Conference Agenda

Using valuation models of financial analysts, we identify the drivers of disagreement

in stock valuation. Disagreement in the discount rate is as important in explaining

the variation in a stock’s intrinsic value as the disagreement in expected cash flows.

Analysts derive the discount rate by estimating the same return-generating model

(CAPM) but over different trailing horizons and under different assumptions about the

market risk premium. This approach produces large variation in betas and the discount

rate. These methodological choices are specific to the analyst rather than their firm.

Overall, we offer micro evidence on the inner workings of securities valuation.

The financial press is a conduit for popular narratives that reflect collective memory about historical events. Some collective memories relate to major stock market crashes, and investors may rely on associated narratives, or “crash narratives,” to inform current beliefs and choices. Using recent advances in computational linguistics, we develop a higher-order measure of narrativity based on newspaper articles that appear following major crashes. We provide evidence that crash narratives propagate broadly once they appear in news articles, and significantly explain predictive variation in market volatility. We exploit investor heterogeneity using survey data to distinguish the effects of narrativity and fundamental conditions and find consistent evidence. Finally, we develop a measure of pure narrativity to examine when financial press is more likely to employ narratives.

I show that the decline in interest rates and corporate tax rates over the past three decades accounts for the majority of the period’s exceptional stock market performance. Lower interest expenses and corporate tax rates mechanically explain over 40 percent of the real growth in corporate profits from 1989 to 2019. In addition, the decline in risk-free rates alone accounts for all of the expansion in price-to-earnings multiples. I argue, however, that the boost to profits and valuations from ever-declining interest and corporate tax rates is unlikely to continue, indicating significantly lower profit growth and stock returns in the future.

I develop a framework to quantify which features of investors’ dynamic trading strategies lead to momentum in equilibrium. I distinguish persistent demand shocks, capturing underreaction, and the term structure of demand elasticities, representing arbitrage intensities decreasing with investor horizon. I introduce both channels into an asset demand system that I estimate from institutional investors’ portfolio holdings and prices. Investors respond more to short-term than longer-term price changes: the term structure of elasticities is downward-sloping, creating momentum, whereas demand shocks mean-revert, contributing toward reversal. Stocks with more investors with downward-sloping term structures exhibit stronger momentum returns by 7% per year.

This paper studies the distributional effects of earning extrapolation bias on monetary transmission. Empirically, over-pessimistic firms with lower earning forecasts have higher investment elasticity to monetary shocks, which is more pronounced in the advertising-intensive industries. I develop a dynamic model to quantify the effects of extrapolation bias in a frictional product market, where firms extrapolate over idiosyncratic productivity news when making decisions on physical investment and customer acquisition. The model implies that firm-level overreaction amplifies the allocative efficiency of monetary easing: it raises aggregate productivity as capital flows to high markup firms. Moreover, the rise in aggregate output is underestimated by 57% if we assume rational expectation.

We study a macro-finance model with entrepreneurs who have diverse views about the likelihood that their ideas will lead to successful innovations. These views and the resulting experimentation stimulate economic growth and overcome market failures that would otherwise occur in an equilibrium without this diversity. The resulting benefits for future generations come at the cost of higher wealth and consumption inequality because a few entrepreneurs will ex-post be successful while most entrepreneurs will fail. Hence, our model provides a potential explanation for the “entrepreneurial puzzle” in which entrepreneurs choose to innovate despite taking on substantial idiosyncratic risk accompanied by low expected returns. Venture capital funds and taxes enhance risk sharing among entrepreneurs, stimulating innovation and growth unless high taxes deplete entrepreneurial capital. Redistribution via taxes reduces inequality and can raise interest rates. Nevertheless, a tradeoff exists between risk-sharing and the exertion of costly effort, giving rise to a hump-shaped economic growth curve when plotted against tax rates.

Off-exchange trades are often executed by referencing on-exchange prices. In equilibrium, such price referencing softens market makers' on-exchange competition and makes liquidity expensive for investors. Additionally, by equalizing on- and off-exchange prices, price referencing guarantees “best-execution” and makes investors indifferent where to trade. Market makers effectively obtain a license to fragment orders off exchange, raising their profits but reinforcing market-wide illiquidity. This inefficiency remains tenacious even if more market makers enter and if they are forced to compete off exchange, as in the SEC's proposed order-by-order auction. The model yields important implications for regulating various forms of off-exchange trading.

We show a significant loss in US Treasury market functionality when intensive use of dealer balance sheets is needed to intermediate bond markets, as in March 2020. Although yield volatility explains most of the variation in Treasury market liquidity over time, when dealer balance sheet utilization reaches sufficiently high levels, liquidity is much worse than predicted by yield volatility alone. This is consistent with the existence of occasionally binding constraints on the intermediation capacity of bond markets.

U.S. retail brokers route order flow to wholesalers based on their past performance. Brokers

face a strategic choice over how often to reallocate order flow, how aggressively to reward or

punish performance, and what history, across time or securities, to consider. This paper analyzes

how broker choices for allocating order flow shape competition among wholesalers. Our empirical

results are consistent with the theory that prospects for future order flow provide wholesalers

with strong incentives to offer price improvement and allow brokers to discipline the provision

of liquidity.

Using 150,000 actual trades, we examine competition among wholesalers, to which brokers route orders from their retail investors. We find that each broker's wholesaler execution prices have substantial dispersion and are persistent. However, most brokers do not adjust their routing even when they are sending more orders to higher-cost wholesalers. We also observe that the entry of a new wholesaler improves other wholesalers' execution quality. Finally, we present a stylized model that illustrates how brokers’ limited response to execution allows wholesalers to exercise their market power. Overall, our findings are inconsistent with perfect competition.

The canonical mechanism for financial asset exchange is the limit-order book. In decentralized blockchain ledgers (DeFi), costs and delays in appending new blocks to the ledger render a limit-order book impractical. Instead, a “pricing curve” is specified (e.g., the "constant product pricing function") and implemented using smart contracts deployed to the ledger. We develop a framework to study the equilibrium properties of such markets. Our framework provides new insights into how informational frictions distort liquidity provision in DeFi markets.

Financial data vendors intermediate the flow of information from firms to investors. I study frictions that arise in the context of this intermediation by focusing on one of the most prominent data vendors in the finance industry: Standard & Poor's ('S&P') Compustat database. Compustat provides subscribers with decades of 10-K and 10-Q data; however, it does not cover every public firm in every period. I show that a significant fraction of institutional investors do not invest in firms with missing data -- institutional ownership is over 40% below its unconditional mean for firms not covered in Compustat. A policy change instituted at S&P in the early 1990s provides a quasi-natural experiment to confirm a causal association between Compustat data coverage and institutional investor demand. In a battery of empirical tests, I then show that limited access to financial data is associated with lower informational efficiency of equity prices. This highlights the role that data vendors play in facilitating the flow of information within financial markets.

We quantify racial differences in the total rate of return on owner-occupied housing from 1975-2021. The total rate of return of buying a house equals the price appreciation plus the rental value of its housing services, minus taxes and maintenance. To measure the total return, we develop a new method to estimate the rental value of each owner-occupied house. We use houses that switch between the rental and owner-occupied market to estimate the relationship between purchase prices and rents. We then use this regression to predict the rental value of the entire owner-occupied housing stock and find this prediction out-performs standard hedonic techniques. We document both in raw data and with our new method that minority homeowners earn a 1.5-2 percentage point higher rental yield on housing than

white homeowners, which largely explains their 2-2.5 percentage point higher total return. Black and Hispanic homeowners’ total returns are also more volatile and sensitive to the business cycle. Observable differences in household income largely account for these racial return disparities. Our findings are broadly consistent with a model with a more severe credit constraint for minorities, which bids up rents, lowers house prices, and makes house prices sensitive to credit supply.

We characterise the large number of mortgage offers for which people qualify in the United Kingdom. Very few pick the cheapest option, nonetheless the one selected is not usually noticeably more expensive. A few borrowers make very expensive choices. These are most common when the menu they face has many expensive options, and are most likely for high loan-to-value and loan-to-income borrowers. Young people and first-time buyers are more prone to making expensive choices. The dispersion in the mortgage menu is consistent with banks price discriminating for borrowers who might pick poorly while competing for others who shop more effectively.

We study the impact of rising mortgage rates on mobility and labor reallocation. Using individual-level credit record data and variation in the timing of mortgage origination, we show that a 1 p.p. decline in mortgage rate deltas (Δr), measured as the difference between the mortgage rate locked in at origination and the current market rate, reduces moving rates by 0.68 p.p, or 9%. We find that this relationship is nonlinear: once Δr is high enough, households’ alternative of refinancing without moving becomes attractive such that moving probabilities no longer depend on Δr. Lastly, we find that mortgage lock-in attenuates household responsiveness to shocks to nearby employment opportunities that require moving, measured as wage growth in counties within a 50 to 150-mile ring and instrumented with a shift-share instrument. We provide causal estimates of mortgage lock-in effects, highlighting unintended consequences of monetary tightening with long-term fixed-rate mortgages on mobility and labor markets.

In this paper, we study the implications of a vacant home tax for housing availability and affordability. We develop a model with owner-occupied homes, tenanted rental units, and empty houses. Housing units are constructed by competitive developers and supplied to local households, but can also be sold to investors as a store of wealth. Empty homes held by investors are classified as speculative vacancies. Frictional vacancies, on the other hand, are the equilibrium result of search-and-matching frictions in the owner-occupied market. A tax on empty homes can improve housing availability and affordability in the rental market by reducing speculative vacancies, but can dis- tort the incentives to supply vacant homes for sale in the owner-occupied market (i.e., frictional vacancies), thereby increasing house prices and lowering home-ownership. Empirical predictions derived from the calibrated model are consistent with the pat- terns we observe for listings, sales, prices and rents in Vancouver following the recent implementation of an empty homes tax.

This paper studies how language barriers between lenders and borrowers translate into differences in borrower outcomes in the U.S. mortgage market. I use survey data to infer and machine learning techniques to predict borrowers' English proficiency. I document significant descriptive differences in perceptions of mortgages, application experiences, and mortgage rates between limited English proficient (LEP) and non-LEP borrowers. To measure the causal effects of language frictions, I exploit a Federal Housing Finance Agency policy that provided translated mortgage documents in Spanish to mortgage lenders. After the policy change, LEP Hispanic borrowers had a streamlined application process, contacted more lenders, understood mortgage contracts better, and enjoyed lower borrowing costs. Reducing language frictions also led to expanded access to credit, reduced loan risks, and a more competitive mortgage market for LEP borrowers. Overall, my findings highlight a cost-effective way to create a responsible inclusion of well-qualified LEP borrowers in the mortgage market.

Does emergency credit prevent long-term financial distress? We study the causal effects of government provided recovery loans to small businesses following natural disasters. The rapid financial injection might enable viable firms to survive and grow or might hobble precarious firms with more risk and

interest obligations. We show that the loans reduce exit and bankruptcy, increase employment and revenue, unlock private credit, and reduce delinquency. These effects, especially the crowding-in of private credit, appear to reflect resolving uncertainty about repair. We do not find capital reallocation away from neighboring firms and see some evidence of positive spillovers on local entry.