Knowledge that Transforms

We study the influence of bounded rationality on companies’ disclosure to investors in new industries. Using a historical example of a new industry, we document that several companies initially withheld their earnings, despite external capital needs and investor information demands. However, almost all these companies started disclosing shortly thereafter. Interpreted through the lens of a disclosure model featuring level-$ k $ thinking, these patterns suggest that limited strategic thinking of some companies contributed to the initial failure to disclose, while feedback and learning over time contributed to the quick convergence to an equilibrium of (almost) full disclosure in the new industry.

We present a novel methodology for the out-of-sample forecast of the equity premium. Our predictive slope coefficient is a conservative constant that has a lower bias than the zero slope employed by the historical average, but has the same variance. We demonstrate that, theoretically and empirically, our method dominates the historical average in forecast performance. Our methodology establishes a simple yet powerful paradigm for exploiting the real-time equity premium predictability derived from a predictor. Applications of our method reveal that many predictors can forecast the equity premium, and that parameter estimates in previous studies add value to out-of-sample forecasts.

This paper examines how physical climate exposure affects firm performance and global supply chains. We document that heat at supplier locations reduces the operating income of suppliers and their customers. Further, customers respond to perceived changes in suppliers’ exposure: when suppliers’ realized exposure exceeds ex ante expectations, customers are 7% more likely to terminate supplier relationships. Consistent with experience-based learning, this effect increases with signal strength and repetition and decreases with country-level climate adaptation. Subsequent replacement suppliers show a lower expected and realized but similar projected heat exposure. We find similar results for suppliers’ exposure to floods.

Collecting large asset managers’ capital market assumptions, we revisit the relationships between subjective equity premium expectations, equity valuations, and financial portfolios. In contrast to the well-documented extrapolative expectations of retail investors, asset managers’ equity premium expectations are countercyclical: they are high (low) when valuations are low (high). We find that asset managers’ portfolios reflect their heterogeneous expectations: allocation funds of asset managers with larger U.S. equity premium expectations invest significantly more in U.S. equities. The sensitivity of portfolios to expectations seems to be muted by investment mandates and is smaller than the one predicted by a standard portfolio choice model.

Changes in the propagation of shocks along firm networks are important to understanding aggregate and cross-sectional features of stock returns. When calibrated to match key characteristics of supplier–customer networks in the United States, a model in which firms are interlinked via enduring relationships generates long-run consumption risks, high and volatile risk premiums, and a small and stable risk-free rate. The model also matches cross-sectional patterns of portfolio returns sorted by firm centrality, a feature unaccounted for by standard asset pricing models.

We show that larger trades incur lower trading costs in government bond markets (“size discount”), but costs increase in trade size after controlling for client identity (“size penalty”). The size discount is driven by the cross-client variation of larger traders obtaining better prices, consistent with theories of trading with imperfect competition. The size penalty, driven by the within-client variation, is larger for corporate bonds, during major macroeconomic surprises and during COVID-19. These differences are larger among more sophisticated clients, consistent with information-based theories.

We study a large currency cross-section using asset pricing methods that account for omitted-variable and measurement-error biases. First, we show that the pricing kernel includes at least three latent factors that resemble (but are not identical to) a strong U.S. “dollar” factor and two weak high Sharpe ratio “carry” and “momentum” slope factors. Evidence for an additional “value” factor is weaker. Second, using this pricing kernel, we find that only a small fraction of the over 100 nontradable candidate factors considered have a statistically significant risk premium, mostly relating to volatility, uncertainty, and liquidity conditions, rather than macro variables.

We analyze the distributional effects of macroprudential policy on mortgage cycles by exploiting the U.K. mortgage register and a 2014 15% limit imposed on lenders’ high loan-to-income (LTI) mortgages. Constrained lenders issue fewer and more expensive high-LTI mortgages, with stronger effects on low-income borrowers. Unconstrained lenders strongly substitute high-LTI loans in local areas with higher constrained lender presence, but not high-LTI loans to low-income borrowers—consistent with adverse selection problems—implying lower overall credit to low-income borrowers. Consistently, policy-affected areas experience lower house price growth postregulation and, following the Brexit referendum (negative aggregate shock), better house price growth and lower mortgage defaults for low-income borrowers.

We conjecture that mutual funds with large shares of outstanding bond issues are more inclined to internalize the negative price spillovers of fire sales and thus sell their holdings in those issues, to a lower extent, when they experience redemptions. We provide evidence consistent with this conjecture and further show that ownership concentration limits bonds’ exposures to flow-induced fire sales. We exploit variation in negative spillovers arising from the Fed’s SMCCF to confirm the economic mechanism and explore our findings’ implications for fund performance and fire-sale spillovers to other funds.

Inspired by experimental evidence, we amend the recursive utility model to let risk aversion decrease with the temporal horizon. Our pseudo-recursive preferences remain tractable and retain appealing features of the long-run risk framework, notably its success at explaining asset pricing moments. In addition, our model addresses two challenges to the standard model. Calibrating the agents’ preferences to explain the equity premium no longer implies an extreme preference for early resolutions of uncertainty. Horizon-dependent risk aversion helps resolve key puzzles in finance on the valuation of assets across maturities and captures the term structure of equity risk premiums and its dynamics.