We analyze contemporaneous and predictive relations between credit ratings and measures of equity market liquidity and find that common measures of adverse selection, which reflect a portion of the uncertainty about future firm value, are larger when credit ratings are poorer. We also show that future rating changes can be predicted using current levels of adverse selection. Collectively, our results validate widely used microstructure measures of adverse selection and offer new insights into the value of credit ratings and the specific nature of the information they contain.

The apparent conflict between the level of resources dedicated to technical analysis by practitioners and academic theories of market efficiency is a long-standing puzzle. We explore a previously unexamined feature of technical analysis–namely its relation to liquidity provision. We demonstrate that support and resistance levels coincide with peaks in depth on the limit order book and moving average forecasts reveal information about the relative position of depth on the book. Furthermore, we show that these relationships stem from technical rules locating depth already in place on the limit order book.

New York Stock Exchange specialists disseminate information to market participants by displaying price schedules consisting of bid prices, ask prices, bid depths, and ask depths. We examine how specialists update these price schedules in a simultaneous equations model. We find that changes in the best prices and depths on the limit order book have a significant impact on the posted price schedule, while the effects of transactions and order activity are secondary. Furthermore, we show that specialists revise prices and depths differently, but find no evidence that they revise the price schedule in response to changes in inventory.

In 1997, the Securities and Exchange Commission enacted significant reforms in U.S. markets. Several studies document that the new order handling rules increased competition for Nasdaq stocks, but the reforms were designed with an additional goal in mind—to increase quote competition for the trading of NYSE-listed securities on Nasdaq (i.e., third market trading). An evaluation of the reforms in the third market indicates that they did not achieve this objective. Instead, both quote quality and quoting frequency were diminished, due primarily to elimination of the excess spread rule. This suggests that more significant changes are needed to increase inter-exchange competition.

Models of adverse selection risk generally assume that market makers offset expected losses to informed traders with expected gains from the uninformed. We recognize that the expected loss captures a combination of two effects: (1) the probability that some traders have private information, and (2) the likely magnitude of that information. We use a maximum-likelihood approach to separately estimate the probability and magnitude of private information events for NYSE-listed stocks from 1993 through 2003. The results shed light on the price discovery process and have implications for many areas of finance.

We analyze contemporaneous and predictive relations between credit ratings and measures of equity market liquidity and find that common measures of adverse selection, which reflect a portion of the uncertainty about future firm value, are larger when credit ratings are poorer. We also show that future rating changes can be predicted using current levels of adverse selection. Collectively, our results validate widely used microstructure measures of adverse selection and offer new insights into the value of credit ratings and the specific nature of the information they contain.

The apparent conflict between the level of resources dedicated to technical analysis by practitioners and academic theories of market efficiency is a long-standing puzzle. We explore a previously unexamined feature of technical analysis — namely its relation to liquidity provision. We demonstrate that support and resistance levels coincide with peaks in depth on the limit order book and moving average forecasts reveal information about the relative position of depth on the book. Furthermore, we show that these relationships stem from technical rules locating depth already in place on the limit order book.

New York Stock Exchange specialists disseminate information to market participants by displaying price schedules consisting of bid prices, ask prices, bid depths, and ask depths. We examine how specialists update these price schedules in a simultaneous equations model. We find that changes in the best prices and depths on the limit order book have a significant impact on the posted price schedule, while the effects of transactions and order activity are secondary. Furthermore, we show that specialists revise prices and depths differently, but find no evidence that they revise the price schedule in response to changes in inventory.