The CAPM, National Stock Market Betas, and Macroeconomic Covariates: a Global Analysis


Using global data on aggregate stock markets, this paper finds that the capital asset pricing model fares much better than suggested previously. At shorter time horizons, our results also show that the positive risk-reward relation can collapse during times of high volatility. Compared to other countries, we retrieve evidence of lower systematic risks across frontier equity portfolios. We find that countries characterized by higher levels of openness, exchange rate volatility, and larger economic size are exposed to higher systematic covariances with the world stock market. Conversely, we obtain an inverse link between international reserves and systematic risks in national equity.

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Fig. 1

Notes: * significant at 10%; ** significant at 5%; *** significant at 1%. MXWD (MSCI ACWI) is used as the world stock market portfolio. Red circles represent equity while green squares represent long-term government debt

Fig. 2

Notes: * significant at 10%; ** significant at 5%; *** significant at 1%. MXWO is used as the world stock market portfolio. Red circles represent equity while green squares represent long-term government debt

Fig. 3

Notes: Sample consists of developed national stock markets. Global portfolio employed is the MSCI All Country World Index (MXWD). Security market line (SML) plotted is both the empirical and theoretical one. SML has a slope of 0.004, consistent with the average monthly excess return on the world portfolio over the period. When national stock market beta is equal to 0, SML shows an average monthly return equal to 0.001, consistent with the average risk-free rate over the period

Fig. 4

Notes: * significant at 10%; ** significant at 5%; *** significant at 1%. MXWD (MSCI ACWI) is used as the world stock market portfolio for the period 1988-2017. MXWO proxies for the world stock market over the period 1968-1987. Red circles represent equity while green squares represent long-term government debt

Fig. 5

Notes: The horizontal axis marks the end of each 5-year period. The red dashed line marks the average return volatility over the entire sample period

Fig. 6

Notes: Blue circles, red squares, and green triangles correspond to developed, emerging, and frontier stock markets respectively. Annualized figures are shown

Fig. 7

Notes: Blue circles, red squares, and green triangles correspond to developed, emerging, and frontier stock markets respectively. The horizontal axis marks the final year of each non-overlapping 5-year period. Jensen’s alpha is the average return on the national stock market portfolio over and above that predicted by the CAPM

Fig. 8

Notes: Blue circles, red squares, and green triangles correspond to developed, emerging, and frontier stock markets respectively. 5-year alphas and betas are employed. Jensen’s alpha is the average return on the national stock market portfolio over and above that predicted by the CAPM. Parametric and non-parametric correlations between alpha and beta are close to zero


  1. 1.

    Early studies employed short samples with a handful of advanced economies to investigate the investment behavior of citizens of one country when facing an expanded international investment opportunity set or gains from international diversification (Grubel 1968; Lee 1969; Levy and Sarnat 1970; Miller and Whitman 1970; Grubel and Fadner 1971; Solnik 1974, 1977). The subsequent literature diverged by looking at differences in consumption profiles, multifactor models, conditional CAPM, and other variants (Korajczyk and Viallet 1989; Harvey 1991; Dumas and Solnik 1995). Tests were mostly inconclusive.

  2. 2.

    We confine our analysis to the traditional CAPM alone, as multi-factor models (i.e. augmented CAPMs) are known to diminish the dispersion in market portfolio betas, pushing them toward unity (Ahn et al. 2013; Fama and French 1992, 1996, 2015). Conditional CAPM estimation is also not feasible in our study given our data.

  3. 3.

    Alpha is the return above that predicted by the CAPM.

  4. 4.

    According to Pentecöte et al. (2015), new trade flows (extensive margin) tend to strengthen specialization and the decoupling of business cycles across countries.

  5. 5.

    This materializes unless there are significant cross-border (intermediate) input-output linkages running over heterogeneous industries. In this latter scenario, comovements are induced by countries using foreign heterogeneous goods as intermediate inputs in their sector of specialization.

  6. 6.

    Following Fama and MacBeth (1973), we also estimate month-by-month and year-by-year cross-section regressions, obtaining time series means of the intercepts and slopes for testing. This approach yielded similar results. Results are robust to Shanken correction and GMM approach to estimation.

  7. 7.

    See MSCI methodology for construction details.

  8. 8.

    Parametric Pearson correlations are similar.

  9. 9.

    The annualized rate is approximately 5 percent.

  10. 10.

    Gross rank correlation coefficient of -0.20 that is statistically significant at the 10 percent level.

  11. 11.

    Quite similar patterns are found over the shorter interval 1988-2017 too.

  12. 12.

    That is, Jensen’s alpha can be obtained as the intercept from time series regression (2).

  13. 13.

    Qualitatively, in a less refined preliminary approach, non-parametric gross (unconditional) correlation coefficients over the cross section mostly yielded similar results.

  14. 14.

    Economies in which it is easier to conduct business, as a result of greater political stability or less rigid regulation for example, are expected to have more pronounced global ties through higher levels of international portfolio investment, foreign direct investment etc. Importantly, better business environments are more conducive to success among domestic firms, that, building on their foundations, can go on to compete on the world stage with their exports. Over the cross section, we find a strong positive relation between market betas and ease-of-doing business rankings.


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Correspondence to Adnan Velic.

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We thank John Burger, Charles Calomiris, Scott Dressler, Vahagn Galstyan, Erasmus Kersting, George Tavlas, and two anonymous referees for very helpful comments and suggestions. Ryan Zalla, Bernard Zaritsky, Riley McCarten, Yanyao Shi, Ibrahim Annabi, and Rashaad Robinson provided diligent research assistance.

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Curran, M., Velic, A. The CAPM, National Stock Market Betas, and Macroeconomic Covariates: a Global Analysis. Open Econ Rev 31, 787–820 (2020).

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  • Portfolios
  • Stock market
  • Cross-country
  • Systematic risk
  • Capital asset pricing model
  • Macroeconomic covariates

JEL Classification

  • F30
  • F31
  • F41
  • G15