A Comprehensive Look at the Empirical Performance ofEquity Premium Prediction II

By Ivo Welch, Amit Goyal. Social Science Research Network, 2008

1,442 citations recorded by the source corpus.

Economists have suggested a whole range of variables that predict the equity premium: dividend price ratios, dividend yields, earnings-price ratios, dividend payout ratios, corporate or net issuing ratios, book-market ratios, beta premia, interest rates (in various guises), and consumption-based macroeconomic ratios (cay). Our paper comprehensively reexamines the performance of these variables, both in-sample and out-of-sample, as of 2005. We find that [a] over the last 30 years, the prediction models have failed both in-sample and out-of-sample; [b] the models are unstable, in that their out-of-sample predictions have performed unexpectedly poorly; [c] the models would not have helped an investor with access only to information available at the time to time the market.

Subfields: Finance, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/c2e2668444e64d070010e59a5b0dbd42be1e6d90

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Finance

In Strategy and Management

Citations in the corpus

Stock market volatility: Identifying major drivers and the nature of their impact (2015, neutral): “Although there has been a long tradition in attempting to predict asset prices (cf. Goyal and Welch, 2003; Welch and Goyal, 2008; Cochrane and Piazzesi, 2005; Lustig et al., 2011), the intense interest in volatility modeling began only after the seminal works of Engle (1982) and Bollerslev (1986),…”
Stock return predictability from a mixed model perspective (2020, methodology): “In this paper, we use 14 macroeconomic variables 1 that originally used in Welch and Goyal (2008) as predictors to predict stock return, as those variables are 1Those 14 economic variables can be downloaded from homepage of Amit Goyal at http://www.hec.unil.ch/agoyal/ Jo ur na l P re -p ro…”
Asset pricing tests with long run risks in consumption growth (2011, neutral): “[20] Goyal, A.”
Should investors include Bitcoin in their portfolios? A portfolio theory approach (2020, background): “An in-sample setting would implicitly assume perfect forecasts of the input parameters, but in practice, forecasts are subject to estimation errors, see for instance Welch and Goyal (2008), and many others.”
An Augmented q-Factor Model with Expected Growth* (2020, neutral): “…different from the influential stock market predictability literature, in which the predictive results depend on the predictors employed (Welch and Goyal, 2008), as well as the conditional asset pricing literature, in which the pricing results depend on the variables in the conditional beta…”
Time-varying model averaging (2020, positive): “Quarterly variables from Welch and Goyal (2008) are available for 1927Q1-2005Q4, since quarterly tock returns before 1927 are constructed by interpolation of lower-frequency data, which may be not reliable.”
Time series momentum: Is it there? (2020, background): “Due to concerns of data mining and structural breaks, studies on return predictability have shifted the focus to out-of-sample performance since Welch and Goyal (2008).”
The Time Variation in Risk Appetite and Uncertainty (2019, neutral): “We do this exercise out-of-sample as the literature has shown huge biases because of in-sample over ﬁ tting (Welch and Goyal 2008) and parameter instability (Koijen and Van Nieuwerburgh 2011).”