We use non-Gaussian features in U.S. macroeconomic data to identify aggregate supply and demand shocks while imposing minimal economic assumptions. Macro risks represent the variables that govern the time-varying variance, skewness, and higher-order moments of these two shocks, with ”good” (”bad”) variance associated with positive (negative) skewness. We document that macro risks significantly contribute to the variation of yields and risk premiums for nominal bonds. While overall bond risk premiums are countercyclical, an increase in aggregate demand variance significantly lowers risk premiums. Macro risks also significantly predict future realized bond return variances.

Drawing on a novel database of the 401(k) plans of 296 firms, we examine the international equity allocations of 3.8 million individuals over the 2005–2011 period. We find enormous cross-individual variation, ranging from zero to more than 75%, and strong cohort effects, with younger cohorts investing more internationally than older ones and each cohort investing more internationally over time. Access to financial advice, lower fees, and more international fund choices are associated with higher international allocations, suggesting a role for plan design and policy. Education, financial literacy, and the fraction of foreign-born population in the ZIP code also have positive effects on international diversification, consistent with explanations based on familiarity bias and information barriers.

Understanding volatility in emerging capital markets is important for determining the cost of capital and for evaluating direct investment and asset allocation decisions. We provide an approach that allows the relative importance of world and local information to change through time in both the expected returns and conditional variance processes. Our time-series and cross-sectional models analyze the reasons that volatility is different across emerging markets, particularly with respect to the timing of capital market reforms. We find that capital market liberalizations often increase the correlation between local market returns and the world market but do not drive up local market volatility.

We identify the relative importance of changes in the conditional variance of fundamentals (which we call “uncertainty”) and changes in risk aversion in the determination of the term structure, equity prices, and risk premiums. Theoretically, we introduce persistent time-varying uncertainty about the fundamentals in an external habit model. The model matches the dynamics of dividend and consumption growth, including their volatility dynamics and many salient asset market phenomena. While the variation in price–dividend ratios and the equity risk premium is primarily driven by risk aversion, uncertainty plays a large role in the term structure and is the driver of countercyclical volatility of asset returns.

Regulatory changes that appear comprehensive will have little impact on the functioning of a developing market if they fail to lead to foreign portfolio inflows. We specify a reduced-form model for a number of financial time series and search for a common, endogenous break in the data generating process. We also estimate a confidence interval for the break. Our endogenous break dates are accurately estimated but do not always correspond closely to dates of official capital market reforms. Indeed, the endogenous dates are usually later than official dates, highlighting the important distinction between market liberalization and market integration.

We document extreme bias and dispersion in the small-sample distributions of four standard regression-based tests of the expectations hypothesis of the term structure of interest rates. The biases arise because of the extreme persistence in short interest rates. We derive approximate analytic expressions for the biases under a simple first-order autoregressive data generating process for the short rate. We then conduct Monte Carlo experiments based on a bias-adjusted first-order autoregressive process for the short rate and for a more realistic bias-adjusted VAR-GARCH model incorporating the short rate and three term spreads. Conducting inference with the small-sample distributions of test statistics rather than with their asymptotic distributions provides a more consistent rejection of the expectations hypothesis. Plausible sources of measurement error in short and long yields do not salvage the expectations hypothesis.

We use close to 80 million daily returns for more than 19,000 CRSP listed firms to establish the best forecasting model for realized idiosyncratic variances. Comparing forecasts from multiple models, we find that the popular martingale model performs worst. Using the root-mean-squared-error (RMSE) to judge model performance, ARMA(1,1) models perform the best for about 46% of the firms in out-of-sample tests. The ARMA(1,1) model delivers an average RMSE that is statistically significantly lower than all alternative models, and also performs well when not the very best. Its forecasts reverse large, unexpected shocks to realized variances. When using this model to revisit the relation between idiosyncratic risk and returns (the IVOL puzzle), we fail to find a significant relation. The IVOL puzzle is closely connected to a very small set of observations where the martingale forecast over-predicts the future realized variance. These extreme observations are correlated with well-known firm characteristics associated with the IVOL puzzle such as poor liquidity as measured by high bid-ask spreads and the “MAX” effect.

We provide a formal treatment of both static and dynamic portfolio choice using the Disappointment Aversion preferences of Gul (1991. Econometrica 59(3), 667–686), which imply asymmetric aversion to gains versus losses. Our dynamic formulation nests the standard CRRA asset allocation problem as a special case. Using realistic data generating processes, we find reasonable equity portfolio allocations for disappointment averse investors with utility functions exhibiting low curvature. Moderate variation in parameters can robustly generate substantial cross-sectional variation in portfolio holdings, including optimal non-participation in the stock market.

We use industry valuation differentials across European countries to study the impact of membership in the European Union as well as the Eurozone on both economic and financial integration. In integrated markets, discount rates and expected growth opportunities should be similar within one industry, irrespective of the country, implying narrowing valuation differentials as countries become more integrated. Our analysis of the 1990–2007 period shows that membership in the EU significantly lowered discount rate and expected earnings growth differentials across countries. In contrast, the adoption of the Euro was not associated with increased integration. Our results do not change when the sample is extended to include the recent crisis period.