Abstract
ABSTRACTThis paper uses a vector autoregressive model to decompose excess stock and 10‐year bond returns into changes in expectations of future stock dividends, inflation, short‐term real interest rates, and excess stock and bond returns. In monthly postwar U.S. data, stock and bond returns are driven largely by news about future excess stock returns and inflation, respectively. Real interest rates have little impact on returns, although they do affect the short‐term nominal interest rate and the slope of the term structure. These findings help to explain the low correlation between excess stock and bond returns.
Highlights
Mainstream research in empirical asset pricing has traditionally treated the variances and covariances of asset returns as being exogenous
Suppose that innovations to a particular variable, say industrial production, are associated with stock market movements. This could reflect an association of industrial production with changing expectations of future cash flows, or an association with changing discount rates
We show why asset prices are useful for forecasting long-horizon returns, and why lagged asset returns may not help to forecast returns even when expected returns vary through time
Summary
Mainstream research in empirical asset pricing has traditionally treated the variances and covariances of asset returns as being exogenous. A number of authors have challenged the finance profession to bring the second moments of asset returns within the set of phenomena to be explained. Richard Roll has issued a similar challenge in a recent Presidential Address to the American Finance Association (1988), saying that "The immaturity of our science is illustrated by the conspicuous lack of predictive content about some of its most intensely interesting phenomena, changes in asset prices". Eugene Fama (1990a) has applied a similar methodology to the aggregate stock market He finds that almost two-thirds of the variance of aggregate stock price movements can be accounted for by innovations in variables proxying for corporate cash flows and investors' discount rates.. The use of contemporaneous regressions to explain asset price variability is appealing because it is simple, and because it is an extension of the well-established event study methodology in finance. The contemporaneous regression approadi cannot distinguish these possibilities, or tell us about their relative importance
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