"Does Anonymity Matter in Electronic Limit Order Markets?"We develop a model of limit order trading in which some traders have better information on future price volatility. As limit orders have option-like features, this information is valuable for limit order traders. We solve for informed and uninformed limit order traders' bidding strategies in equilibrium when limit order traders' IDs are concealed and when they are visible. In either design, a large (resp. small) spread signals that informed limit order traders expect volatility to be high (resp. low). However the quality of this signal and market liquidity are different in each market design. We test these predictions using a natural experiment. As of April 23, 2001, the limit order book for stocks listed on Euronext Paris became anonymous. For our sample stocks, we find that following this change, the average quoted and effective spreads declined significantly. Consistent with our model, we also find that the size of the spread is a predictor of future price volatility and that the strength of the association between the spread and volatility is weaker after the switch to anonymity.

"We analyse transactions by corporate insiders in Germany. We find that insider trades are associated with significant abnormal returns. Insider trades that occur prior to an earnings announcement have a larger impact on prices. This result provides a rationale for the UK regulation that prohibits insiders from trading prior to earnings announcements. Both the ownership structure and the accounting standards used by the firm affect the magnitude of the price reaction. The position of the insider within the firm has no effect, which is inconsistent with the informational hierarchy hypothesis." Copyright (c) 2007 The Authors Journal compilation (c) 2007 Blackwell Publishing Ltd.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract: We analyze price discovery in floor-based and electronic exchanges using data from the German stock market. We find that both markets contribute to price discovery. There is bidirectional Granger causality, and prices from both markets adjust to deviations from the long-run equilibrium. We use two different measures of the contributions to price discovery, the information share (Hasbrouck 1995) and the weights with which the series enter the common long memory component as defined by Gonzalo / Granger (1995). The contributions of the two trading systems to the process of price discovery are almost equal when transaction prices are used for the estimation. Models based on quote midpoints indicate that the electronic trading system has a larger share in the price discovery process. A cross-sectional analysis reveals that the contributions to price discovery are positively related to the market shares of the trading systems. Terms of use: Documents in JEL classification: G 10Keywords: Floor versus screen trading, Error correction, Information shares, Common long memory components * I thank Deutsche Börse AG for providing the data. Financial support from the TMR grant "Financial Market Efficiency and Economic Efficiency" is gratefully acknowledged. Part of this research was undertaken while I was visiting Groupe HEC, Jouy-en-Josas. I thank Jesus Gonzalo and seminar participants at the universities of Cologne and Frankfurt for valuable comments. ** Erik Theissen, University of Bonn, BWL 1, Adenauerallee 24-42, 53113 Bonn, Germany; Email: theissen@uni-bonn.de. Price Discovery in Floor and Screen Trading SystemsAbstract: We analyze price discovery in floor-based and electronic exchanges using data from the German stock market. We find that both markets contribute to price discovery. There is bidirectional Granger causality, and prices from both markets adjust to deviations from the long-run equilibrium. We use two different measures of the contributions to price discovery, the information share (Hasbrouck 1995) and the weights with which the series enter the common long memory component as defined by Gonzalo / Granger (1995). The contributions of the two trading systems to the process of price discovery are almost equal when transaction prices are used for the estimation. Models based on quote midpoints indicate that the electronic trading system has a larger share in the price discovery process. A cross-sectional analysis reveals that the contribution...

Abstract:We reconsider the issue of price discovery in spot and futures markets. We use a threshold error correction model to allow for arbitrage opportunities to have an impact on the return dynamics.We estimate the model using quote midpoints, and we modify the model to account for time-varying transaction costs. We find that a) the futures market leads in the process of price discovery and that b) the presence of arbitrage opportunities has a strong impact on the dynamics of the price discovery process. Keywords:Price discovery, futures markets, threshold error correction, common factor weights JEL classification: G13, G14 Price Discovery in Spot and Futures Markets: A Reconsideration March 2011Abstract: We reconsider the issue of price discovery in spot and futures markets. We use a threshold error correction model to allow for arbitrage opportunities to have an impact on the return dynamics.We estimate the model using quote midpoints, and we modify the model to account for time-varying transaction costs. We find that a) the futures market leads in the process of price discovery and that b) the presence of arbitrage opportunities has a strong impact on the dynamics of the price discovery process.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in December 2002Abstract: Easley / Kiefer / O'Hara / Paperman (1996) (EKOP) have proposed an empirical methodology that allows to estimate the probability of informed trading and that has subsequently been used to address a wide range of issues in market microstructure. The data needed for estimation is the number of buyer-and seller-initiated trades. This information often has to be inferred by applying trade classification algorithms like the one proposed by Lee / Ready (1991). These algorithms are known to be inaccurate. In this paper we perform extensive simulations to show that inaccurate trade classification leads to biased estimation of the probability of informed trading when applying the EKOP methodology. The estimate is biased downward and the magnitude of the bias is related to the trading intensity of the stock in question. Scrutinizing prior empirical studies using the EKOP methodology, we conclude that the bias may severely affect the results of empirical microstructure studies.JEL classification: C52, G10, G14Keywords: Informed trading, market microstructure, trade classification * We thank seminar participants at the University of St. Gallen for helpful comments.

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We analyze transactions by corporate insiders in Germany. We find that insider trades are associated with significant abnormal returns. Insider trades that occur prior to an earnings announcement have a larger impact on prices. This result provides a rationale for the UK regulation that prohibits insiders from trading prior to earnings announcements. Both the ownership structure and the accounting standards used by the firm affect the magnitude of the price reaction. The position of the insider within the firm has no effect, which is inconsistent with the informational hierarchy hypothesis,.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract: We analyze the dynamics of liquidity in Xetra, an electronic open limit order book. We use the Exchange Liquidity Measure (XLM), a measure of the cost of a roundtrip trade of given size V. This measure captures the price and the quantity dimension of liquidity. Terms of use: Documents inWe present descriptive statistics, analyze the cross-sectional determinants of the XLM measure and document its intraday pattern. Our main contribution is an analysis of the dynamics of the XLM measure around liquidity shocks. We use intraday event study methodology to analyze how a shock affects the XLM measure. We consider two sets of liquidity shocks, large transactions (which are endogenous events because they originate in the market) and Bloomberg ticker news items (which are exogenous events because they originate outside of the market). We find that resiliency after large transactions is high, i.e., liquidity quickly reverts to "normal" levels. We further document that large trades take place at times when liquidity is unusually high. We interpret this as evidence that large transactions are timed. The Bloomberg ticker news items do not have a discernible effect on liquidity.JEL classification: G 10