Earnings and price momentum

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Abstract

This paper examines whether earnings momentum and price momentum are related. Both in time-series as well as in cross-sectional asset pricing tests, we find that price momentum is captured by the systematic component of earnings momentum. The predictive power of past returns is subsumed by a zero-investment portfolio that is long on stocks with high earnings surprises and short on stocks with low earnings surprises. Further, returns to the earnings-based zero-investment portfolio are significantly related to future macroeconomic activities, including growth in GDP, industrial production, consumption, labor income, inflation, and T-bill returns.

Introduction

In a seminal paper, Fama (1998) once again makes the case for the efficient markets hypothesis. Notwithstanding the recent interest in behavioral finance—an interest that is driven by data that are inconsistent with the standard frictionless asset pricing models—Fama argues that the null should still be one of market efficiency. However, Fama concedes that two robust and persistent anomalies pose challenges to the efficient markets paradigm. These two anomalies are (i) the post-earnings announcement drift, or earnings momentum, first documented by Ball and Brown (1968) and (ii) the short-run return continuation, or price momentum, documented by Jegadeesh and Titman (1993). Earnings momentum refers to the fact that firms reporting unexpectedly high earnings subsequently outperform firms reporting unexpectedly low earnings. The superior performance lasts for about nine months after the earnings announcement. Price momentum refers to the strategy that buys past winners and sells past losers, which earns abnormal returns for a period of up to one year after the execution of the strategy.

In this paper, we study whether earnings momentum and price momentum are related. Our analysis extends Chan et al. (1996), who also investigate whether the predictability of future returns based on past returns is subsumed by individual stock earnings surprises in cross-sectional tests. If price momentum is related to macroeconomic variables, as shown by Chordia and Shivakumar (2002), Ahn et al. (2003) and Avramov and Chordia (2005), then firm-specific characteristics, such as earnings surprises, will be insufficient to capture price momentum. We seek a relation between price momentum and the systematic component of earnings momentum.

Based on the most recent earnings surprise, measured as standardized unexpected earnings (SUE) following standard practice in post-earnings announcement drift literature, we sort firms into decile portfolios and then examine whether a zero-investment portfolio that is long the highest earnings surprise portfolio and short the lowest earnings surprise portfolio captures the price momentum phenomenon. Both in time-series and cross-sectional asset pricing tests, we find that the earnings-based zero-investment portfolio (denoted PMN for positive minus negative) captures the payoffs to price momentum strategies. For instance, the price momentum effect (as measured by the portfolio WML, which is long past winners and short past losers), at about 76 basis points per month, is reduced to essentially zero in time-series tests after controlling for the exposure of firms to PMN. Since PMN is a diversified portfolio, it is unlikely to reflect any firm-specific information. Thus, the above results are consistent with price momentum being primarily related to the systematic component of earnings momentum.

To better understand the ability of PMN to explain price momentum, we analyze the properties of PMN. During our sample period from January 1972 through December 1999, the payoffs to the PMN portfolio average a significant 90 basis points per month. These payoffs are not subsumed by the Fama and French (1993) factors or the momentum factor of Carhart (1997). Thus, while the earnings momentum anomaly subsumes the price momentum anomaly, it is not itself subsumed by the price momentum anomaly. The correlation between PMN and the price momentum based portfolio, WML, is 0.66. Also, WML is more volatile than PMN. These results suggest that price momentum is a noisy proxy for earnings momentum. This is consistent with the results in Hong et al. (2003) who examine earnings and price momentum in 11 international equity markets and find that price momentum exists only in those countries in which earnings momentum is profitable.

Using a variety of measures to capture future macroeconomic conditions, we show that the return on PMN forecasts future business conditions. In particular, we find that the return on PMN is correlated with future GDP growth, industrial production growth, consumption growth, labor income growth, inflation, and T-bill returns. These correlations persist even after controlling for the Fama–French factors. These results suggest that the PMN portfolio may be viewed as a risk factor that earns a risk premium.1 However, PMN is negatively related to the business cycle as measured by GDP growth. Portfolios that vary countercyclically with the business cycle should not earn a positive risk premium. Thus, while PMN is related to the business cycle, it is unlikely to proxy for a risk factor. Overall, these results suggest that earnings momentum (or post-earnings-announcement-drift) contains a systematic component related to the macroeconomy, but that this component is unlikely to represent a (macroeconomic) risk factor.2

Chordia and Shivakumar (2005) offer a potential explanation for the systematic component in earnings momentum by showing that earnings momentum, or the post-earnings announcement drift, results from an inflation illusion. The inflation illusion hypothesis, first proposed by Modigliani and Cohn (1979), suggests that while bond market investors correctly anticipate the impact of inflation on discount rates, stock market investors fail to incorporate inflation when forecasting the rate of future earnings growth.3 Thus, when inflation rises, investors do not adjust the future earnings growth rate, even though they fully adjust the discount rates. A direct implication of this hypothesis is that if earnings growth varies across stocks in response to inflation, then an inflation illusion would induce misvaluation in the cross-section. Chordia and Shivakumar (2005) show that the effect of inflation on earnings growth increases monotonically across SUE-sorted portfolios. Due to inflation illusion, stocks with earnings growth positively related to inflation are undervalued, whereas those with earnings growth negatively related to inflation are overvalued. The subsequent correction of this under- and overvaluation drives the post-earnings-announcement-drift.

This paper contributes to the ongoing debate on the sources of profits to price momentum. Several studies suggest that the momentum profits are driven by cognitive biases on the part of investors (e.g., Daniel et al., 1998; Barberis et al., 1998). In contrast, Chordia and Shivakumar (2002), Ahn et al. (2003), and Avramov and Chordia (2005) argue that the price momentum payoffs are related to the business cycle. Korajcyzk and Sadka (2004) argue that the momentum phenomenon persists due to frictions in the price adjustment process that are caused by transactions costs. The finding that price momentum is subsumed by a common factor related to the macroeconomy is significant since it does not rely on capital market frictions to explain the price momentum effect.

This paper narrows the search for an explanation of the price momentum and earnings momentum anomalies by documenting that the price momentum anomaly is a manifestation of the earnings momentum anomaly. That is, the two anomalies that Fama (1998) cites as being above suspicion may, in fact, correspond to the same anomaly, namely, the earnings momentum, or the post-earnings announcement drift, anomaly. Moreover, our results indicate that the price momentum-based factor, WML, in the Carhart (1997) four-factor model is merely a noisy proxy for the earnings momentum-based factor, PMN. This implies that PMN, rather than WML, is the more appropriate factor to use in asset pricing tests. Of course, both PMN and WML are empirically motivated and neither may represent a state variable in the Merton (1973) sense.

The rest of this paper is organized as follows. Section 2 discusses the two momentum strategies, and Section 3 discusses the formation of portfolios that are based on these momentum strategies. Section 4 presents time-series and cross-sectional asset pricing tests. Section 5 presents the properties of PMN and Section 6 analyses the link between PMN and the macroeconomy. Section 7 concludes.

Section snippets

Momentum strategies

As we mention above, the two anomalies that we focus on in this paper are the price momentum and earnings momentum anomalies. The profitability of price momentum strategies, first documented by Jegadeesh and Titman (1993), has been particularly intriguing, as, among all the anomalies examined by Fama and French (1996), it is the only anomaly that is unexplained by the Fama and French (1993) three-factor model. Jegadeesh and Titman (2001) argue that their initial results are not due to data

Zero-investment portfolios

To study the impact of earnings momentum on price momentum, we first create earnings portfolios that capture the post-earnings announcement drift phenomenon. For each month, we sort all NYSE-AMEX firms on the monthly Center for Research in Security Prices (CRSP) files with data on COMPUSTAT into deciles based on their SUE from the most recent earnings announcement.4

Asset pricing tests

To study the relation between earnings- and price-based momentum strategies, we examine whether the systematic component of one strategy fully subsumes payoffs to the other. The primary motivation for our focus on the systematic component are the findings of Chordia and Shivakumar (2002), Ahn et al. (2003), and Avramov and Chordia (2005) that price momentum is related to macroeconomic variables and that it is unrelated to firm-specific news. We implement our tests by extending the Fama–French

Properties of PMN

Table 6 documents seasonality in payoffs to the SUE portfolios P10 and P1 as well as the zero-investment strategy, PMN. The returns on the zero-investment portfolio, PMN, are highest in April, July, October and December. It is positive in all months except in January when it is −1.42%. In the non-January months the average P10−P1 returns is 1.11%. This seasonality in payoffs to PMN is mainly attributable to the low-SUE portfolio P1, for which the average return is 6.17% in January compared to

PMN and the macroeconomy

PMN could be related to the macroeconomy for two reasons. First, PMN could proxy for a risk factor in an intertemporal asset pricing model, such as Merton (1973). In this case, the payoffs to PMN would reflect future macroeconomic activities as these activities contain information about the future investment opportunity set of investors. Liew and Vassalou (2000) use this approach to examine whether the Fama–French factors proxy for risk factors. Alternatively, PMN could reflect mispricing of

Conclusions

Two robust and persistent anomalies over the last four decades that have defied rational explanations are the post-earnings announcement drift, or earnings momentum, and the short-run return continuations, or price momentum. In this paper we ask whether the two are related. A zero-investment portfolio (denoted PMN) that is long the highest earnings surprise portfolio and short the lowest earnings surprise portfolio captures the price momentum phenomenon in time-series and cross-sectional asset

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    We thank an anonymous referee, Ray Ball, Michael Brennan, Greg Clinch, Francisco Gomes, Paul Irvine, Narasimhan Jegadeesh, Josef Lakonishok, Maureen McNichols, Stefan Nagel, Bhaskaran Swaminathan, Jacob Thomas, and seminar participants at Case Western University, London Business School, University of Chicago, University of Rochester, and the LBS accounting symposium for helpful comments. The second author was supported by the Dean's Fund for Research at the London Business School. All errors are our own.

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