Premium
Identifying Expensive Trades by Monitoring the Limit Order Book
Author(s) -
Detollenaere Benoit,
D'hondt Catherine
Publication year - 2017
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.2422
Subject(s) - transaction cost , computer science , econometrics , limit (mathematics) , sample (material) , database transaction , order (exchange) , market microstructure , lasso (programming language) , operations research , economics , mathematics , microeconomics , finance , database , world wide web , mathematical analysis , chemistry , chromatography
This paper provides an analysis of the impact of microstructure variables on the transaction costs for split orders on 171 Euronext large cap stocks. First, using the adaptive Lasso selection method, we conduct an exploratory study to identify which microstructure variables best explain the transaction costs of split orders. Then, we propose an ordinal logistic model to classify ex ante transaction costs into buckets. Our empirical work demonstrates that our model performs very well both in‐sample and out‐of‐sample. All the findings show that microstructure information is of great importance for any investor who attempts to manage the execution of split orders throughout the day. Copyright © 2016 John Wiley & Sons, Ltd.