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Abstract

The objective of this chapter is to define the term informed trading and to determine the adequate measure for identifying informed trading on the trader level for this study. It starts with a brief introduction to the information paradigm, followed by a classification of traders along different motives for trading and the corresponding level of information. Common measures of informed trading will be briefly presented.111 The choice of method follows (i) the need to identify the level of information for each transaction and (ii) data restrictions, i.e. there is no possibility to rebuild the order book.

Keywords

Adverse Selection Limit Order Market Maker Order Book Market Order 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    Measures for information asymmetry can be distinguished into two groups: (i) microstructure measures and (ii) corporate finance measures (e.g. analysts’ forecasts, market-to-book or earnings-price ratio). This study solely focuses on microstructure measures. The latter have been additionally implemented by Clarke/ Shastri (2000) and Van Ness/Van Ness/Warr (2001a).Google Scholar
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    Recent critics voiced by Boehmer/ Grammig/ Theissen (2007) based on trade misclassification due to implementing trade classification algorithms do not play a role in automated order-driven markets: Trades can only take place at the posted bid and ask prices, as per definition price improvement is not possible. The trade initiator of any trade can be identified through the available order entry and execution timestamps for all orders involved in the trade.Google Scholar
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