The Journal of Finance publishes leading research across all the major fields of finance. It is one of the most widely cited journals in academic finance, and in all of economics. Each of the six issues per year reaches over 8,000 academics, finance professionals, libraries, and government and financial institutions around the world. The journal is the official publication of The American Finance Association, the premier academic organization devoted to the study and promotion of knowledge about financial economics.
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Search results: 5.
Measuring Readability in Financial Disclosures
Published: 03/26/2014 | DOI: 10.1111/jofi.12162
TIM LOUGHRAN, BILL MCDONALD
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.
When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks
Published: 01/06/2011 | DOI: 10.1111/j.1540-6261.2010.01625.x
TIM LOUGHRAN, BILL MCDONALD
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.
Nonnormalities and Tests of Asset Pricing Theories
Published: 09/01/1989 | DOI: 10.1111/j.1540-6261.1989.tb02629.x
JOHN AFFLECK‐GRAVES, BILL MCDONALD
The robustness of the multivariate test of Gibbons, Ross, and Shanken (1986) to nonnormalities in the residual covariance matrix is examined. After considering the relative performance of various tests of normality, simulation techniques are used to determine the effects of nonnormalities on the multivariate test. It is found that, where the sample nonnormalities are severe, the size and/or power of the test can be seriously misstated. However, it is also shown that these extreme sample values may overestimate the population parameters. Hence, we conclude that the multivariate test is reasonably robust with respect to typical levels of nonnormality.
Predicting Stock Returns in an Efficient Market
Published: 09/01/1990 | DOI: 10.1111/j.1540-6261.1990.tb02429.x
RONALD J. BALVERS, THOMAS F. COSIMANO, BILL MCDONALD
An intertemporal general equilibrium model relates financial asset returns to movements in aggregate output. The model is a standard neoclassical growth model with serial correlation in aggregate output. Changes in aggregate output lead to attempts by agents to smooth consumption, which affects the required rate of return on financial assets. Since aggregate output is serially correlated and hence predictable, the theory suggests that stock returns can be predicted based on rational forecasts of output. The empirical results confirm that stock returns are a predictable function of aggregate output and also support the accompanying implications of the model.