Network Centrality and Stock Market Volatility: The Impact of Communication Topologies on Prices
Year: 2012
Type: article
Abstract: Summary. We study the relationship between communication network topologies and the simulation results of an artificial stock market, here the Frankfurt Arti-ficial Stock Market. Heterogeneous interacting agents communicate their success and trading strategy to their nearest neighbors. A process of information diffusion arises through the adaptive behavior of agents when encountering more successful strategies in their direct neighborhood. We want to show that an increased central-ity measure of the network will lead to higher volatility and distortion within our simulation model. 1 Network Centrality and Stock Market Volatility The Frankfurt Artificial Stock Market (FASM)4 was designed to study how different communication network topologies affect the properties of the re-sulting time series of prices [2] and if a modified version of the Tobin tax is able to reduce the volatility of prices [3]. Two types of trading strategies, namely the fundamental strategy and the trend oriented strategy, as used in other models [6], propagate according to their actual performance, through a
Authors: Oliver Hein, Michael Schwind, Markus Spiwoks
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2181574698