SABCEMM: A Simulator for Agent-Based Computational Economic Market Models

Torsten Trimborn (), Philipp Otte, Simon Cramer, Maximilian Beikirch, Emma Pabich and Martin Frank
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Torsten Trimborn: RWTH Aachen
Philipp Otte: RWTH Aachen
Simon Cramer: RWTH Aachen
Maximilian Beikirch: RWTH Aachen
Emma Pabich: RWTH Aachen
Martin Frank: Karlsruhe Institute of Technology, Steinbuch Center for Computing

Computational Economics, 2020, vol. 55, issue 2, No 14, 707-744

Abstract: Abstract We introduce the simulation tool SABCEMM (Simulator for Agent-Based Computational Economic Market Models) for agent-based computational economic market (ABCEM) models. Our simulation tool is implemented in C++ and we can easily run ABCEM models with several million agents. The object-oriented software design enables the isolated implementation of building blocks for ABCEM models, such as agent types and market mechanisms. The user can design and compare ABCEM models in a unified environment by recombining existing building blocks using the XML-based SABCEMM configuration file. We introduce an abstract ABCEM model class which our simulation tool is built upon. Furthermore, we present the software architecture as well as computational aspects of SABCEMM. Here, we focus on the efficiency of SABCEMM with respect to the run time of our simulations. We show the great impact of different random number generators on the run time of ABCEM models. The code and documentation is published on GitHub at https://github.com/SABCEMM/SABCEMM, such that all results can be reproduced by the reader.

Keywords: Agent-based models; Monte Carlo simulations; Economic market models; Stylized facts; Simulator; Finite size effects; Random number generator (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10614-019-09910-1

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