This paper introduces reinforcement learning to examine the effect of trading on noise in a dynamic limit order market equilibrium. It shows that intensive noise liquidity provision (consumption) increases speculators' liquidity consumption (provision), improving (reducing) market liquidity. Channeled by uninformed chasing and informed aggressive liquidity provision, the increasing noise liquidity provision and consumption, respectively, improve price efficiency, generating a U-shaped price efficiency to the noise trading uncertainty on liquidity provision and consumption. Associated with a hump-shaped (U-shaped) profitability for the informed (uninformed) at a U-shaped noise trading cost in the noise trading uncertainty, this implies that, at increasing noise trading cost, intensive noise liquidity provision improves market liquidity, price efficiency, order profitability of informed traders, and reduces the loss, even makes profit, for uninformed traders.

We study how investor composition is related to future return, trading volume, and price volatility in the cross- section of the music-content non-fungible tokens (music NFTs). Our results show that the breadth of NFT ownership negatively predicts weekly collection-level median-price returns and trading counts. In contrast, ownership concentration and the fraction of small wallets are positive predictors. The fraction of large NFT wallets is a bearish signal for future collection floor-price returns. Investor composition measures have weak predictive power on price volatility. Further analysis indicates that an artist’s Spotify presence moderates the predictive power of investor composition for future NFT returns and trading volume, consistent with the notion that reducing information asymmetry helps improve price efficiency.

This study examines how short-sale constraints affect investors’ information acquisition and thereby shape stock price efficiency. By exploiting two settings that relax short-sale constraints in the US and China, respectively, we find that the removal of short-sale constraints increases investors’ information acquisition in both markets, but the effect is more prompt in China. Investors acquire value-relevant information, especially bad news, and improve their short-selling decisions in both markets. Lastly, information acquisition induced by the removal of short-sale constraints improves price efficiency. Our evidence shows that a reduction in trading frictions promotes information acquisition and improves price efficiency.

This study examines how short-sale constraints affect investors’ information acquisition and thereby shape stock price efficiency. By exploiting two settings that relax short-sale constraints in the US and China, respectively, we find that the removal of short-sale constraints increases investors’ information acquisition in both markets, but the effect is more prompt in China. Investors acquire value-relevant information, especially bad news, and improve their short-selling decisions in both markets. Lastly, information acquisition induced by the removal of short-sale constraints improves price efficiency. Our evidence shows that a reduction in trading frictions promotes information acquisition and improves price efficiency.

Using multiple short sale measures, we examine the predictive power of short sales for future stock returns in 38 countries from July 2006 to December 2014. We find that the days-to-cover ratio and the utilization ratio measures have the most robust predictive power for future stock returns in the global capital market. Our results display significant cross-country and cross-firm differences in the predictive power of alternative short sale measures. The predictive power of shorts is stronger in countries with non-prohibitive short sale regulations and for stocks with relatively low liquidity, high shorting fees, and low price efficiency.

We propose a model of trading in the over-the-counter corporate bond market where investors can buy and sell bonds through a dealer and can short bonds by borrowing them in the securities lending market. The model predicts that higher dealer inventory costs are associated with lower short interest for bonds, particularly for high-credit-quality bonds. We construct bond-level proxies for inventory costs and provide empirical evidence in support of the model's prediction. We find that much of the dramatic decline in short interest observed since the Great Financial Crisis (GFC) can be explained by an increase in proxies for inventory costs. We document that the short-sale constraints imposed by higher dealer inventory costs have had a negative impact on price efficiency. Our findings suggest that tighter post-GFC regulation may have had unintended consequences for bond market quality.