Consensus professional stock return forecasts are three times more volatile than those of non-professionals and econometricians. We show that this difference reflects professionals’ strong countercyclical responses to macro shocks, which explain 20–40% of forecast variation and are consistent with rational asset pricing models in which discount rates rise in bad times. We use macro shocks to identify the discount-rate component of professional forecasts and find that it closely matches realized returns. We conclude that professionals’ assessment of the discount-rate impact of macro shocks distinguishes them from other forecasts, challenging existing models of expectation formation.

We study the horizon dimension of cross-sectional return predictability using a model where characteristics contain both persistent and transitory components. We test the implications of this model for the average returns of popular characteristic-based trading strategies at short versus long horizons after portfolio formation. Our evidence supports the claim that the relative compensation for persistent and transitory components varies across characteristics, in both magnitude and sign. Benchmark factor models cannot explain the returns of portfolios sorted on characteristics where either the persistent or transitory component is dominant. Finally, we discuss implications for the long-term discount rates of firms.

Today’s investors have near-instant access to return data, yet it remains unclear whether they respond to such information and how this shapes asset managers’ incentives. We show that investors react strongly to performance on down-market days but are largely insensitive in up-markets. One bad day moves flows as much as five normal days. These flows efficiently reallocate capital toward funds that outperform on bad days. Bad-day performance is persistent and unrelated to performance on other days, indicating a distinct form of skill. This skill is not explained by timing or derivatives strategies but is instead associated with stronger broker connections.

Consensus professional stock return forecasts are three times more volatile than those of nonprofessionals and econometricians. We show that this difference reflects professionals’ strong countercyclical responses to macro shocks, which explain 20–40% of forecast variation and are consistent with rational asset pricing models in which discount rates rise in bad times. We use macro shocks to identify the discount-rate component of professional forecasts and find that it closely matches realized returns. We conclude that professionals’ assessment of the discount-rate impact of macro shocks distinguishes them from other forecasts, challenging existing models of expectation formation.

We classify asset pricing anomalies into those exacerbating mispricing (build-up anomalies) and those resolving it (resolution anomalies). We estimate the dynamics of price wedges for well-known anomaly portfolios and map them to firm-level mispricings. We find that several prominent anomalies like momentum and profitability further dislocate prices. Multi-factor models designed to eliminate one-month alphas still produce large price wedges. Our estimates yield a novel decomposition of Tobin’s q, revealing that q’s mispricing component has substantial explanatory power for firm investment. Overall, our results suggest that financial intermediaries chasing build-up anomalies negatively affect price efficiency and associated real capital allocation.

ABSTRACTThe response of corporate bond credit spreads to three exogenous macro shocks—oil supply, investment‐specific technology, and government spending—is large, significant, and a mirror image of macroeconomic activity. This countercyclicality is driven largely by credit risk premia and translates into significant return predictability. Equity risk premia exhibit similar responses, providing external validity. Information rigidities and leverage play a key role in the transmission of the shocks. Since causal evidence linking macro shocks to credit markets is scarce and recent work highlights the real effects of credit fluctuations, our findings contribute to understanding the joint dynamics of credit markets and the macroeconomy.

We study how macroeconomic developments affect asset prices by analyzing the response of equity yields to a well-identified long-run growth shock. Using synthetic equity yield data from Giglio et al. (2024), we show that a positive long-run shock steepens the equity yield curve by increasing expected dividend growth while leaving discount rates largely unchanged. We examine how the investment driving this growth is financed and how yields respond across value and growth firms. Growth-firm yields respond more strongly than value-firm yields, reflecting larger changes in expected dividend growth. Ai et al. (2018)’s model, modified to separate cash dividends from total payout, best matches these responses relative to benchmark equity term structure models.

We study a large set of macroeconomic announcements (MAs), disentangle their news content, and estimate risk premia for each type of news in the cross-section of stocks. Our most interesting finding is that a portfolio that pays off around MAs that negatively impact the stock market commands a large and positive risk premium. Adding this portfolio to a position in the stock market substantially increases the Sharpe ratio, while reducing price impact exposure to MAs. We argue that this portfolio is risky, consistent with models of reinvestment risk. Our findings challenge equilibrium models predicting a negative relation between shocks to discount rates and marginal utility as well as stories of cash flow news arriving on MA days.

We show that returns to value strategies in individual equities, industries, commodities, currencies, global government bonds, and global stock indexes are predictable in the time series by their respective value spreads. In all these asset classes, expected value returns vary by at least as much as their unconditional level. A single common component of the value spreads captures about two-thirds of value return predictability and the remainder is asset class specific. We argue that common variation in value premia is consistent with rationally time-varying expected returns, because (i) common value is closely associated with standard proxies for risk premia, such as the dividend yield, intermediary leverage, and illiquidity, and (ii) value premia are globally high in bad times.

We study the horizon-dimension of cross-sectional return predictability through the lens of a model where characteristics contain persistent and transitory components. We test the implications of this model for the average returns of popular characteristic-based trading strategies at short versus long horizons after portfolio formation. Our evidence supports the claim that the relative compensation for persistent and transitory components varies across characteristics, in magnitude and sign. Benchmark factor models cannot explain the returns of portfolios sorted on characteristics where either the persistent or transitory component is dominant. Finally, we model and test implications for firms' long-term discount rates.

We show that inflation risk is priced in stock returns and that inflation risk premia in the cross-section and the aggregate market vary over time, even changing sign as in the early 2000s. This time variation is due to both price and quantities of inflation risk changing over time. Using a consumption-based asset pricing model, we argue that inflation risk is priced because inflation predicts real consumption growth. The historical changes in this predictability and in stocks' inflation betas can account for the size, variability, predictability and sign reversals in inflation risk premia.

We introduce a return predictor related to the slope and curvature of the futures term structure: basis-momentum. Basis-momentum strongly outperforms benchmark characteristics in predicting commodity spot and term premiums in the time series and cross section. Exposure to basis-momentum is priced among commodity-sorted portfolios and individual commodities. We argue that basis-momentum captures imbalances in the supply and demand of futures contracts that materialize when the market-clearing ability of speculators and intermediaries is impaired, and that basis-momentum represents compensation for priced risk. Our findings are inconsistent with alternative explanations based on storage, inventory, and hedging pressure.

We find that the relation between state variables, such as the t-bill rate and term spread, and consumption growth is time-varying. In the cross-section of U.S. stocks, risk premia for exposure to state variables vary over time accordingly. When a state variable predicts consumption strongly relative to its own history, its annualized risk premium increases by 6% (0.4 in Sharpe ratio). This effect implies that risk premia can switch signs and are increasing in the conditional variance of the state variable. These common drivers of time-varying risk premia are consistent with the Intertemporal CAPM. Benchmark factors contain the same conditional expected return effects as state variable risk premia.

I study whether risk premiums for exposure to state variables in the cross-section of individual stocks are consistent with how these variables forecast macroeconomic activity in the time-series. I find such time-series and cross-sectional consistency. This finding suggests that investors are ultimately concerned about business cycle risk and therefore require a premium for exposure to variables that contain systematic economic news. This finding challenges recent portfolio-level evidence showing that state variable risk premiums are inconsistent with hedging incentives in the ICAPM. Moreover, state variable risk premiums are not fully captured by the factors and characteristics of Fama and French (1992, 1993).

The dissertation consists of three essays in asset pricing. Chapter I is motivated by the recent surge in institutional investment in commodity futures markets. The chapter studies how commodity risk is priced in stock and futures markets and asks whether this risk premium is time-varying with these changes in investment practices. Chapter II and III are at the intersection of macroeconomics and asset pricing. Chapter II is motivated by the introduction of real bonds as well as the poor empirical track record for inflation as a risk factor in stock returns. The chapter estimates the inflation risk premium in the stock market and identifies the proximate causes of its variation over time. Chapter III tests an element that is common to most asset pricing models, but often overlooked in empirical tests: time-series and cross-sectional consistency. The chapter studies whether risk premiums for state variable risks in the cross-section of individual stocks are consistent with how these variables predict macroeconomic activity in the time-series. The dissertation resuscitates a central role for real factors in asset pricing and identifies a novel channel through which stock market risk premiums vary over time: the introduction of an asset that hedges the underlying risk more adequately.

We show that decomposing macroeconomic risks across horizon is key to uncover a tight link between risk premia and the real economy. Exposure in four-year returns to innovations in macroeconomic growth and volatility with a matching half-life of over four years is priced in a wide variety of test assets. Shorter-term risks are not priced. Importantly, we show that long-term growth and volatility capture largely common risk. We then propose a single, long-term, macroeconomic risk factor which drives out standard long-run risk measures and performs similar to the Fama-French three-factor model in cross-sectional tests. Our empirical results strongly support the use of long-horizon betas to measure macroeconomic risks in asset returns.

We show that inflation risk is priced in the cross section of U.S. stock returns. The inflation risk premium varies over time conditional on the nominal-real covariance—the time-varying relation between inflation and the real economy. Using a consumption-based equilibrium asset pricing model, we argue that inflation is priced because it predicts real consumption growth. The historical changes in the predictability of consumption with inflation, which are mediated by the nominal-real covariance, can account for the size, variability, predictability, and sign-reversals— last observed in the 2000s—in the inflation risk premium.