Do Stock Prices More Too Much to be Justified by Subsequent Changes in Dividends?
By Robert J. Shiller (June 1981)
A simple model that is commonly used to interpret movements in corporate common stock price indexes asserts that real stock prices equal the present value of rationally expected or optionally forecasted future real dividends discounted by a constant read discount rate.
Stock price indexes seem too "volatile", =>the movement in stock prices indexes could not realistically be attributed to any objective new information, since movement in the price indexes seem to be " too big" relative to actual subsequent events.
Merton Miller and Franco Modigliani argued, such present value formula would entail on fundamental sort of double counting. It is incorrect to include in the present value formula both earnings at time t and the later earnings that accrue when time t earnings are reinvented. Muller and Modigliani showed a formula by which price might be regarded as the present value of earnings corrected for investments.
The standard deviation of the fitted value divided by average detrended price is 5.24 and 8.67 percent.
Measures of stock price volatility over the past century appear to be far too high -five to thirteen times too high - to be attributed to new information about future real dividends if uncertainty about future dividends is measured by the sample standard alterations of real dividends around their long- run exponential growth path.
One way of saving the general notion of efficient markets would be to attribute the movements m stock prices to changes m expected real interest rates.
Another way of saving the general notion of efficient markets is to say that our measure of the uncertainty regarding future dividends- the sample standard deviation of the movements of real dividends around their long-run exponential uncertainty about future dividends.
Such as explanation of the volatility of stock prices, however is "academic" , in that it relies fundamentally on unobservables and can not be evaluated statistically .
No comments:
Post a Comment