2020/28 | LEM Working Paper Series | ||||||||||||||||
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Directed Acyclic Graph based Information Shares for Price Discovery |
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Sebastiano Michele Zema |
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Keywords | |||||||||||||||||
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Structural VECM; Information Shares; Microstructure noise; Independent Component Analysis; Directed acyclic graphs.
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JEL Classifications | |||||||||||||||||
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C32, C58, G14
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Abstract | |||||||||||||||||
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The possibility to measure the contribution of agents and exchanges to the price
formation process in financial markets acquired increasing importance in the literature.
In this paper I propose to exploit a data-driven approach to identify structural
vector error correction models (SVECM) typically used for price discovery.
Exploiting the non-Normal distributions of the variables under consideration, I propose a
variant of the widespread Information Share measure, which I will refer to as the
Directed Acyclic Graph based-Information Shares(DAG-IS), which can identify the
leaders and the followers in the price formation process through the exploitation of
a causal discovery algorithm well established in the area of machine learning. The
approach will be illustrated from a semi-parametric perspective, solving the identification
problem with no need to increase the computational complexity which usually
arises when working at incredibly short time scales. Finally, an empirical application
on IBM intraday data will be provided.
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