We propose a theory in which each stock's environmental, social, and governance (ESG) score plays two roles: (1) providing information about firm fundamentals and (2) affecting investor preferences. The solution to the investor's portfolio problem is characterized by an ESG-efficient frontier, showing the highest attainable Sharpe ratio for each ESG level. The corresponding portfolios satisfy four-fund separation. Equilibrium asset prices are determined by an ESG-adjusted capital asset pricing model, showing when ESG raises or lowers the required return. Combining several large data sets, we compute the empirical ESG-efficient frontier and show the costs and benefits of responsible investing. Finally, we test our theory's predictions using proxies for E (carbon emissions), S, G, and overall ESG.

We model the demand-pressure effect on prices when options cannot be perfectly hedged. The model shows that demand pressure in one option contract increases its price by an amount proportional to the variance of the unhedgeable part of the option. Similarly, the demand pressure increases the price of any other option by an amount proportional to the covariance of their unhedgeable parts.

We study three cases in which specialized arbitrageurs lost significant amounts of capital and, as a result, became liquidity demanders rather than providers. The effects on security markets were large and persistent: Prices dropped relative to fundamentals and the rebound took months. While multi-strategy hedge funds who were not capital constrained increased their positions, a large fraction of these funds actually acted as net sellers consistent with the view that information barriers within a firm (not just relative to outside investors) can lead to capital constraints for trading desks with mark-to-market losses. Our findings suggest that real world frictions impede arbitrage capital.

We document significant “time series momentum” in equity index, currency, commodity, and bond futures for each of the 58 liquid instruments we consider. We find persistence in returns for one to 12 months that partially reverses over longer horizons, consistent with sentiment theories of initial under-reaction and delayed over-reaction. A diversified portfolio of time series momentum strategies across all asset classes delivers substantial abnormal returns with little exposure to standard asset pricing factors and performs best during extreme markets. Examining the trading activities of speculators and hedgers, we find that speculators profit from time series momentum at the expense of hedgers.

This paper examines whether capital structure is irrelevant for enterprise value and investment when investors care about environmental, social, and governance issues, which we refer to as “ESG-Modigliani-Miller” (ESG-MM). Theoretically, we show that ESG-MM holds with linear pricing and additive ESG. ESG-MM means that issuing low-yielding green bonds does not lower the overall cost of capital because it makes the issuer’s other securities browner. Hence, a firm’s incentive to make a green investment does not depend on its financing choice. We provide suggestive evidence of failure of ESG-MM, implying that firms and governments can exploit inconsistent ESG attribution or segmented markets.

Based on high-frequency data for more than fifty commodities, currencies, equity indices, and fixed-income instruments spanning more than two decades, we document strong similarities in realized volatility patterns within and across asset classes. Exploiting these similarities through panel-based estimation of new realized volatility models results in superior out-of-sample risk forecasts, compared to forecasts from existing models and conventional procedures that do not incorporate the similarities in volatilities. We develop a utility-based framework for evaluating risk models that shows significant economic gains from our new risk model. Lastly, we evaluate the effects of transaction costs and trading speed in implementing different risk models.Received March 7, 2016; editorial decision February 3, 2018 by Editor Andrew Karolyi.

We find consistent value and momentum return premia across eight diverse markets and asset classes, and a strong common factor structure among their returns. Value and momentum returns correlate more strongly across asset classes than passive exposures to the asset classes, but value and momentum are negatively correlated with each other, both within and across asset classes. Our results indicate the presence of common global risks that we characterize with a three‐factor model. Global funding liquidity risk is a partial source of these patterns, which are identifiable only when examining value and momentum jointly across markets. Our findings present a challenge to existing behavioral, institutional, and rational asset pricing theories that largely focus on U.S. equities.

We provide the impact on asset prices of search-and-bargaining frictions in over-the-counter markets. Under certain conditions, illiquidity discounts are higher when counterparties are harder to find, when sellers have less bargaining power, when the fraction of qualified owners is smaller, or when risk aversion, volatility, or hedging demand is larger. Supply shocks cause prices to jump, and then “recover” over time, with a time signature that is exaggerated by search frictions: The price jump is larger and the recovery is slower in less liquid markets. We discuss a variety of empirical implications.

This chapter introduces the institutional setting of over-the-counter (OTC) markets and raises some of the key conceptual issues associated with market opaqueness. An OTC market does not use a centralized trading mechanism, such as an auction, specialist, or limit-order book, to aggregate bids and offers and to allocate trades. Instead, buyers and sellers negotiate terms privately, often in ignorance of the prices currently available from other potential counterparties and with limited knowledge of trades recently negotiated elsewhere in the market. OTC markets are thus said to be relatively opaque; investors are somewhat in the dark about the most attractive available terms and about whom to contact for attractive terms. Prices and allocations in OTC markets are, to varying extents, influenced by opaqueness and by the role of intermediating brokers and dealers.

We characterize when physical probabilities, marginal utilities, and the discount rate can be recovered from observed state prices for several future time periods. We make no assumptions of the probability distribution, thus generalizing the time-homogeneous stationary model of Ross (2015). Recovery is feasible when the number of maturities with observable prices is higher than the number of states of the economy (or the number of parameters characterizing the pricing kernel). When recovery is feasible, our model allows a closed-form linearized solution. We implement our model empirically, testing the predictive power of the recovered expected return and other recovered statistics.