Expected Returns on Value, Growth,
and HML
In this paper, I analyze the
predictability of returns on value and growth portfolios and examine
time variation of the expected value premium. As a major tool, I use
the filtering technique, which accounts for time variation in
expected cash flows and explicitly exploits the constraints imposed
by the present value relation. I construct new predictors for
returns and dividend growth rates on the value and growth portfolios
and find that returns on growth stocks are much more predictable
than returns on value stocks. Applying the filtering technique to
the HML portfolio, I build a novel powerful forecaster for the value
premium. Consistent with the rational theories of the value premium,
I find evidence that the expected value premium is time-varying and
countercyclical.
This version: February 2008
Filtering Out Expected Dividends and Expected Returns
This paper suggests a new state space approach
to analysis of stock return predictability. Acknowledging that
expected returns and expected dividends are unobservable, the Kalman
filter technique is used to extract them from the observed history
of realized dividends and returns. This approach explicitly accounts
for the variation in expected dividend
growth and allows to make estimates more robust to structural breaks
in the means of dividend growth and returns. The constructed
predictor outperforms the dividend-price ratio both in and out of
sample, providing statistically and
economically significant forecasts. The finite sample likelihood
ratio test reliably rejects the hypothesis of constant expected
returns.
This version: October 2007
Forecasting the Forecasts of
Others: Implications for Asset Pricing
(joint with Igor Makarov)
We study rational expectation equilibria (REE) in
dynamic asset pricing models with heterogeneously informed agents.
The contribution of the paper is twofold. First, we show that under
mild conditions the state space of such models can be infinite
dimensional. This result indicates that the domain of analytically
tractable dynamic models with asymmetric information is severely
restricted. Second, we demonstrate that even though dynamics of
stochastic supply place significant restrictions on the possible
sign of return autocorrelations, under some circumstances asymmetric
information can generate positive autocorrelation in REE.
This version: June 2008
Other papers