlight areas of future research.

Form S-1 is the first SEC filing in the initial public offering (IPO) process. The tone of the S-1, in terms of its definitiveness in characterizing the firm’s business strategy and operations, should affect investors’ ability to value the IPO. We find that IPOs with high levels of uncertain text have higher first-day returns, absolute offer price revisions, and subsequent volatility. Our findings provide empirical evidence for the theoretical models of uncertainty, bookbuilding, and prospect theory.

An analysis of 4,814 SEOs during 1986–1999 indicates that the average offering ofnew shares is priced at a discount of 3% from the closing price on the day before the issue. Discounts have risen steadily over time, sharply increasing the indirect costs of issuing seasoned equity. There is evidence of increased clustering of offer prices at integers, and of greater importance in the analyst coverage provided by underwriters. Adjusting for other factors, we find that issues with integer offer prices, and underwriters with highly regarded analysts, are increasingly associated with larger discounts. The rise in discounts is consistent with an increased ability of investment bankers to extract rents from issuing firms.

Numerous banks and thrifts went public amid the favorable regulatory climate and strong capital market of the mid-1980s. A sample of 393 bank initial public offerings from 1983 to 1991 lagged three benchmarks of returns over a five-year post-offering holding period. This poor performance is concentrated among larger institutions with more aggressive loan growth. Following the IPO, many of these banks also recorded dramatic increases in loan losses. The evidence suggests the market may have fixated on the rapid growth of these institutions or did not adequately account for changes in the post-IPO risk of their loan portfolios.

Practitioners increasingly use the enterprise multiple (EM) as a valuation measure. EM is (equity value + debt + preferred stock – cash) / (EBITDA). We document that EM is a strong determinant of stock returns. Following Fama and French (1993) and Chen, Novy-Marx, and Zhang (2010), we create an EM factor that generates a return premium of 5.28% per year. We interpret EM as a proxy for the discount rate. Firms with low EM values appear to have higher discount rates and higher subsequent stock returns than firms with high EM values.

One of the puzzles regarding initial public offerings (IPOs) is that issuers rarely get upset about leaving substantial amounts of money on the table, defined as the number of shares sold times the difference between the first-day closing market price and the offer price. The average IPO leaves $9.1 million on the table. This number is approximately twice as large as the fees paid to investment bankers and represents a substantial indirect cost to the issuing firm. We present a prospect theory model that focuses on the covariance of the money left on the table and wealth changes. Our reasoning also provides an explanation for a second puzzling pattern: much more money is left on the table following recent market rises than after market falls. This results in an explanation of hot issue markets. We also offer a new explanation for why IPOs are underpriced.