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Conditional Means of Time Series Processes and Time Series Processes for Conditional Means

Gabriele Fiorentini () and Enrique Sentana ()

Working Papers from CEMFI

Abstract: We study the process for the conditional mean of vector linear processes, which nest many models of interest. We also consider the joint process for a variable and its mean conditional on a multivariate information set. We compare the persistence of shocks to stationary variables and their means using impulse response functions. An empirical application suggests that US real stock returns are close to white noise, while expected returns follow an AR(1) with high autocorrelation. We also find that unexpected variations in expected returns immediately produce large negative observed returns, thereafter compensated by slowly diminishing increments on expected returns.

Date: 1996
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Related works:
Journal Article: Conditional Means of Time Series Processes and Time Series Processes for Conditional Means (1998)
Working Paper: Conditional means of time series processes and time series processes for conditional means (1997) Downloads
Working Paper: Conditional Means of Time Series Processes and Time Series Processes for Conditional Means (1996)
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