Torsten Trimborn, Philipp Otte, Simon Cramer, Max Beikirch, Emma Pabich, Martin Frank
arXiv 5 Jan 2018 · Finance — Computational · publishedComputational Economics (2019) · 11 citations (OpenAlex)
arXiv:1801.01811 · PDF · DOI · OpenAlex · Extracted main text
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.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | G. Harras and D. Sornette (2011) How to grow a bubble: A model of myopic adapting agents | 0.969 | 11 | 4 | 91% |
| 2 | R. Cross, M. Grinfeld, H. Lamba, and T. Seaman (2005) A threshold model of investor psychology | 0.965 | 10 | 4 | 90% |
| 3 | M. Levy, H. Levy, and S. Solomon (1994) A microscopic model of the stock market: cycles, booms, and crashes | 0.928 | 5 | 3 | 80% |
| 4 | R. Cont and J.-P. Bouchaud (2000) Herd behavior and aggregate fluctuations in financial markets | 0.874 | 5 | 2 | 100% |
| 5 | A. Beja and M. B. Goldman (1980) On the dynamic behavior of prices in disequilibrium | 0.811 | 4 | 2 | 100% |
| 6 | W. A. Brock and C. H. Hommes (1997) A rational route to randomness | 0.811 | 4 | 2 | 100% |
| 7 | C. H. Hommes (2006) Heterogeneous agent models in economics and finance | 0.811 | 4 | 2 | 100% |
| 8 | W. A. Brock and C. H. Hommes (1998) Heterogeneous beliefs and routes to chaos in a simple asset pricing model | 0.737 | 3 | 2 | 100% |
| 9 | N. Ehrentreich (2007) Agent-based modeling: The Santa Fe Institute artificial stock market model revisited, volume 602 | 0.737 | 3 | 2 | 100% |
| 10 | T. Lux and M. Marchesi (1999) Scaling and criticality in a stochastic multi-agent model of a financial market | 0.737 | 3 | 2 | 100% |
Showing the top 10 of 107 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Simulation of Stylized Facts in Agent-Based Computational Economic Market Models | 1.000 | 9 | 4 |
| 2 | Stylized Facts and Agent-Based Modeling | 0.644 | 4 | 1 |