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Asset Pricing: Stock Markets

Paper Session

Sunday, Jan. 6, 2019 1:00 PM - 3:00 PM

Hilton Atlanta, Grand Ballroom B
Hosted By: American Finance Association
  • Chair: Johan Walden, University of California-Berkeley

Asset Prices and No-Dividend Stocks

Adem Atmaz
,
Purdue University
Suleyman Basak
,
London Business School

Abstract

We incorporate stocks that pay no dividends into an otherwise standard, parsimonious dynamic asset pricing framework. We find that such a simple feature leads to profound asset price implications, which are all supported empirically. In particular, we demonstrate that no-dividend stocks command lower mean returns, but also have higher return volatilities and higher market betas than comparable stocks that pay dividends. We also show that the presence of no-dividend stocks in the stock market leads to a lower correlation between the stock market return and aggregate consumption growth rate, a non-monotonic and even a negative relation between the stock market risk premium and its volatility, and a downward sloping term structure of equity risk premia. We provide straightforward intuition for all these results and the underlying economic mechanisms at play.

That Is Not My Dog: Why Doesn't the Log Dividend-Price Ratio Seem to Predict Future Log Returns or Log Dividend Growths?

Phil Dybvig
,
Washington University-St. Louis
Huacheng Zhang
,
Southwestern University of Finance and Economics

Abstract

Campbell and Shiller’s “accounting identity” implies that changes in the log dividend-price ratio must predict either future returns or future log dividend growth. However, neither quantity seems to be predictable — a well-known puzzle in the literature. We examine this puzzle step-by-step from theoretical derivation through empirical testing. Stationarity of the log dividend-price ratio is an important assumption behind the accounting identity, but Campbell and Shiller’s test justifying this assumption does not make sense, and a corrected test does not reject non-stationarity. Nonetheless, a truncated accounting identity works reasonably well in the existing sample, and we find that the log dividend-price ratio predicts log dividend growth, not returns. Traditional tests using one or a
few lags have trouble detecting predictability of log dividend growth because predictability is spread over many periods. Unfortunately, predictability of log dividend growth is not robust to subsamples,and it seems unwise to rely too much on the estimates given that the entire sample includes only five non-overlapping observations.

Expected Stock Returns and the Correlation Risk Premium

Adrian Buss
,
INSEAD
Lorenzo Schoenleber
,
Frankfurt School of Finance and Management
Grigory Vilkov
,
Frankfurt School of Finance and Management

Abstract

We document that information about the comovement of individual stocks, jointly extracted from index options and individual stock options, can be used to predict future market excess returns for horizons of up to 1 year, both in-sample and out-of-sample. The predictive power is incremental to that of risk measures exclusively based on the marginal distribution of the market, including (semi)variances and their risk premiums.~We attribute this predictability to the ability of expected correlation to capture expected variations in idiosyncratic risk and in the cross-sectional dispersion in systematic risk. A novel extension of the contemporaneous-beta approach significantly improves out-of-sample predictability.
Discussant(s)
Daniel Andrei
,
University of California-Los Angeles
Nicolae Gârleanu
,
University of California-Berkeley
Christian Heyerdahl-Larsen
,
London Business School
JEL Classifications
  • G1 - General Financial Markets