Disentangling Managers’ and Analysts’ Non‐GAAP Reporting

Researchers frequently proxy for managers’ non‐GAAP disclosures using performance metrics available through analyst forecast data providers (FDPs), such as I/B/E/S. The extent to which FDP‐provided earnings are a valid proxy for managers’ non‐GAAP reporting, however, has been debated extensively. We explore this important question by creating the first large‐sample data set of managers’ non‐GAAP earnings disclosures, which we directly compare to I/B/E/S data. Although we find a substantial overlap between the two data sets, we also find that they differ in systematic ways because I/B/E/S (1) excludes managers’ lower quality non‐GAAP numbers and (2) sometimes provides higher quality non‐GAAP measures that managers do not explicitly disclose. Our results indicate that using I/B/E/S to identify managers’ non‐GAAP disclosures significantly underestimates the aggressiveness of their reporting choices. We encourage researchers interested in managers’ non‐GAAP reporting to use our newly available data set of manager‐disclosed non‐GAAP metrics because it more accurately captures managers’ reporting choices.     

Real Stock Returns and Inflation

This paper develops the relation between the real rate of return on the stock market and changes in the price level using a multiperiod economy with production. The observed relation between real ex post stock returns and inflation is shown to be consistent with equilibrium in an economy with rational investors. The relation between expected real returns and expected inflation is shown to depend on the form of the economy's production function and on the form of investor preferences. When the production function exhibits stochastic constant returns to scale, the model explains the negative relation between expected real returns and expected inflation which has frequently been observed in empirical studies.     

Which Institutional Investors Trade Based on Private Information About Earnings and Returns?

Recent work suggests that institutional investors execute profitable trades based on private information about earnings and returns. We provide new evidence on the prevalence and sources of such informed trading by (1) testing for the creation and liquidation of positions based on private information, (2) introducing private information proxies that reflect the size and nature of an institution's position in each portfolio firm, and (3) using a methodology that examines multiple investor characteristics simultaneously at the institution‐firm level. We find that changes in ownership by institutions with large positions in a firm are consistent with informed trading. However, other previously documented proxies for private information produce results more consistent with risk‐based trading (e.g., investment style) or insignificant in the presence of other proxies (e.g., fiduciary type). We also find that informed trading is more prevalent in small firms and when the large positions are taken by investment advisers and large institutions.     

A Comparison of Dividend,Cash Flow,and Earnings Approaches to Equity Valuation*

Standard formulas for valuing the equity of going concerns require forecasting payoffs to infinity but practical analysis requires that payoffs be forecasted over finite horizons. This truncation inevitably involves often-troublesome terminal value calculations. This paper contrasts dividend discount techniques, discounted cash flow analysis, and techniques based on accrual earnings when each is applied with finite-horizon forecasts. Valuations based on average ex post payoffs over various horizons, with and without terminal value calculations, are compared with ex ante market prices to discover the error introduced by each technique in truncating the horizon. Valuation errors are lower using accrual earnings techniques rather than cash flow and dividend discounting techniques. The accounting features that make a given technique less than ideal for finite horizon analysis are also detailed. Conditions where a given technique requires particularly long forecasting horizons are identified and the performance of the alternative techniques under those conditions is examined.