Asquith, Oman, and Safaya (2010) conclude that short sales are often misclassified by the Lee-Ready algorithm. The algorithm identifies most short sales as buyer-initiated, whereas the authors posit that short sales should be overwhelmingly seller-initiated. Using order data to identify true...

Using a database of daily institutional trades, we document that a majority of short-term institutional trades lose money. In aggregate, over 23% of round-trip trades are held for less than three months, and the returns on these trades average -3.91% (non-annualized). These losses are pervasive...

We propose a parsimonious metric – the Adjusted Benford score (AB-score) – to improve the detection of financial misstatements. Based on Benford's Law, which predicts the leading-digit distribution of naturally occurring numbers, the AB-score estimates a firm-year's likelihood of financial...

A stream of literature shows that human attention constraints affect asset pricing in predictable ways. When traders are distracted, stock prices tend to initially underreact to earnings news and then gradually incorporate the news over subsequent weeks. In modern markets, however, the majority...

We identify a new channel ndash; market makers' attention constraints ndash; through which earnings announcements for one stock affect the liquidity of other stocks. When some stocks handled by a designated market maker have earnings announcements, liquidity is lower for non-announcement stocks...

Much of the liquidity supply in modern markets comes from algorithmic traders (ATs). Prompted by concerns of fragility induced by such voluntary market making, we examine ATs’ liquidity-provision role during the COVID-19 crisis. We find that amidst the turmoil as market liquidity declined ATs...

We compare the accuracy of the Bulk Volume classification (BVC) to that of the conventional rules: the tick rule (TR) and the Lee-Ready algorithm (LR) for a large sample of equities. TR and LR produce significantly better classifications than does BVC. This result applies to stocks of all sizes,...

We study the order exposure choice of various trader types in high-speed markets. Using message-level data to identify algorithmic (ATs) and non-algorithmic traders (NATs) we examine how technological differences affect order exposure. While both ATs and NATs hide orders, superior technology...

The trading of shares of the same firm in multiple markets has become common over the last thirty years, but there is little empirical evidence on the extent to which investors actively exploit multimarket environments. We introduce a volume-based measure of multimarket trading to address this...