2023/03 LEM Working Paper Series

A non-Normal framework for price discovery: The independent component based information shares measure

Sebastiano Michele Zema
Vector error correction models (VECMs); information shares; market microstructure; independent component analysis; pseudo maximum likelihood; price discovery.

  JEL Classifications
C32, C58, G14
I propose a new measure of price discovery, which I will refer to as the Independent Component based Information Share (IC-IS). This measure constitutes a variant of the widespread Information Share, with the main difference being it does not suffer the same identification issues. Under the assumptions of non-normality and independence of the shocks, a rather general theoretical framework leading to the estimation of the IC-IS is illustrated. After testing the robustness of the proposed measures to different non-Normal distributions in a simulated environment, an empirical exercise encompassing different price discovery applications will follow.
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