Abstract
Artificial market simulations have the potential to be a strong tool for studying rapid and large market fluctuations and designing financial regulations. High-frequency traders, that exchange multiple assets simultaneously within a millisecond, are said to be a cause of rapid and large market fluctuations. For such a large-scale problem, this paper proposes a software or computing platform for large-scale and high-frequency artificial market simulations (Plham: /pl\(\Lambda\)m). The computing platform, Plham, enables modeling financial markets composed of various brands of assets and a large number of agents trading on a short timescale. The design feature of Plham is the separation of artificial market models (simulation models) from their execution (execution models). This allows users to define their simulation models without parallel computing expertise and to choose one of the execution models they need. This computing platform provides a prototype execution model for parallel simulations, which exploits the variety in trading frequency among traders, that is, the fact that some traders do not require up-to-date information of markets changing in millisecond order. We evaluated a prototype implementation on the K computer using up to 256 computing nodes.





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Plham is now available on https://github.com/plham.
The results of this paper were obtained using an old version of Plham, before open sourcing.
See http://x10-lang.org for further information.
In X10, x10.util.List[T] is a generic collection with the type parameter T for the elements.
References
Chiarella C, Iori G (2002) A simulation analysis of the microstructure of double auction markets. Quant Finance 2:346–353
Darley V, Outkin AV (2007) A NASDAQ market simulation: insights on a major market from the science of complex adaptive systems. World Scientific, NJ, USA
Kawakubo S, Izumi K, Yoshimura S (2014) Analysis of an option market dynamics based on a heterogeneous agent model. Intell Syst Acc Finance Manag 21(2):105–128
Mizuta T, Hayakawa S, Izumi K, Yoshimura S (2013) Simulation study on effects of tick size difference in stock markets competition. In: Proceedings of the 8th international workshop on agent-based approach in economic and social complex systems (AESCS2013), pp 235–246
Mizuta T, Noritake Y, Hayakawa S, Izumi K (2015) Impacts of speed-up of market system on price formations using artificial market simulations. Working Paper 9, Japan Exchange Group (JPX)
Senft E (2013) How many markets do you trade simultaneously? http://traderkingdom.com/trading-futures-education-topics/trading-futures-basics/2856-how-many-markets-do-you-trade-simultaneously
Torii T, Izumi K, Yamada K (2015) Shock transfer by arbitrage trading: analysis using multi-asset artificial market. Evol Inst Econ Rev 12(2):395–412
U.S. Securities and Exchange Commission, and the Commodity Futures Trading Commission (2010) Findings regarding the market events of May 6, 2010
Xu H-C, Zhang W, Xiong X, Zhou W-X (2014) An agent-based computational model for China’s stock market and stock index futures market. Math Probl Eng 2014:563912
Yokokawa M, Shoji F, Uno A, Kurokawa M, Watanabe T (2011) The k computer: Japanese next-generation supercomputer development project. In: IEEE/ACM international symposium on low power electronics and design, pp 371–372
Yu C, Chen X, Wang C, Wu H, Sun J, Li Y, Zhang X (2015) An improved platform for multi-agent based stock market simulation in distributed environment. IEICE Trans Inf Syst 98(10):1727–1735
Acknowledgements
This work was supported by CREST, JST. Part of the results is obtained by using the K computer at the RIKEN Advanced Institute for Computational Science.
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Torii, T., Kamada, T., Izumi, K. et al. Platform design for large-scale artificial market simulation and preliminary evaluation on the K computer. Artif Life Robotics 22, 301–307 (2017). https://doi.org/10.1007/s10015-017-0368-z
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DOI: https://doi.org/10.1007/s10015-017-0368-z