We investigate how different components in firm characteristics affect expected returns and comovements in international stock markets. We decompose characteristics into country, industry, and country- and industry-adjusted (i.e., orthogonal) components. Then, we use these components to capture time-series and cross-sectional variations in stock-level alphas and factor exposures. Decomposing characteristics is crucial to explain jointly expected returns and comovements: (i) adjusted (country) components are the most important determinant of alphas (comovements), (ii) component-based models outperform benchmark models, and (iii) alphas are statistically significant. However, alphas have been trending down over time, and alpha-chasing strategies are not profitable once we account for estimation risk and trading costs.

We provide a new methodology to empirically investigate the respective roles of systematic and idiosyncratic skewness in explaining expected stock returns. Using a large number of predictors, we forecast the cross-sectional ranks of systematic and idiosyncratic skewness, which are easier to predict than their actual values. Compared to other measures of ex ante systematic skewness, our forecasts create a significant spread in ex post systematic skewness. A predicted systematic skewness risk factor carries a significant and robust risk premium that ranges from 6% to 12% per year. In contrast, the role of idiosyncratic skewness in pricing stocks is less robust.

The 4 equity market factors from Fama and French (1993) and Carhart (1997) are pervasive in academia and practice. However, not much is known about their joint distribution and dynamics. We find striking evidence of asymmetric tail dependence across the factors. While the linear factor correlations are small and even negative, the extreme correlations are large and positive, so that the linear correlations drastically overstate the benefits of diversification across the factors. We model the nonlinear factor dependence dynamics and explore their economic importance in a portfolio allocation experiment showing that significant economic value is earned when acknowledging nonlinear dependence.

We develop a new global asset pricing model to study how illiquidity interacts with market segmentation and investability constraints in 42 markets. Noninvestable stocks that can only be held by foreign investors earn higher expected returns compared to freely investable stocks due to limited risk sharing and higher illiquidity. In addition to the world market premium, on average, developed and emerging market noninvestables earn an annual unspanned local market risk premium of 1.17% and 9.04%, and a liquidity level premium of 1.06% and 2.39%, respectively. These results obtained in a conditional setup are robust to the choice of liquidity measure.

We characterize dependence in corporate credit and equity returns for 215 firms using a new class of large-scale dynamic copula models. Copula dependence and especially tail dependence are highly variable and persistent, increase significantly in the financial crisis, and have remained high since. The most drastic increases in credit dependence occur in July/August of 2007 and in August of 2011 and the decrease in diversification potential caused by the increases in dependence and tail dependence is large. Credit default swap correlation dynamics are important determinants of credit spreads.