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Business Cycle Variation in Earnings Forecasts and Common Stock Returns

Business Cycle Variation in Earnings Forecasts and Common Stock Returns

Co-author: Vivek Mande, University of Nebraska at Omaha

Abstract: There is considerable evidence that common stock returns are predictable and that they vary over the business cycle. One way to assess whether this predictability is a result of the rational variation of risk premia, consistent with market efficiency, is to measure the expectations of market participants over the business cycle. If the time variation of returns is a result of market inefficiency, then the expectational errors of market participants should be predictable using the same variables that forecast future returns. In this paper we investigate whether one measure of expectations, analysts' forecasts of earnings, exhibit predictable biases.

We investigate the Value-Line forecasts of the annual earnings of firms on the Dow-Jones indices (industrial, transportation and utility) over the period 1960-1986, and find that the forecast errors are predictable using the same variables that forecast future returns. We find that analysts consistently overestimate future earnings in economic downturns and underestimate future earnings in economic expansions. In addition, we find that the analysts revise their forecasts in a predictable way so that the magnitude of the analysts' bias decreases as the end of the fiscal year approaches. Counter to some previous studies, we find that average forecast errors may be either positive or negative, depending on economic conditions.

To determine whether the expectational biases of the analysts are incorporated into market prices, we measure the share price reaction to analysts' forecast revisions. If the market is efficient there should be no price reaction to predictable revisions. We find that the market reacts positively to upward forecast revisions, but find only mixed evidence on the price reaction to the predictable component of these revisions.   »»» Click Here For More

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