Zappa, Paola and Vu, Duy Q. (2021) Markets as networks evolving step by step: Relational Event Models for the interbank market. Physica A: Statistical Mechanics and its Applications, 565. p. 125557. ISSN 0378-4371

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Abstract

We introduce a modeling framework for continuous-time relational data that allows detecting the fine-grained dynamics of network formation and change in financial markets. We propose newly derived Relational Event Models with time-weighting functions and corresponding time-weighted statistics as a suitable approach to capture the temporal aspects of observed network processes (i.e., memory) as well as a variety of extra-dyadic microstructures that include tie frequency (i.e., trading intensity) and tie value (i.e., traded amount). By specifying novel statistics and fine tuning weighting-function parameters, we show how this framework allows (1) obtaining more accurate representation of market dynamics, (2) disentangling competing micromechanisms of network formation and change, and (3) assessing their relevance. Also, by comparing alternative specifications of time effects, we emphasize the parsimony afforded by our approach. We illustrate the merits of our modeling framework in a study of the interbank liquidity market during the 2008 financial crisis.

Item Type:	Article
Keywords:	Network structure of markets; Financial markets; Market dynamics; Relational Event Models; Time-weighted statistics; Interbank money market;
Academic Unit:	Faculty of Social Sciences > School of Business
Item ID:	18373
Identification Number:	https://doi.org/10.1016/j.physa.2020.125557
Depositing User:	Paola Zappa
Date Deposited:	11 Apr 2024 14:00
Journal or Publication Title:	Physica A: Statistical Mechanics and its Applications
Publisher:	Elsevier BV, North-Holland
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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