What Factors Drive Global Stock Returns?
Social Science Research Network
This study seeks to identify which factors are important for explaining the time-series and cross-section variation in global stock returns. We evaluate firm characteristics, like size, earnings/price, cash flow/price, dividend/price, book-to-market equity, leverage, momentum, that have been suggested in the empirical asset pricing literature to be cross-sectionally correlated with average returns in the United States and in developed and emerging markets around the world. For monthly returns
... r monthly returns of 26,000 individual stocks from 49 countries over the 1981 to 2003 period, we perform cross-sectional regression tests of average returns at the individual firm level and we construct factor-mimicking portfolios based on these firm-level characteristics to assess their ability to explain time-series return variation in country, industry and characteristics-sorted portfolios. We find that the momentum and cash flow/price factor-mimicking portfolios, together with a global market risk factor, capture substantial common variation in global stock returns. In addition, the three factors explain the average returns for country and industry portfolios, and a wide variety of single-and double-sorted characteristics-based portfolios. JEL classification: F30, G14, G15. There has been considerable evidence that the cross-section of average returns are related to firm-level characteristics such as size, earnings/price, cash flow/price, dividend/price, book-to-market equity, leverage, momentum both in the United States and in developed and emerging markets around the world. Measured over long sample periods, small stocks earn higher average returns than large stocks (Banz, 1981; show that value stocks with high book-to-market (B/M), earnings-to-price (E/P), or cash-flow-to-price (C/P) ratios outperform growth stocks with low B/M, E/P or C/P ratios. Moreover, stocks with high return over the past 3-to 12-months continue to outperform stocks with poor prior performance ( The interpretation of the evidence is, of course, strongly debated. Some believe that the premiums associated with these characteristics are compensation for pervasive extra-market risk factors, others attribute them to inefficiencies in the way markets incorporate information into prices (among others, Haugen and Baker, 1996; Daniel and Titman, 1997; Daniel, Titman and Wei, 2001). Yet others propose that the premiums are just a manifestation of survivorship or data-snooping biases (Kothari, Shanken and Sloan, 1995; MacKinlay, 1995) . Many of the studies listed above that focus on international markets motivate their efforts as a response to this latter criticism. That is, to the extent that developed or emerging markets move independently from U.S. markets, they provide independent verification of the size, value and momentum premiums. We motivate our study in this same spirit, but we dare to broaden the investigation to over 26,000 stocks from 49 countries using monthly returns over the 1981 to 2003 period to re-examine the size, value and momentum effects. To this end, we take advantage of the breadth and coverage of Thomson Financial's Datastream International and Worldscope databases. We assess a variety of firm attributes (including market capitalization, B/M, E/P, C/P, momentum, dividend yield, and financial leverage) for the cross-section of expected stock returns at the individual firm level. Perhaps more importantly, we seek to identify which factors are important for explaining the common variation in global stock returns. For each of the firm attributes discussed above, we construct a zero-2 investment factor-mimicking portfolio (in the spirit of Huberman, Kandel and Stambaugh, 1987, using the methodology of Fama and French, 1993, and Chan, Karceski and Lakonishok, 1998) by going long in stocks that have high values of an attribute (such as B/M) and short in stocks with low values of the attribute. Examining the returns behavior of the different mimicking portfolios can help us evaluate and interpret the underlying factors (Charoenrook and Conrad, 2005). Finally, we assess the performance of different models combining these factor-mimicking portfolios to capture the time-series variation in a wide variety of characteristics-sorted portfolios and to explain the cross-sectional differences in average returns (Fama and French, 1993, 1996). The identification of the common sources of comovement and, hence, possible sources of portfolio risk in international stock returns is, of course, just as important for investment practitioners as for academic researchers. The popularity of global factor models has grown dramatically in industry with their extensive use for portfolio risk optimization, active-risk budgeting, performance evaluation and style/attribution analysis. In addition to market, currency, macroeconomic and industry-specific risk factors, models such as BARRA's Integrated Global Equity Model (Stefek, 2002; Senechal, 2003 ), Northfield's Global Equity Risk Model (Northfield, 2005), ITG's Global Equity Risk Model (ITG, 2003) and Salomon Smith Barney's Global Equity Risk Management (GRAM, Miller et al., 2002) all include -what are referred to as -"style," "fundamental," "financial-statement ratio," or "bottom-up" factors. They all rationalize their choice of factor model specifications based on the joint goals of robustness and parsimony. What do we find? First, our cross-sectional Fama-MacBeth (1973) tests of individual stock returns confirm the weak relationship between average returns and market betas (measured locally, relative to the national market index, or globally, relative to the world market portfolio, or within industry, relative to the industry portfolio to which a firm belongs). The positive relationship with B/M, momentum, C/P is reliable, but that with size is not. These effects are much stronger in developed countries than emerging markets and especially in the second half of the sample (1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003). Second, we uncover desirable attributes for factormimicking portfolios constructed on the basis of many of the same characteristics that were successful in the cross-sectional analysis. Global factor mimicking portfolios based on B/M, momentum, C/P, and now even size and E/P have statistically significant and appropriately-signed average returns and considerable timeseries variability, comparable to global, industry and country market excess returns. Third, and finally, among the various multifactor models combining these candidate global factor mimicking portfolios, the momentum and C/P factor-mimicking portfolios, together with a global market factor, capture strong common variation in global stock returns. In addition, the three-factor model explains the average returns (using F-tests of Gibbons, Ross and Shanken, 1989) for country and industry portfolios, and even a broad set 1 A number of recent studies use Datastream International due to its broad and deep coverage