Norman Ehrentreich

Personal Details

First Name:	Norman
Middle Name:
Last Name:	Ehrentreich
Suffix:
RePEc Short-ID:	peh3
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	http://www.wiwi.uni-halle.de/wiwi/lui/bwl/bank/top.htm
	Martin Luther University of Halle-Wittenberg Dept. of Banking and Finance Universitätsplatz 8-9 D-06099 Halle/Saale (Germany)
	+49-345-552 3453

Affiliation

Wirtschaftswissenschaftliche Fakultät
Martin-Luther-Universität Halle

Halle-Wittenberg, Germany
http://www.wiwi.uni-halle.de/
RePEc:edi:wwhalde (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

1. Norman Ehrentreich, 2002. "The Santa Fe Artificial Stock Market Re-Examined - Suggested Corrections," Computational Economics 0209001, University Library of Munich, Germany.

   Cited by:

   1. Germán Creamer, 2012. "Model calibration and automated trading agent for Euro futures," Quantitative Finance, Taylor & Francis Journals, vol. 12(4), pages 531-545, December.
   2. LeBaron, Blake, 2006. "Agent-based Computational Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 24, pages 1187-1233, Elsevier.
   3. José Manuel Galán & Luis R. Izquierdo & Segismundo S. Izquierdo & José Ignacio Santos & Ricardo del Olmo & Adolfo López-Paredes & Bruce Edmonds, 2009. "Errors and Artefacts in Agent-Based Modelling," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-1.
   4. Haijun Yang & Harry Wang & Gui Sun & Li Wang, 2015. "A comparison of U.S and Chinese financial market microstructure: heterogeneous agent-based multi-asset artificial stock markets approach," Journal of Evolutionary Economics, Springer, vol. 25(5), pages 901-924, November.

Articles

1. Ehrentreich, Norman, 2006. "Technical trading in the Santa Fe Institute Artificial Stock Market revisited," Journal of Economic Behavior & Organization, Elsevier, vol. 61(4), pages 599-616, December.

   Cited by:

   1. Wei-Xing Zhou & Guo-Hua Mu & Si-Wei Chen & Didier Sornette, "undated". "Strategies used as Spectroscopy of Financial Markets Reveal New Stylized Facts," Working Papers ETH-RC-11-005, ETH Zurich, Chair of Systems Design.
      • Wei-Xing Zhou & Guo-Hua Mu & Wei Chen & Didier Sornette, 2011. "Strategies used as spectroscopy of financial markets reveal new stylized facts," Papers 1104.3616, arXiv.org.
   2. Valentyn Panchenko & Sergiy Gerasymchuk & Oleg V. Pavlov, 2013. "Asset Price Dynamics with Heterogeneous Beliefs and Local Network Interactions," Discussion Papers 2013-18, School of Economics, The University of New South Wales.
      • Panchenko, Valentyn & Gerasymchuk, Sergiy & Pavlov, Oleg V., 2013. "Asset price dynamics with heterogeneous beliefs and local network interactions," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2623-2642.
   3. Chueh-Yung Tsao & Ya-Chi Huang, 2018. "Revisiting the issue of survivability and market efficiency with the Santa Fe Artificial Stock Market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(3), pages 537-560, October.
   4. Haijun Yang & Shuheng Chen, 2018. "A heterogeneous artificial stock market model can benefit people against another financial crisis," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-25, June.
   5. Ya-Chi Huang & Chueh-Yung Tsao, 2018. "Evolutionary Frequency and Forecasting Accuracy: Simulations Based on an Agent-Based Artificial Stock Market," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 79-104, June.
   6. Narayan, Paresh Kumar & Sharma, Susan Sunila, 2014. "Firm return volatility and economic gains: The role of oil prices," Economic Modelling, Elsevier, vol. 38(C), pages 142-151.
   7. Maciel, Leandro & Gomide, Fernando & Ballini, Rosangela, 2016. "A differential evolution algorithm for yield curve estimation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 129(C), pages 10-30.
   8. Vagnani, Gianluca, 2009. "The Black-Scholes model as a determinant of the implied volatility smile: A simulation study," Journal of Economic Behavior & Organization, Elsevier, vol. 72(1), pages 103-118, October.
   9. Gianluca Vagnani, 2009. "The Black-Scholes model as a determinant of the implied volatility smile: A simulation study," Post-Print hal-00736952, HAL.
   10. José Manuel Galán & Luis R. Izquierdo & Segismundo S. Izquierdo & José Ignacio Santos & Ricardo del Olmo & Adolfo López-Paredes & Bruce Edmonds, 2009. "Errors and Artefacts in Agent-Based Modelling," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-1.
   11. Gerasymchuk, S. & Pavlov, O.V., 2010. "Asset Price Dynamics with Local Interactions under Heterogeneous Beliefs," CeNDEF Working Papers 10-02, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
   12. Adão, Luiz F.S. & Silveira, Douglas & Ely, Regis A. & Cajueiro, Daniel O., 2022. "The impacts of interest rates on banks’ loan portfolio risk-taking," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
   13. Lijian Wei & Xiong Xiong & Wei Zhang & Xue-Zhong He & Yongjie Zhang, 2017. "The effect of genetic algorithm learning with a classifier system in limit order markets," Published Paper Series 2017-3, Finance Discipline Group, UTS Business School, University of Technology, Sydney.

Books

1. Norman Ehrentreich, 2008. "Agent-Based Modeling," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-540-73879-4, July.

   Cited by:

   1. Magda Fontana, 2010. "The Santa Fe Perspective on economics: emerging patterns in the science of complexity," History of Economic Ideas, Fabrizio Serra Editore, Pisa - Roma, vol. 18(2), pages 167-196.
      • Fontana Magda, 2009. "The Santa Fe Perspective on Economics: emerging patterns in the science of complexity," CESMEP Working Papers 200908, University of Turin.
   2. Maximilian Beikirch & Simon Cramer & Martin Frank & Philipp Otte & Emma Pabich & Torsten Trimborn, 2018. "Simulation of Stylized Facts in Agent-Based Computational Economic Market Models," Papers 1812.02726, arXiv.org, revised Nov 2019.
   3. Simon Cramer & Torsten Trimborn, 2019. "Stylized Facts and Agent-Based Modeling," Papers 1912.02684, arXiv.org.
   4. Philip Z. Maymin, 2012. "A New Kind of Finance," Papers 1210.1588, arXiv.org.
   5. Jan Polach & Jiri Kukacka, 2016. "Prospect Theory in the Heterogeneous Agent Model," Working Papers IES 2016/14, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jul 2016.
      • Jan Polach & Jiri Kukacka, 2019. "Prospect Theory in the Heterogeneous Agent Model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(1), pages 147-174, March.
   6. Gonzalo Castañeda, 2010. "Crisis económicas y cambios de paradigma," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 25(2), pages 425-441.
   7. Lucas Fievet & Didier Sornette, 2018. "Calibrating emergent phenomena in stock markets with agent based models," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-17, March.
   8. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
   9. C. Gonçalves P., 2015. "Financial Market Modeling With Quantum Neural Networks," Review of Business and Economics Studies // Review of Business and Economics Studies, Финансовый Университет // Financial University, vol. 3(4), pages 44-63.
   10. Longbing Cao & Qiang Yang & Philip S. Yu, 2020. "Data science and AI in FinTech: An overview," Papers 2007.12681, arXiv.org, revised Jul 2021.
   11. Longbing Cao, 2021. "AI in Finance: Challenges, Techniques and Opportunities," Papers 2107.09051, arXiv.org.
   12. Verónica Amarante & Ivone Perazzo, 2011. "Cantidad de niños en los hogares uruguayos: un análisis de los determinantes económicos, 1996-2006," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 26(1), pages 3-34.
   13. Flaminio Squazzoni, 2010. "The impact of agent-based models in the social sciences after 15 years of incursions," History of Economic Ideas, Fabrizio Serra Editore, Pisa - Roma, vol. 18(2), pages 197-234.
   14. Didier SORNETTE, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based Models," Swiss Finance Institute Research Paper Series 14-25, Swiss Finance Institute.
   15. Jonathan Köhler & Fjalar de Haan & Georg Holtz & Klaus Kubeczko & Enayat Moallemi & George Papachristos & Emile Chappin, 2018. "Modelling Sustainability Transitions: An Assessment of Approaches and Challenges," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 21(1), pages 1-8.
   16. Dimitris Kremmydas, 2012. "Agent based modeling for agricultural policy evaluation: A review," Working Papers 2012-3, Agricultural University of Athens, Department Of Agricultural Economics.
   17. Torsten Trimborn & Philipp Otte & Simon Cramer & Max Beikirch & Emma Pabich & Martin Frank, 2018. "SABCEMM-A Simulator for Agent-Based Computational Economic Market Models," Papers 1801.01811, arXiv.org, revised Oct 2018.
   18. Daniel C. Wagner & Thilo A. Schmitt & Rudi Schafer & Thomas Guhr & Dietrich E. Wolf, 2014. "Analysis of a decision model in the context of equilibrium pricing and order book pricing," Papers 1404.7356, arXiv.org.
   19. Lijian Wei & Wei Zhang & Xiong Xiong & Lei Shi, 2014. "Position-Limit Design for the CSI 300 Futures Markets," Research Paper Series 349, Quantitative Finance Research Centre, University of Technology, Sydney.
   20. Torsten Trimborn & Philipp Otte & Simon Cramer & Maximilian Beikirch & Emma Pabich & Martin Frank, 2020. "SABCEMM: A Simulator for Agent-Based Computational Economic Market Models," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 707-744, February.

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