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.

We study the economic sources of stock-bond return comovements and their time variation using a dynamic factor model. We identify the economic factors employing a semistructural regime-switching model for state variables such as interest rates, inflation, the output gap, and cash flow growth. We also view risk aversion, uncertainty about inflation and output, and liquidity proxies as additional potential factors. We find that macroeconomic fundamentals contribute little to explaining stock and bond return correlations but that other factors, especially liquidity proxies, play a more important role. The macro factors are still important in fitting bond return volatility, whereas the "variance premium" is critical in explaining stock return volatility. However, the factor model primarily fails in fitting covariances. (JEL G11, G12, G14, E43, E44) Stock and bond returns in the United States display an average correlation of about 19% during the post-1968 period. Shiller and Beltratti (1992) underestimate the empirical correlation using a present value with constant discount rates, whereas Yet, these models generate realistically positive correlations using economic state variables.

We examine aggregate idiosyncratic volatility in 23 developed equity markets, measured using various methodologies. We find no evidence of upward trends after extending the sample to 2008. Instead, idiosyncratic volatility is well described by a stationary autoregressive process that occasionally switches into a higher-variance regime that has relatively short duration. We also document that idiosyncratic volatility is highly correlated across countries. Most of the time variation in idiosyncratic volatility can be attributed to variation in a growth opportunity proxy, total (U.S.) market volatility, and in most specifications, the variance premium, a business cycle sensitive risk indicator.

We propose a cross‐sectional time‐series model to assess the impact of market liberalizations in emerging equity markets on the cost of capital, volatility, beta, and correlation with world market returns. Liberalizations are defined by regulatory changes, the introduction of depositary receipts and country funds, and structural breaks in equity capital flows to the emerging markets. We control for other economic events that might confound the impact of foreign speculators on local equity markets. Across a range of specifications, the cost of capital always decreases after a capital market liberalization with the effect varying between 5 and 75 basis points.

We propose a measure of capital market integration arising from a conditional regime‐switching model. Our measure allows us to describe expected returns in countries that are segmented from world capital markets in one part of the sample and become integrated later in the sample. We find that a number of emerging markets exhibit time‐varying integration. Some markets appear more integrated than one might expect based on prior knowledge of investment restrictions. Other markets appear segmented even though foreigners have relatively free access to their capital markets. While there is a perception that world capital markets have become more integrated, our country‐specific investigation suggests that this is not always the case.

We propose a conditional measure of capital market integration that allows us to characterize both the cross-section and time-series of expected returns in developed and emerging markets.Our measure, which arises from a conditional regime-switching model, allows us to describe expected returns in countries that are segmented from world capital markets in one part of the sample and become integrated later in the sample.Our results suggest that a number of emerging markets exhibit time-varying integration.Interestingly, some markets appear to be more integrated than one might expect based on prior knowledge of investment restrictions.Other markets appear segmented even though foreigners have relatively free access to their capital markets.

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 identify flight-to-safety (FTS) days for twenty-three countries using only stock and bond returns and a model averaging approach. FTS days comprise less than 2% of the sample and are associated with a 2.7% average bond-equity return differential and significant flows out of equity funds and into government bond and money market funds. FTS represents flights to both quality and liquidity in international equity markets, but mainly a flight to quality in the U.S. corporate bond market. Emerging markets, endowment funds, and hedge funds perform poorly during FTS, whereas hedge funds appear to vary their systematic exposures prior to an FTS.

Changes in nominal interest rates must be due to either movements in real interest rates, expected inflation, or the inflation risk premium. We develop a term structure model with regime switches, time‐varying prices of risk, and inflation to identify these components of the nominal yield curve. We find that the unconditional real rate curve in the United States is fairly flat around 1.3%. In one real rate regime, the real term structure is steeply downward sloping. An inflation risk premium that increases with maturity fully accounts for the generally upward sloping nominal term structure.