Knowledge that Transforms

Can a socially responsible fund (SRF) improve social welfare while maximizing assets under management? We consider a two-sector model integrating financial intermediation, emissions’ negative externalities, and investors’ social preferences with regard to value alignment and impact. In scenarios with a high proportion of value-aligned investors, the SRF invests in clean sectors and compels recipients companies to use low-emission suppliers from the polluting sector, which appeals to both investor types. Alternatively, the SRF adopts a dual-fund approach, with one fund targeting clean sectors for value-aligned investors and another focusing on reducing direct emissions in polluting sectors to attract impact investors.

The U.S. stock market’s return during the first month of a quarter correlates strongly with returns in future months, but the correlation is negative if the future month is the first month of a quarter, and positive if it isn’t. These correlations offset, consistent with the well-known near-zero unconditional autocorrelation, yet they are pervasive, present across industries and countries. The pattern accords with a model in which investors extrapolate announced earnings to predict future earnings, not recognizing that earnings in the first month of a quarter are discretely less predictable than in prior months. Survey data support the model.

We propose a general simulation-based procedure for estimating the quality of approximate policies in heterogeneous-agent equilibrium models, which allows us to verify that such approximate solutions describe a near-rational equilibrium. Our procedure endows agents with superior knowledge of the future path of the economy, while imposing a suitable penalty for such foresight. The relaxed problem is more tractable than the original, and results in an upper bound on agents’ welfare. Our method applies to various solution algorithms. We illustrate our approach in two applications: the incomplete-markets model of Krusell and Smith (1998) and the heterogeneous firm model of Khan and Thomas (2008).

We document the widespread nature and structure of missing observations of firm fundamentals and show how to systematically handle them. Missing financial data affects more than 70% of firms that represent about half of the total market cap. Firm fundamentals have complex systematic missing patterns, invalidating traditional approaches to imputation. We propose a novel imputation method to obtain a fully observed panel of firm fundamentals that exploits both time-series and cross-sectional dependency of data to impute missing values and allows for general systematic patterns of missingness. We document important implications for risk premiums estimates, cross-sectional anomalies, and portfolio construction. (JEL C14, C38, C55, G12)

This paper studies whether investor composition affects the sovereign debt market. We construct a data set of sovereign debt holdings by foreign and domestic bank, nonbank private and official investors for 101 countries across three decades. Compared with other investors, private nonbank investors absorb a disproportionate share of the debt supply, and their demand for emerging market debt is most price responsive. A counterfactual analysis of emerging market sovereigns shows a 10% increase in debt leads to a 5.8% yield increase but an outsized 8.4% increase without nonbank investors. We conclude that sovereigns are vulnerable to the loss of nonbanks.

Fractional trading (FT)—the ability to trade less than a whole share—removes barriers to high-priced stocks and facilitates entry by capital-constrained retail investors. We observe a surge of tiny trades, measured using off-exchange one-share trades, among high-priced stocks compared to low-priced stocks after FT is introduced to the U.S. equity markets. These tiny trades, when coordinated during attention-grabbing events, are forceful enough to exert large price pressure on high-priced stocks. Further evidence suggests that FT can even fuel meme-stock-like trading frenzies and bubbles in high-priced stocks, for which the feedback effect likely plays a role. (JEL G10, G12, G14, G18, G32, G41)

Higher-order beliefs—beliefs about others’ beliefs—may be important for trading behavior and asset prices but have received little systematic empirical examination. Examining more than 20 years of evidence from the Robert Shiller Investor Confidence surveys, we find that investors’ higher-order beliefs provide substantial motivations for nonfundamental speculation—taking a stock market position that conflicts with one’s valuation of the market. To explore the equilibrium implications, we construct a model that matches the survey evidence and highlights that investors’ higher-order beliefs amplify stock market overreaction and excess volatility.

Mutual funds investing in illiquid corporate bonds actively manage Treasury positions to buffer redemption shocks. This liquidity management practice can transmit non-fundamental fund flow shocks onto Treasuries, generating excess return volatility. Consistent with this hypothesis, we find that Treasury excess return volatility is positively associated with bond fund ownership, and this pattern is more pronounced among funds conducting intensive liquidity management. Causal evidence is provided by exploiting the U.S. Securities and Exchange Commission’s 2017 Liquidity Risk Management Rule. Evidence also suggests that the COVID-19 Treasury market turmoil was attributed to intensified liquidity management, an unintended consequence of the 2017 Liquidity Risk Management Rule.

Financial transaction taxes, or generally transaction costs, are salient in derivatives markets and seldom studied in equilibrium models. We study a tractable model with proportional transaction costs where agents trade a derivative with nonlinear payoffs to hedge nontraded endowments. We show that trade is sustained in an equilibrium with transaction costs only if there is sufficient heterogeneity in risk aversion. When there is trade, the equilibrium return variance increases in transaction costs. These results are driven by how mean-variance demands, hedging demands, and asymmetry of no-transaction region widths determine the equilibrium Sharpe ratio and return volatility when transaction costs change.

We examine the optimal financing of infrastructure when governments can expropriate rents from private sector firms that manage infrastructure. While private firms need incentives to implement projects well, governments need incentives to limit expropriation. This double moral hazard limits the willingness of outside investors to fund infrastructure projects. Optimal financing contracts involve government guarantees to investors against project failure to incentivize the government to agree not to expropriate, thus improving private sector incentives and project quality. The contract also reflects several other features prevalent in infrastructure financing in practice, among which are government coinvestment, tax subsidies, and development rights.