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Multifrequency News and Stock Returns

Listed author(s):
  • Laurent E. Calvet
  • Adlai J. Fisher

Recent research documents that aggregate stock prices are driven by shocks with persistence levels ranging from daily intervals to several decades. Building on these insights, we introduce a parsimonious equilibrium model in which regime-shifts of heterogeneous durations affect the volatility of dividend news. We estimate tightly parameterized specifications with up to 256 discrete states on daily U.S. equity returns. The multifrequency equilibrium has significantly higher likelihood than the classic Campbell and Hentschel (1992) specification, while generating volatility feedback effects 6 to 12 times larger. We show in an extension that Bayesian learning about stochastic volatility is faster for bad states than good states, providing a novel source of endogenous skewness that complements the "uncertainty" channel considered in previous literature (e.g., Veronesi, 1999). Furthermore, signal precision induces a tradeoff between skewness and kurtosis, and economies with intermediate investor information best match the data.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 11441.

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Date of creation: Jun 2005
Publication status: published as Calvet, Laurent E. and Adlai J. Fisher. "Multifrequency News and Stock Returns." Journal of Financial Economics 86, 1 (October 2007): 178-212.
Handle: RePEc:nbr:nberwo:11441
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