Synthetically Controlled Bandits
We consider experimentation in settings where, due to interference or other concerns, experimental units are coarse. ‘Region-split’ experiments on online platforms, where an intervention is applied to a single region over some experimental horizon, are one example of such a setting. Synthetic control is the state-of-the-art approach to inference in such experiments. The cost of these experiments is high since the opportunity cost of a sub-optimal intervention is borne by an entire region over the length of the experiment.
Is Physical Climate Risk Priced? Evidence from Regional Variation in Exposure to Heat Stress
We exploit regional variations in exposure to heat stress to study if physical climate risk is priced in municipal and corporate bonds as well as in equity markets. We find that local exposure to damages related to heat stress equaling 1% of GDP is associated with municipal bond yield spreads that are higher by around 15 basis points per annum (bps), the effect being larger for longer-term, revenue-only and lower-rated bonds, and arising mainly from the expected increase in energy expenditures and decrease in labor productivity.
Where Has All the Data Gone?
As financial technology improves and data becomes more abundant, do market prices reflect this growing information and allocate capital more efficiently? While a number of recent studies have documented rises in aggregate price efficiency, we show that there are large cross-sectional differences. The previously-documented increases are driven by a rise in the informativeness of large, growth stocks. The informational efficiency of smaller assets' prices or prices of assets with less growth potential are either flat or declining.
Bond Convenience Yields in the Eurozone Currency Union
In a monetary union, the risk-free rate cannot respond to country-level fiscal shocks, leaving only default spreads and convenience yields to respond. Empirically, we find that convenience yields play an important role as fiscal shock absorbers in the Eurozone. Consistent with downward-sloping demand for safety, Eurozone countries earn larger convenience yields after they release positive fiscal news.
What Drives Variation in the Debt/Output Ratio? The Dogs that Did Not Bark
Higher U.S. government debt/output ratios do not forecast higher future surpluses or lower real returns on Treasurys. Neither future cash flows nor discount rates account for the variation in the current debt/output ratio. The market valuation of Treasurys is surprisingly insensitive to the macro fundamentals. Instead, the future debt/output ratio accounts for most of the variation. Systematic surplus forecast errors may help to account for these findings. Since the start of the GFC, surplus projections have anticipated a large fiscal correction that failed to materialize.
Machine-Learning the Skill of Mutual Fund Managers
We show, using machine learning, that fund characteristics can consistently differentiate high from low-performing mutual funds, as well as identify funds with net-of-fees abnormal returns. Fund momentum and fund flow are the most important predictors of future risk-adjusted fund performance, while characteristics of the stocks that funds hold are not predictive. Returns of predictive long-short portfolios are higher following a period of high sentiment or a good state of the macro-economy.
Liquidity Regulation and Banks: Theory and Evidence
This paper investigates, theoretically and empirically, the effects of liquidity regulation on the banking system. We document that the current quantity-based liquidity rule has reduced banks' liquidity risks. However, the mandated liquidity buffer appears to crowd out bank lending and lead to a migration of liquidity risks to banks that are not subject to liquidity regulation. These findings motivate a model of liquidity regulation with endogenous liquidity premium and heterogeneous banks.
Privacy and Consumer Empowerment in Online Advertising
With heightened concerns regarding user privacy, there is a recent movement for empowering consumers with the ability to control how their private data are collected, stored, used and shared. Notably, between 2018 and 2020, the General Data Protection Regulation (GDPR) has been implemented in the European Union (EU), and the California Consumer Privacy Act (CCPA) and the California Privacy Rights Act (CPRA) have been implemented/passed in the state of California in the United States. These regulations address both consumer data security and consumer privacy rights.
Cross-Sectional Variation of Intraday Liquidity, Cross-Impact, and Their Effect on Portfolio Execution
The composition of natural liquidity has been changing over time. An analysis of intraday volumes for the S&P500 constituent stocks illustrates that (i) volume surprises, i.e., deviations from their respective forecasts, are correlated across stocks, and (ii) this correlation increases during the last few hours of the trading session.
Risk-Sensitive Optimal Execution via a Conditional Value-at-Risk Objective
We consider a liquidation problem in which a risk-averse trader tries to liquidate a fixed quantity of an asset in the presence of market impact and random price fluctuations. When deciding the liquidation strategy, the trader encounters a trade-off between the transaction costs incurred due to market impact and the volatility risk of holding the position.
Improving Match Rates in Dating Markets Through Assortment Optimization
Problem definition: We study how online platforms can leverage the behavioral considerations of their users to improve their assortment decisions. Motivated by our collaboration with a dating company, we study how a platform should select the assortments to show to each user in each period to maximize the expected number of matches in a time horizon, considering that a match is formed if two users like each other, possibly on different periods.
Artificial Intelligence, Firm Growth, and Product Innovation
We study the use and economic impact of artificial intelligence (AI) technologies among U.S. firms. We propose a new measure of firm-level AI investments, using a unique combination of detailed worker resume and job postings datasets. Our measure reveals a stark increase in AI investments across sectors in the last decade. AI-investing firms see higher growth in sales, employment, and market valuations.