An Examination of Changes in Specialists' Posted Price Schedules

New York Stock Exchange specialists disseminate informationto market participants by displaying price schedules consistingof bid prices, ask prices, bid depths, and ask depths. We examinehow specialists update these price schedules in a simultaneousequations model. We find that changes in the best prices anddepths on the limit order book have a significant impact onthe posted price schedule, while the effects of transactionsand order activity are secondary. Furthermore, we show thatspecialists revise prices and depths differently, but find noevidence that they revise the price schedule in response tochanges in inventory.     

A Framework for Developing and Testing Financial Capability Education Programs Targeted to Elementary Schools

Concerns about consumers’ ability to manage their finances have triggered a range of proposals, including interventions aimed at elementary school students. The goal of these approaches is to improve lifelong economic decision making, but the evidence supporting their efficacy is thin. In this article, the authors discuss the trend toward elementary financial education and propose a framework for developing evidence-based programs. They emphasize the need for understanding the underlying mechanisms that facilitate the translation of student knowledge into the ability to make sound economic decisions over the life course. The framework illustrates the importance of articulating the intended mechanisms and effects of education programs. This focus on mechanisms will not only facilitate the evaluation of individual programs, but also the synthesis of evidence across interventions.     

Credit Ratings and Stock Liquidity

We analyze contemporaneous and predictive relations betweencredit ratings and measures of equity market liquidity and findthat common measures of adverse selection, which reflect a portionof the uncertainty about future firm value, are larger whencredit ratings are poorer. We also show that future rating changescan be predicted using current levels of adverse selection.Collectively, our results validate widely used microstructuremeasures of adverse selection and offer new insights into thevalue of credit ratings and the specific nature of the informationthey contain.     

Technical Analysis and Liquidity Provision

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

The probability and magnitude of information events

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.     

Volatility and market structure

This study examines volatility within three related intra-day series – transaction returns, quote midpoint returns, and limit order book midpoint returns – for a set of NYSE-listed stocks. We document statistically significant GARCH effects both overall and surrounding earnings announcements in all three series for the majority of stocks in the sample. We then compare the extent of volatility clustering among the series. In addition, the relation between volatility and market structure is examined via a set of cross-sectional regressions, and relations among the series over time are studied in a vector autoregressive framework.