scispace - formally typeset
Journal ArticleDOI

Market Expectations in the Cross‐Section of Present Values

Bryan T. Kelly, +1 more
- 01 Oct 2013 - 
- Vol. 68, Iss: 5, pp 1721-1756
TLDR
Kelly et al. as mentioned in this paper showed that relying on aggregate quantities drastically understates the degree of value ratios' predictive content for both returns and cash flow growth, and hence understate the volatility of investor expectations.
Abstract
Returns and cash flow growth for the aggregate U.S. stock market are highly and robustly predictable. Using a single factor extracted from the cross-section of book-tomarket ratios, we find an out-of-sample return forecasting R 2 of 13% at the annual frequency (0.9% monthly). We document similar out-of-sample predictability for returns on value, size, momentum, and industry portfolios. We present a model linking aggregate market expectations to disaggregated valuation ratios in a latent factor system. Spreads in value portfolios’ exposures to economic shocks are key to identifying predictability and are consistent with duration-based theories of the value premium. THE MOST COMMON APPROACH to measuring aggregate return and cash flow expectations is predictive regression. As suggested by the present value relationship between prices, discount rates, and future cash flows, research shows that the aggregate price-dividend ratio is among the most informative predictive variables. Typical in-sample estimates find that about 10% of annual return variation can be accounted for by forecasts based on the aggregate book-tomarket ratio, but find little or no out-of-sample predictive power. 1 In this paper we show that reliance on aggregate quantities drastically understates the degree of value ratios’ predictive content for both returns and cash flow growth, and hence understates the volatility of investor expectations. Our estimates suggest that as much as 13% of the out-of-sample variation in annual market returns (as much as 12% for dividend growth), and somewhat more of the insample variation, can be explained by the cross-section of past disaggregated value ratios. To harness disaggregated information we represent the cross-section of assetspecific book-to-market ratios as a dynamic latent factor model. We relate disaggregated value ratios to aggregate expected market returns and cash flow growth. Our model is based on the idea that the same dynamic state variables driving aggregate expectations also govern the dynamics of the entire panel ∗ Kelly is with Booth School of Business, University of Chicago, and Pruitt is with the Board of Governors of the Federal Reserve System. The view expressed here are those of the authors and do not necessarily reflect the views of the Federal Reserve System or its staff. 1 See Cochrane (2005) and Koijen and Van Nieuwerburgh (2011) for surveys of return and cash flow predictability evidence using the aggregate price-dividend ratio. Similar results obtain from forecasts based on the aggregate book-to-market ratio.

read more

Citations
More filters
Proceedings ArticleDOI

Chinese Investor Sentiment and Stock Returns

Mengni Xie
TL;DR: Wang et al. as discussed by the authors used principal component analysis method to construct the monthly investor sentiment index, then using Granger test to examine whether Chinese investor sentiment and stock returns can influence each other.
Journal ArticleDOI

Industry variance risk premium, cross‐industry correlation, and expected returns

TL;DR: In this paper , the authors investigated the variance risk premium (VRP) and implied correlation (IC) at the industry level, using the index and sector exchange-traded fund options, and construct-sector VRPs and cross-sector IC measures.
Journal ArticleDOI

A PLS Approach to Measuring Investor Sentiment in Chinese Stock Market

TL;DR: Wang et al. as mentioned in this paper selected five objective sentiment indicators and one subjective sentiment indicator to build investor sentiment composite index in Chinese stock market by using the partial least squares, which improved the shortcomings of the principal component analysis.
Journal ArticleDOI

Nonlinear asset pricing in Chinese stock market: A deep learning approach

TL;DR: Wang et al. as discussed by the authors presented a Long and Short-Term Memory Neural Network Model (LSTM) to capture the non-linear pricing structure among five elements in the Chinese stock market, including market portfolio return, market capitalisation, book-to-market ratio, earnings factor, and investment factor.
Journal ArticleDOI

Principal Portfolios

References
More filters
Journal ArticleDOI

A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity

Halbert White
- 01 May 1980 - 
TL;DR: In this article, a parameter covariance matrix estimator which is consistent even when the disturbances of a linear regression model are heteroskedastic is presented, which does not depend on a formal model of the structure of the heteroSkewedness.
Journal ArticleDOI

Common risk factors in the returns on stocks and bonds

TL;DR: In this article, the authors identify five common risk factors in the returns on stocks and bonds, including three stock-market factors: an overall market factor and factors related to firm size and book-to-market equity.
ReportDOI

A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix

Whitney K. Newey, +1 more
- 01 May 1987 - 
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

Capital asset prices: a theory of market equilibrium under conditions of risk*

TL;DR: In this paper, the authors present a body of positive microeconomic theory dealing with conditions of risk, which can be used to predict the behavior of capital marcets under certain conditions.
Journal ArticleDOI

Risk, Return, and Equilibrium: Empirical Tests

TL;DR: In this article, the relationship between average return and risk for New York Stock Exchange common stocks was tested using a two-parameter portfolio model and models of market equilibrium derived from the two parameter portfolio model.
Related Papers (5)