We analyze how ETFs compete. Drawing on a new model and empirical analysis, we show that ETF secondary market liquidity plays a key role in determining fees. More liquid ETFs for a given index charge higher fees and attract short-horizon investors who are more sensitive to liquidity than to fees. Higher turnover from these investors sustains the ETF’s high liquidity, allowing the ETF to extract a rent through its fee, and creating a first-mover advantage. Liquidity segmentation through clientele effects generates welfare losses. Our findings resolve the apparent paradox that higher-fee ETFs not only survive but also flourish in equilibrium

Using the staggered entry of Chi-X in 12 European equity markets as a source of exogenous variation in high frequency trading (HFT), we find that HFT causes significant increases in comovement in returns and in liquidity. About one-third of the increase in return comovement is due to faster diffusion of market-wide information. We attribute the remaining two-thirds to correlated trading strategies of HFTs. The increase in liquidity comovement is consistent with HFT liquidity providers being better able to monitor other stocks and adjust their liquidity provision accordingly. Our findings suggest a channel by which HFT impacts the cost of capital

We examine returns, order flow, and market conditions in the minutes before, during, and after NYSE and Nasdaq short sales. We find two distinct types of short sales: those that provide liquidity, and those that demand it. Liquidity-supplying shorts are strongly contrarian at intraday horizons. They trade when spreads are unusually wide, facing greater adverse selection. Liquidity-demanding shorts trade when spreads are narrow and tend to follow short-term price declines. These results support a competitive rational expectations model where both market-makers and informed traders short, indicating that these two shorting types are integral to both price discovery and liquidity provision

We exploit a unique natural experiment—recent restrictions of dark trading in Canada and Australia—and proprietary trade-level data to analyze the effects of dark trading. Disaggregating two types of dark trading, we find that dark limit order markets are beneficial to market quality, reducing quoted, effective, and realized spreads and increasing informational efficiency. In contrast, we do not find consistent evidence that dark midpoint crossing systems significantly affect market quality. Our results support recent theory that dark limit order markets encourage aggressive competition in liquidity provision. We discuss implications for the regulation of dark trading and tick sizes

97% of orders in US stock markets are cancelled before they trade, straining market infrastructure and raising concerns about predatory or manipulative trading. To understand the drivers of these extreme cancellation rates, we develop a simple model of liquidity provision and find that growth in order-to-trade ratios (OTTRs) is driven by fragmentation of trading and technological improvements that lower monitoring costs. High OTTRs occur legitimately in stocks with high volatility, fragmented trading, small tick sizes, and low volume. OTTRs are usually within levels consistent with market making, but occasionally spike to levels that may indicate illegitimate trading such as spoofing

Applying a well-established neuroscience framework to the issue of investor perception of volatility, we propose that after prolonged exposure to high volatility, investors tend to underestimate volatility due to adaptation to the high volatility, and vice versa. Using a combination of field and laboratory tests, we find strong support for this hypothesis. The evidence suggests that this neurobiologically-grounded perceptual bias can cause distortions of asset prices in sophisticated and liquid financial markets