Knowledge that Transforms

Finance theory proposes that firms’ cost of capital increases when market makers set wider spreads due to perceived higher information asymmetry across traders. Using a sample of UK investment property firms and controlling for firms’ non‐random selection of external monitors, we find evidence that market makers perceive information asymmetry across traders to be lower for firms employing external appraisers versus those employing internal appraisers. This evidence is consistent with liquidity‐motivated traders being unable to overcome such reliability differences using asset value information from sources other than accounting. We fail to find a similar difference for firms employing Big 6 versus non‐Big 6 auditors. Our findings contribute to the debate over the recognition of fair value estimates for long‐lived tangible assets by documenting that reliability differences attributable to differential monitoring by appraisers can affect information asymmetry, and therefore firms’ cost of capital.

Recent studies suggest the apparent delay in the stock‐price response to earnings announcements (i.e., post‐earnings announcement drift) is caused by investors who underestimate the autocorrelation of seasonally‐differenced earnings (persistence). I present results that suggest: (1) a firm’s future persistence is predictable on the basis of its past persistence; (2) the immediate stock‐price response to earnings is positively related to historical persistence; (3) post‐earnings‐announcement drift is independent of historical persistence; and (4) consistent with (2) and (3), the difference between a firm’s current observed persistence and that implied in stock prices is independent of its historical persistence. These results extend prior research by demonstrating that investors are aware not only that seasonally‐differenced earnings are autocorrelated, but that investors recognize firm‐specific differences in the magnitude of the autocorrelation.

Preannouncements of earnings tend to overstate negative or understate positive news, which decreases the chance of a negative surprise when actual earnings is announced. We conduct an experiment to investigate how experienced sell‐side analysts’ earnings forecasts are affected by preannouncements that either understate, accurately state, or overstate the magnitude of positive or negative total earnings news, holding total earnings news constant. We find that firms with negative (positive) total news receive the highest post‐earnings announcement forecasts of future earnings when the earlier preannouncement overstates (understates) the magnitude of the news. These forecasts are consistent with the analysts’ perceptions about the firms’ future prospects, but not their perceptions of management. While analysts expect preannouncements to be lower than actual earnings, they do not adjust their forecasts for these beliefs. These insights into analysts’ responses have implications both for managers and analysts.

We use a simulation model for a pharmaceutical R&D program to examine the tradeoff between objectivity and relevance of accounting information under various methods of R&D reporting. A simple capitalization rule, similar to the successful‐efforts method of capitalizing oil and gas exploration costs, provides a stronger relation between accounting information and economic values than immediate expensing of R&D outlays or capitalizing the full cost of outlays. The superior relevance of this “successful‐efforts” method persists even when earnings management is widespread.

The costs associated with compiling data on employee stock option portfolios is a substantial obstacle in investigating the impact of stock options on managerial incentives, accounting choice, financing decisions, and the valuation of equity. We present an accurate method of estimating option portfolio value and the sensitivities of option portfolio value to stock price and stock‐return volatility that is easily implemented using data from only the current year’s proxy statement or annual report. This method can be applied to either executive stock option portfolios or to firm‐wide option plans. In broad samples of actual and simulated CEO option portfolios, we show that these proxies capture more than 99% of the variation in option portfolio value and sensitivities. Sensitivity analysis indicates that the degree of bias in these proxies varies with option portfolio characteristics, and is most severe in samples of CEOs with a large proportion of out‐of‐the‐money options. However, the proxies’ explanatory power remains above 95% in all subsamples.

While the influence of earnings performance on disclosure is a fundamental issue in the disclosure literature, our understanding of this influence is limited. In this paper, I examine a comprehensive set of disclosures from a sample of firms experiencing an extended period of seasonally adjusted earnings increases. I study how these firms adjust disclosure in response to earnings increases, how disclosure changes as the period of strong earnings performance nears an end and how firms disclose during a subsequent period of earnings decline. I find an increase in disclosure during the period of increased earnings. This increase is pervasive across all types of disclosure and tends to be bundled with earnings announcements. The market responds positively to this disclosure. Firms continue to disclose at a high level as they approach earnings declines. However, they shift to disclosures that focus on the positive short‐term results and do not discuss the impending decreases. While this behavior is systematic, the market does not appear to anticipate the subsequent earnings declines. Once the firms announce earnings declines, the magnitude of disclosure returns to the level provided prior to the increased earnings.

We define an intertemporal tax discontinuity (ITD) as a circumstance in which different tax rates are applied to gains realized at one point in time versus some other point in time. We study the effects of ITDs on market behaviors at the time of disclosures of firm performance, assuming that all investors who trade firm equities are subject to tax. The results of our paper suggest that relative to an economy in which ITDs are absent, ITDs may dampen trading volume and amplify price changes at the time of disclosure.

This paper studies how firm disclosure activity affects the relation between current annual stock returns, contemporaneous annual earnings and future earnings. Our results show that firms with relatively more informative disclosures “bring the future forward” so that current returns reflect more future earnings news. We also find that changes in disclosure activity are positively related to changes in the importance of future earnings news for current returns. These results suggest that a firm’s disclosure activity reveals credible, relevant information not in current earnings, and that this information is incorporated into the current stock price.

We examine the valuation performance of a comprehensive list of value drivers and find that multiples derived from forward earnings explain stock prices remarkably well: pricing errors are within 15 percent of stock prices for about half our sample. In terms of relative performance, the following general rankings are observed consistently each year: forward earnings measures are followed by historical earnings measures, cash flow measures and book value of equity are tied for third, and sales performs the worst. Curiously, performance declines when we consider more complex measures of intrinsic value based on short‐cut residual income models. Contrary to the popular view that different industries have different “best” multiples, these overall rankings are observed consistently for almost all industries examined. Since we require analysts’ earnings and growth forecasts and positive values for all measures, our results may not be representative of the many firm‐years excluded from our sample.

In this paper we develop some econometric theory for factor models of large dimensions. The focus is the determination of the number of factors (r), which is an unresolved issue in the rapidly growing literature on multifactor models. We first establish the convergence rate for the factor estimates that will allow for consistent estimation of r. We then propose some panel criteria and show that the number of factors can be consistently estimated using the criteria. The theory is developed under the framework of large cross-sections (N) and large time dimensions (T). No restriction is imposed on the relation between N and T. Simulations show that the proposed criteria have good finite sample properties in many configurations of the panel data encountered in practice.