We analyze a two-country model of trade in both legitimate and counterfeit products. Domestic firms own trademarks and establish reputations for delivering high-quality products in a steady-state equilibrium. Foreign suppliers export legitimate low-quality merchandise and counterfeits of...

I show that frequent batch auctions for stocks have the potential to reduce the severity of stock price crashes when they occur. For a given sequence of orders from a continuous electronic limit order book market, matching orders using one second apart batch auctions results in nearly the same...

Using over eight trillion observations of market data, we use a regression discontinuity design to analyze the effect of increasing the minimum price variation (MPV) for quoting equity securities in light of recent proposals to increase the MPV from $0.01 to $0.05. We show that a larger MPV...

This paper studies the welfare consequence of increasing trading speed in financial markets. We build and solve a dynamic trading model, in which traders receive private information of asset value over time and trade strategically with demand schedules in a sequence of double auctions. A...

We propose a model of dynamic trading where a strategic high frequency trader receives an imperfect signal about future order flows, and exploits his speed advantage to optimize his quoting policy. We determine the provision of liquidity, order cancellations, and impact on low frequency traders...

Blockchains represent a novel application of cryptography and information technology to ag-eold problems of financial record-keeping, and they may lead to far-reaching changes in corporate governance. Many major players in the financial industry have began to invest in this new technology, and...

Using transaction data from a large non-fungible token (NFT) trading platform, this paper examines how the behavioral bias of selection-neglect interacts with extrapolative beliefs, accelerating the boom and delaying the crash in the recent NFT bubble. We show that the price-volume relationship...

We measure the individual and collective viewpoints of US Congress members on various economic policies by scraping their Twitter accounts. Tweets that criticize (support) a particular company are associated with a significant negative (positive) stock price reaction in a narrow time window...

We use stock exchange message data to quantify the negative aspect of high-frequency trading, known as "latency arbitrage." The key difference between message data and widely-familiar limit order book data is that message data contain attempts to trade or cancel that fail. This allows the...

With the high-frequency data of firm quotes in the transaction platform of foreign exchanges, arbitrage profit opportunities--in the forms of a negative bid-ask spread of a currency pair and triangular transactions involving three currency pairs--can be detected to emerge and disappear in the...