We study the role of informed trading in a fragmented financial market under the absence of inter-market price priority. Due to frictions in traders' market access, liquidity providers on alternative trading platforms may be exposed to an increased adverse selection risk. As a consequence, the...

We present the first evidence of the impact of dark trading on adverse selection in an aggregate market. At moderate levels of dark trading, a positive liquidity effect dominates an information acquisition disincentive effect, such that dark trading induces reductions in both adverse selection...

When short selling is costly, owners of an asset have greater incentive to become informed than nonowners because trading on negative information is easier for them. Thus, information acquisition concentrates among investors owning the asset. A short selling ban restricts selling to only the...

We develop a tractable model of a limit order market where informed and liquidity investors compete with a professional liquidity provider who has a monitoring advantage. We apply our model to study the impact of exogenous transaction costs and investor patience on trading activity and market...

The transaction-level analysis of security price changes by Madhavan, Richardson, and Roomans (1997, hereafter MRR) is a useful framework for financial analysis. The first-order Markov property of trading indicator variables is a critical assumption in the MRR model, which contradicts the...

This paper shows how to map predictions of theoretical models of market microstructure into operational empirical measures of liquidity. A meta-model implies an empirical measure of liquidity, denoted L, which describes various characteristics of trading and funding liquidity such as trading...

This paper aims to search the high volatility of stock prices in stock market crises produced by adverse information, throughout investigating the links between stock price volatility and the institutional features of the major stock exchanges as exist in practice. The study finds that the...

We let "Algorithmic Market-Makers" (AMMs), using Q-learning algorithms, choose prices for a risky asset when their clients are privately informed about the asset payoff. We find that AMMs learn to cope with adverse selection and to update their prices after observing trades, as predicted by...

Asymmetric information theory says that individuals who cooperate in different situations have different levels of knowledge on a subject. The main role of a financial system is to direct funds to individuals and companies that have good money investments. To do this correctly, participants in...