We examine the efficiency of using individual stocks or portfolios as base assets to test asset pricing models using cross-sectional data. The literature has argued that creating portfolios reduces idiosyncratic volatility and allows more precise estimates of factor loadings, and consequently risk premia. We show analytically and empirically that smaller standard errors of portfolio beta estimates do not lead to smaller standard errors of cross-sectional coefficient estimates. Factor risk premia standard errors are determined by the cross-sectional distributions of factor loadings and residual risk. Portfolios destroy information by shrinking the dispersion of betas, leading to larger standard errors.

Based on intraday data for a large cross section of individual stocks and newly developed econometric procedures, we decompose the realized variation for each of the stocks into separate so-called realized up and down semi-variance measures, or “good” and “bad” volatilities, associated with positive and negative high-frequency price increments, respectively. Sorting the individual stocks into portfolios based on their normalized good minus bad volatilities results in economically large and highly statistically significant differences in the subsequent portfolio returns. These differences remain significant after controlling for other firm characteristics and explanatory variables previously associated with the cross section of expected stock returns.

In this paper we present empirical tests of an extended version of the capital asset pricing model (CAPM) that replaces the single-period horizon with a probability distribution over different horizons. Adopting a simple parameterization of the probability distribution of the length of the horizon, we estimate the parameters of the distribution as well as the parameters of the CAPM. We find that the extended model is not rejected for several different samples of common stocks, and for these samples it outperforms not only the standard CAPM but also the Fama–French (1993) 3-factor model. The probability distribution over horizon dates varies over time with the New York Stock Exchange (NYSE) turnover rate. We also find that returns satisfy the Euler equation of a representative financial institution that holds the market portfolio and has horizon probabilities estimated from 13F filings.

We estimate a model for the term structure of discounted risk-adjusted dividend growth using prices of dividend futures for the Eurostoxx 50. A 2-factor model capturing short-term mean reversion within a year and a medium-term component reverting at the business-cycle horizon gives an excellent fit of these prices. Hence, investors update the valuation of dividends beyond the business cycle only to a limited degree. The 2-factor model, estimated on dividend futures data only, explains a large part of observed daily stock market returns. We also show that the 2 latent factors are related to various economic and financial variables.

We estimate Moody’s preference for accurate versus biased ratings using hand-collected data on the internal labor market outcomes of its analysts. We find that accurate analysts are more likely to be promoted and less likely to depart. The opposite is true for analysts who downgrade more frequently, who assign ratings below those predicted by a ratings model, and whose downgrades are associated with large negative market reactions. Downgraded firms are also more likely to be assigned a new analyst. These patterns are consistent with Moody’s balancing its desire for accuracy against its corporate clients’ desire for higher ratings.

We document significant differences in the financing structures of small firms with managers of diverse cultural backgrounds. To isolate the effect of culture, we exploit cultural heterogeneity within a geographical area with shared regulations, institutions, and macroeconomic cycles. Our findings suggest significant cultural differences in the preference toward debt funding and in the use of formal and informal sources of financing (bank loans and trade credit). Our results are robust to alternative explanations based on potential differences in credit constraints and in the distribution of cultural origins across industries, trading partners, and headquarters locations.

We examine investors’ preference for directors serving on fewer versus more boards (“busy directors”) by measuring market reaction to busy directors’ resignations at the companies that still keep these directors on the board. We find a positive reaction implying a preference for fewer directorships. The reaction is more positive when the need for the director’s services is greater, when the resignation frees up more of the director’s time, and when the director is of higher quality. Furthermore, we find that following their resignation, directors increase their board responsibilities/leadership at firms that still retain them and seek no board appointments elsewhere.

This study investigates the implications of cross-country differences in banking regulation and supervision for the international subsidiary locations and risk of U.S. bank holding companies (BHCs). We find that BHCs are more likely to operate subsidiaries in countries with weaker regulation and supervision and that such location decisions are associated with elevated BHC risk and higher contribution to systemic risk. The quality of BHCs’ internal controls and risk management plays an important role in these location choices and risk outcomes. Overall, our study suggests that U.S. banking organizations engage in cross-country regulatory arbitrage, with potentially adverse consequences.

We hypothesize that political activism is valuable because it helps reduce political uncertainty, which, in turn, fosters firm innovation. We find that firms that support more politicians, winning politicians, politicians on congressional committees with jurisdictional authority over the firms’ industries, and politicians who join those committees innovate more. We employ a natural experiment to show a causal effect of political activism on innovation. We also show evidence of intra-industry and geographical political activism spillovers.

We analyze the relation between expected option returns and the volatility of the underlying securities. The expected return from holding a call (put) option is a decreasing (increasing) function of the volatility of the underlying. These predictions are supported by the data. In the cross section of equity option returns, returns on call (put) option portfolios decrease (increase) with underlying stock volatility. This finding is not due to cross-sectional variation in expected stock returns. It holds in various option samples with different maturities and moneyness, and is robust to alternative measures of underlying volatility and different weighting methods.