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Stock Market Forecastability and Volatility: A Statistical Appraisal

N. Gregory Mankiw, +2 more
- 01 May 1991 - 
- Vol. 58, Iss: 3, pp 455-477
TLDR
In this article, the authors present and implement statistical tests of stock market forecastability and volatility that are immune from the severe statistical problems of earlier tests, and show that although the null hypothesis of market efficiency is rejected, the rejections are only marginal.
Abstract: 
This paper presents and implements statistical tests of stock market forecastability and volatility that are immune from the severe statistical problems of earlier tests. It finds that although the null hypothesis of market efficiency is rejected, the rejections are only marginal. The paper also shows how volatility tests and recent regression tests are closely related, and demonstrates that when finite sample biases are taken into account, regression tests also fail to provide strong evidence of violations of the conventional valuation model.

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NBER
Working
Paper
#3154
October
1989
STOCK
MARKET
FORECASTABILITY
AND
VOLATILITY:
A STATISTICAL
APPRAISAL
ABSTRACT
This
paper
presents
and
implements
statistical
tests
of
stock
market
forecastability
and
volatility
that
are
immune
from
the
severe
statistical
problems
of
earlier
tests.
Although
the
null
hypothesis
of
strict
market
efficiency
is
rejected,
the
evidence
against
the
hypothesis
is
not
overwhelming.
That
is,
the
data
do
not
provide
evidence
of
gross
violations
of
the
conventional
valuation
model.
N.
Gregory
Mankiw
Department
of
Economics
Harvard
University
Cambridge,
MA
02138
(617)495-4301
David
Romer
Department
of
Economics
University
of
California
Berkeley,
CA
94720
(415)642-1785
Matthew
D.
Shapiro
Department
of
Economics
University
of
Michigan
Ann
Arbor,
MI 48109
(313)764-5419
Citations
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Exchange Rates and Monetary Fundamentals: What Do We Learn From Long-Horizon Regressions?

Lutz Kilian
- 01 Sep 1999 - 
TL;DR: In this article, the use of a new bootstrap method for small-sample inference in long-horizon regressions is illustrated by analysing the longhorizon predictability of four major exchange rates, and the findings are reconciled with those of an earlier study by Mark.
Journal ArticleDOI

Stock market volatility around national elections

Jędrzej Białkowski, +2 more
- 01 Sep 2008 - 
TL;DR: In this paper, the authors investigated whether the event of a national election induces higher stock market volatility and found that the countryspecific component of index return variance can easily double during the week around the Election Day, which attests to the fact that investors are surprised by the actual election outcome.
Journal ArticleDOI

Explaining the Variance of Price–Dividend Ratios

John H. Cochrane
- 01 Apr 1992 - 
TL;DR: In this paper, the authors report a bound on the variance of price-dividend ratios and a decomposition of their variance into terms that reflect changes in dividend growth and discount rates.
Journal ArticleDOI

Business Fixed Investment and "Bubbles": The Japanese Case

Robert S. Chirinko, +1 more
- 01 Jun 2001 - 
TL;DR: In this paper, the authors investigated the effect of stock market bubbles on fixed investment in Japan and found that there was a bubble that had an economically important statistically significant effect on business fixed investment.
Journal ArticleDOI

Media Frenzies in Markets for Financial Information

Laura Veldkamp
- 01 May 2006 - 
TL;DR: In this article, the authors predict that asset market movements generate news and news raises prices and price dispersion in emerging equity markets, and new panel data on news coverage support the model's predictions.
References
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Posted Content

A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelationconsistent Covariance Matrix

Whitney K. Newey, +3 more
- 01 Apr 1986 - 
TL;DR: In this article, a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction is described.
Journal ArticleDOI

Dividend yields and expected stock returns

Eugene F. Fama, +1 more
- 01 Oct 1988 - 
TL;DR: In this article, the power of dividend yields to forecast stock returns, measured by regression R2, increases with the return horizon, and the authors offer a two-part explanation: high autocorrelation causes the variance of expected returns to grow faster than the return-horizon.
Journal ArticleDOI

Stock Market Prices Do Not Follow Random Walks: Evidence from a Simple Specification Test

Andrew W. Lo, +1 more
- 01 Jan 1988 - 
TL;DR: In this article, the random walk model is strongly rejected for the entire sampleperiod (1962-1985) and for all subperiods for a variety of aggregate returns indexes and size-sorted porfolios.
Journal ArticleDOI

Permanent and Temporary Components of Stock Prices

Eugene F. Fama, +1 more
- 01 Apr 1988 - 
TL;DR: This article found that a slowly mean-reverting component of stock prices tends to induce negative autocorrelation in returns, which is weak for the daily and weekly holding periods common in market efficiency tests but stronger for long-horizon returns.
ReportDOI

Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends

Robert J. Shiller
- 01 Feb 1980 - 
TL;DR: In this article, the authors developed the efficient markets model in Section I to clarify some theoretical questions that may arise in connection with the inequality, and some similar inequalities will be derived that put limits on the standard deviation of the innovation in price and the variance of the change in price.