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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Information Acquisition in Rumor‐Based Bank Runs
Published: 11/11/2014 | DOI: 10.1111/jofi.12202
ZHIGUO HE, ASAF MANELA
We study information acquisition and dynamic withdrawal decisions when a spreading rumor exposes a solvent bank to a run. Uncertainty about the bank's liquidity and potential failure motivates depositors who hear the rumor to acquire additional noisy signals. Depositors with less informative signals may wait before gradually running on the bank, leading to an endogenous aggregate withdrawal speed and bank survival time. Private information acquisition about liquidity can subject solvent‐but‐illiquid banks to runs, and shorten the survival time of failing banks. Public provision of solvency information can mitigate runs by indirectly crowding‐out individual depositors' effort to acquire liquidity information.
Business News and Business Cycles
Published: 08/09/2024 | DOI: 10.1111/jofi.13377
LELAND BYBEE, BRYAN KELLY, ASAF MANELA, DACHENG XIU
We propose an approach to measuring the state of the economy via textual analysis of business news. From the full text of 800,000 Wall Street Journal articles for 1984 to 2017, we estimate a topic model that summarizes business news into interpretable topical themes and quantifies the proportion of news attention allocated to each theme over time. News attention closely tracks a wide range of economic activities and can forecast aggregate stock market returns. A text‐augmented vector autoregression demonstrates the large incremental role of news text in forecasting macroeconomic dynamics. We retrieve the narratives that underlie these improvements in market and business cycle forecasts.