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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.

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Citations
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Journal ArticleDOI

Asset Allocation in Chinese Stock Market: The Role of Return Predictability

TL;DR: Li et al. as discussed by the authors investigated the asset allocation in Chinese stock market from a perspective of incorporating return predictability and found significant out-of-sample return predictionability in Chinese market based on a host of return predictors, and examined the performance of active portfolio strategies such as aggregate market timing strategy, and industry, size, and value rotation strategies to profitably exploit return prediction.
Journal ArticleDOI

Investor Sentiment and Paradigm Shifts in Equity Return Forecasting

TL;DR: Simchi-Levi et al. as discussed by the authors investigated the impact of investor sentiment on excess equity return forecasting and found that although fundamental variables can be strong predictors when sentiment is low, they tend to lose their predictive power when investor sentiment is high.
Journal ArticleDOI

Time-disaggregated dividend-price ratio and dividend growth predictability in large equity markets

TL;DR: In this article, the authors show that in large equity markets, the dividend price ratio is significantly related with the growth of future dividends, and they use monthly dividends and a mixed data sampling technique which allows them to cope with within-year seasonality.
Journal ArticleDOI

Stock Price Movements: Business-Cycle and Low-Frequency Perspectives

TL;DR: In this article, the authors find that a business-cycle component of the aggregate dividend yield strongly predicts short-term aggregate dividend growth and consumption growth, whereas its low-frequency counterpart significantly forecasts long-horizon market returns.
Journal ArticleDOI

Information Aggregation and P-Hacking

TL;DR: The interplay between information aggregation and p-hacking in the context of predicting stock returns is studied to find out whether the standard information-aggregation techniques exacerbate p-Hacking.
References
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Journal ArticleDOI

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ReportDOI

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Whitney K. Newey, +1 more
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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

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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.
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