Using intraday data, we document statistically strong, but temporary, impacts of commodity index trade flows on commodity futures prices. We also examine the previously documented positive returns around the issuance of commodity-linked notes and find that these returns are an order of magnitude too large to be caused by the small trades necessary to hedge the notes. We provide new evidence that they are instead the result of endogenous issuance. Our results provide novel support for commodity financialization but highlight the importance of measuring the magnitude of financial investment, since even large financial flows have economically modest impacts on prices.

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.

Trading halts increase, rather than reduce, both volume and volatility. Volume (volatility) in the first full trading day after a trading halt is 230 percent (50 to 115 percent) higher than following 'pseudohalts': nonhalt control periods matched on time of day, duration, and absolute net-of-market returns. These results are robust over different halt types and news categories. Higher posthalt volume is observed into the third day, while higher posthalt volatility decays within hours. The extent of media coverage is a partial determinant of volume and volatility following both halts and pseudohalts but a separate halt effect remains after controlling for the media effect.

For a sample of NYSE firms, we show that wide spreads are accompanied by low depths, and that spreads widen and depths fall in response to bigger volume. Spreads widen and depths fall in anticipation of earnings announcements; these effects are more pronounced for announcements with larger subsequent price changes. Spreads are also wider following earnings announcements, but this effect dissipates quickly after controlling for volume. Collectively, our results suggest liquidity providers are sensitive to changes in information asymmetry risk and use both spreads and depths to actively manage this risk.

This paper evaluates alternative methods for classifying individual trades as market buy or market sell orders using intraday trade and quote data. We document two potential problems with quote‐based methods of trade classification: quotes may be recorded ahead of trades that triggered them, and trades inside the spread are not readily classifiable. These problems are analyzed in the context of the interaction between exchange floor agents. We then propose and test relatively simple procedures for improving trade classifications.

This paper evaluates alternative methods for classifying individual trades as market buy or market sell orders using intraday trade and quote data. We document two potential problems with quote-based methods of trade classification: quotes may be recorded ahead of trades that triggered them, and trades inside the spread are not readily classifiable. These problems are analyzed in the context of the interaction between exchange floor agents. We then propose and test relatively simple procedures for improving trade classifications.

Trading halts increase, rather than reduce, both volume and volatility. Volume (volatility) in the first full trading day after a trading halt is 230 percent (50 to 115 percent) higher than following “pseudohalts”: nonhalt control periods matched on time of day, duration, and absolute net‐of‐market returns. These results are robust over different halt types and news categories. Higher posthalt volume is observed into the third day while higher posthalt volatility decays within hours. The extent of media coverage is a partial determinant of volume and volatility following both halts and pseudohalts, but a separate halt effect remains after controlling for the media effect.

Trading halts increase, rather than reduce, both volume and volatility. Volume (volatility) in the first full trading day after a trading halt is 230 percent (50 to 115 percent) higher than following “pseudohalts”: nonhalt control periods matched on time of day, duration, and absolute net-of-market returns. These results are robust over different halt types and news categories. Higher posthalt volume is observed into the third day while higher posthalt volatility decays within hours. The extent of media coverage is a partial determinant of volume and volatility following both halts and pseudohalts, but a separate halt effect remains after controlling for the media effect.