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Working Paper
Sluggish news reactions: A combinatorial approach for synchronizing stock jumps
Stock prices often react sluggishly to news, producing gradual jumps and jump delays. Econometricians typically treat these sluggish reactions as microstructure effects and settle for a coarse sampling grid to guard against them. Synchronizing mistimed stock returns on a fine sampling grid allows us to better approximate the true common jumps in related stock prices.
Working Paper
Heterogeneity in the Marginal Propensity to Consume: Evidence from Covid-19 Stimulus Payments
We identify 16,016 recipients of Covid-19 Economic Impact Payments in anonymized transaction-level debit card data from Facteus. We use an event study framework to show that in the two weeks following a sudden $1,200 payment from the IRS, consumers immediately increased spending by an average of $577, implying a marginal propensity to consume (MPC) of 48%. Consumer spending falls back to normal levels after two weeks. Stimulus recipients who live paycheck-to-paycheck spend 68% of the stimulus payment immediately, while recipients who save much of their monthly income spend 23% of the stimulus ...
Working Paper
Do Stay-at-Home Orders Cause People to Stay at Home? Effects of Stay-at-Home Orders on Consumer Behavior
We link the county-level rollout of stay-at-home orders to anonymized cellphone records and consumer spending data. We document three patterns. First, stay-at-home orders caused people to stay at home: county-level measures of mobility declined by between 9% and 13% by the day after the stay-at-home order went into effect. Second, stay-at-home orders caused large reductions in spending in sectors associated with mobility: restaurants and retail stores. However, food delivery sharply increased after orders went into effect. Third, there is substantial county-level heterogeneity in consumer ...
Working Paper
Do Stay-at-Home Orders Cause People to Stay at Home? Effects of Stay-at-Home Orders on Consumer Behavior
We link the county-level rollout of stay-at-home orders to anonymized cellphone records and consumer spending data. We document three patterns. First, stay-at-home orders caused people to stay at home: county-level measures of mobility declined by between 9% and 13% by the day after the stay-at-home order went into effect. Second, stay-at-home orders caused large reductions in spending in sectors associated with mobility: restaurants and retail stores. However, food delivery sharply increased after orders went into effect. Third, there is substantial county-level heterogeneity in consumer ...
Report
The Bitcoin–Macro Disconnect
This paper investigates the link between Bitcoin and macroeconomic fundamentals by estimating the impact of macroeconomic news on Bitcoin using an event study with intraday data. The key result is that, unlike other U.S. asset classes, Bitcoin is orthogonal to monetary and macroeconomic news. This disconnect is puzzling as unexpected changes in discount rates should, in principle, affect the price of Bitcoin even when interpreting Bitcoin as a purely speculative asset.
Working Paper
Heterogeneity in the Marginal Propensity to Consume: Evidence from Covid-19 Stimulus Payments
We identify 16,016 recipients of Covid-19 Economic Impact Payments in anonymized transaction-level debit card data from Facteus. We use an event study framework to show that in the two weeks following a sudden $1,200 payment from the IRS, consumers immediately increased spending by an average of $577, implying a marginal propensity to consume (MPC) of 48%. Consumer spending falls back to normal levels after two weeks. Stimulus recipients who live paycheck-to-paycheck spend 68% of the stimulus payment immediately, while recipients who save much of their monthly income spend 23% of the stimulus ...
Report
The Price of Processing: Information Frictions and Market Efficiency in DeFi
This paper investigates the speed of price discovery when information becomes publicly available but requires costly processing to become common knowledge. We exploit the unique institutional setting of hacks on decentralized finance (DeFi) protocols. Public blockchain data provides the precise time a hack’s transactions are recorded—becoming public information—while subsequent social media disclosures mark the transition to common knowledge. This empirical design allows us to isolate the price impact occurring during the interval characterized by information asymmetry driven purely by ...
Working Paper
Investing in the Batteries and Vehicles of the Future: A View Through the Stock Market
A large number of companies operating in the EV and battery supply chain have listed on a U.S. stock exchange in recent years. I compile a unique data set of high-frequency stock returns for those companies and investigate the extent to which an “industry” factor specific to the EV and battery supply chain (an “EV” factor) can explain their returns. Those returns are decomposed into systematic and idiosyncratic components, with the former given by a set of latent factors extracted from a large panel of stock returns using high-frequency principal components. It is found that a market ...
Working Paper
Mind Your Language: Market Responses to Central Bank Speeches
Researchers have carefully studied post-meeting central bank communication and have found that it often moves markets, but they have paid less attention to the more frequent central bankers’ speeches. We create a novel dataset of US Federal Reserve speeches and use supervised multimodal natural language processing methods to identify how monetary policy news affect financial volatility and tail risk through implied changes in forecasts of GDP, inflation, and unemployment. We find that news in central bankers’ speeches can help explain volatility and tail risk in both equity and bond ...
Working Paper
Mind Your Language: Market Responses to Central Bank Speeches
Researchers have carefully studied post-meeting central bank communication and have found that it often moves markets, but they have paid less attention to the more frequent central bankers’ speeches. We create a novel dataset of US Federal Reserve speeches and develop supervised multimodal natural language processing methods to identify how monetary policy news affect financial volatility and tail risk through implied changes in forecasts of GDP, inflation, and unemployment. We find that news in central bankers’ speeches can help explain volatility and tail risk in both equity and bond ...