International price and earnings momentum

Abstract

In this paper, we find that price and earnings momentum are pervasive features of international equity markets even when controlling for data-snooping biases. For Europe, we show price momentum to be subsumed by earnings momentum on an aggregate level. However, this rationale can hardly be sustained on a country level. Also, the above explanation is confined to certain time periods in the USA. Since we cannot establish a decent relation between momentum and macroeconomic risks, we suspect a behavior-based explanation to be at work. In fact, we find momentum profits to be more pronounced for portfolios characterized by higher information uncertainty. Hence, the momentum anomaly may well be rationalized in a model of investors underreacting to fundamental news. Finally, we find that momentum works better when limited to stocks with high idiosyncratic risk or higher illiquidity, suggesting that limits to arbitrage deter rational investors from exploiting the anomaly.

Keywords:

• earnings momentum
• price momentum
• market efficiency
• multiple hypothesis testing
• information uncertainty
• liquidity

JEL Classification :

• G11
• G12
• G14
• M40

Acknowledgements

We are grateful to Chris Adcock (the editor), two anonymous referees, Yakov Amihud, Frederick Barnard, Wolfgang Bessler, Markus Brechtmann, Andrea Buraschi, Lara Cathcart, Giulio Cifarelli, Michael Damm, Werner De Bondt, Allaudeen Hameed, Dieter Hess, Alexander Kempf, Joëlle Miffre, Thorsten Neumann, Theo Nijman, Christos Pantzalis, Bernd Scherer, James Sefton, Richard Stehle, Michael Wolf, Zaher Zantout, and the seminar participants at the 2008 CFS Research Conference on Asset Management and International Capital Markets in Frankfurt, the 2008 FMA European Conference in Prague, the 2008 EFMA Annual Meeting in Athens, the Third Conference on Advances in the Analysis of Hedge Fund Strategies at Imperial College, the Econometrics Seminar at the University of Zurich, the CFR Research Seminar at the University of Cologne, the 2008 London Quant Group Conference in Cambridge, and the INQUIRE Spring Seminar 2010 in Rome for their helpful comments and suggestions. Note that this paper expresses the authors’ views that do not have to coincide with those of Deka Investment. The authors acknowledge the financial support of INQUIRE Europe and the Swiss National Science Foundation (NCCR FINRISK).

Notes

See Lo and MacKinlay (1990), Sullivan, Timmermann and White (1999), and White (2000).

Lohre (2008).

In fact, according to an employee of Thomson Financial Services, the return time series is constantly screened for possible glitches in the price, dividend, and adjustment factor history. In particular, the history of several US OTC stocks has been fixed recently, which presumably accounted for a lot of issues detected by Ince and Porter (2006).

Note that we are using quintile instead of decile portfolios.

A recent paper of Asness, Moskowitz, and Pedersen (2009) examined price momentum in Europe for a sample period similar to the one used in this paper. They reported an average annual return of 10.3%, which is slightly lower than the annualized return pertaining to our strategy, 13.3%. However, Asness, Moskowitz, and Pedersen (2009) focused on a significantly smaller universe of companies by using 37.5% largest companies in their construction of momentum portfolios. They noted that ‘including the less liquid but tradable securities in our universe improves the performance of our strategies noticeably’.

For details on the construction of European Fama–French factors, we refer the reader to Schrimpf (2011).

For an overview, see [Lehmann and Romano 2005, Chapter 9].

Using the stationary bootstrap with an average block size of six months leaves the results virtually unchanged.

Note that we recovered Chordia and Shivakumar (2006)’s result using analysts’ revision data instead of quarterly earnings data.

In unreported results, we substantiate this observation by means of a structural break test. Such a structural break seems rational given that it obtains in a period in which new regulations with regard to transparency and openness of analyst recommendations have been introduced (see Kadan et al. 2009).

We have obtained similar results using macroeconomic variables other than GDP growth such as real consumption growth, total industrial production, inflation, and 12-month-ahead treasury bill returns. For brevity, we do not report these results, but they are available upon request.

For the remaining countries, the average number of stocks used for the price momentum strategies ranges from 17 (Italy) to 503 (the USA). As for earnings momentum, the ranges is from 14 (Italy) to 438 (the USA).

See Arena, Haggard, and Yan (2008) for price momentum and Mendenhall (2004) for the post-earnings announcement drift.

Among the chosen liquidity metrics, dollar volume is hardly used in prior studies. It suffers from being unscaled and is thus highly correlated with size.

Note that while the first three measures only take into account the stock's liquidity over the precedent month, the Liu measure hinges on data of the preceding year.

For the remaining countries, the average number of stocks used for the price momentum strategies ranges from 21 (Italy) to 534 (Europe). As for earnings momentum, the range is from 21 (Italy) to 545 (Europe).