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Keywords:high-frequency data 

Working Paper
Fed-Driven Systemic Tail Risk: High-Frequency Measurement, Evidence and Implications

We develop a framework to measure market-wide (systemic) tail risk in the cross-section of asset returns. Using high-frequency data on individual U.S. stocks and sector-specific ETF portfolios, we estimate time-varying jump intensities and multi-asset tail risk around Fed policy announcements. While most FOMC announcements generate systemic left-tail risk, there is no evidence that macro announcements have a similar effect. The magnitude of the tail risk induced by Fed policy announcements varies over the business cycle, peaks during the global financial crisis and remains high during phases ...
Working Papers , Paper 2023-016

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 Papers , Paper 2023-013

Working Paper
Systemic Tail Risk: High-Frequency Measurement, Evidence and Implications

We develop a new framework to measure market-wide (systemic) tail risk in the cross-section of high-frequency stock returns. We estimate the time-varying jump intensities of asset prices and introduce a testing approach that identifies multi-asset tail risk based on the release times of scheduled news announcements. Using high-frequency data on individual U.S. stocks and sector-specific ETF portfolios, we find that most of the FOMC announcements create systemic left tail risk, but there is no evidence that macro announcements do so. The magnitude of the tail risk induced by Fed news varies ...
Working Papers , Paper 2023-016

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 Series , Paper WP 2020-15

Working Paper
Mind Your Language: Market Responses to Central Bank Speeches

Post-meeting central bank communication often moves markets, but researchers have paid less attention to the more frequent central bankers’ speeches. We create a novel dataset of U.S. Federal Reserve speeches and develop supervised multimodal natural language processing methods to identify how monetary policy news affect bond and stock market volatility and tail risk through implied changes in forecasts of GDP, inflation, and unemployment. We find that forecast revisions derived from FOMC member speeches can help explain volatility and tail risk in both equity and bond markets. Speeches ...
Working Papers , Paper 2023-013

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 Papers , Paper 2314

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 Series , Paper WP-2020-15

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 Series , Paper WP-2020-12

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 ...
Working Papers , Paper 2023-013

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 during the Covid-19 pandemic to anonymized cell phone records and consumer spending data. We document three patterns. First, stay-at-home orders caused people to stay home: county-level measures of mobility declined 6–7% within two days of when the stay-at-home order went into effect. Second, stay-at-home orders caused large reductions in spending in sectors associated with mobility: small businesses and large retail chains. Third, we estimate fairly uniform responses to stay-at-home orders across the country; effects do not vary by ...
Working Paper Series , Paper WP-2020-12

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