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Shu-Heng Chen

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. Chen, Shu-Heng & Gostoli, Umberto, 2013. "Coordination in the El Farol Bar problem: The role of social preferences and social networks," Economics Discussion Papers 2013-20, Kiel Institute for the World Economy (IfW Kiel).

    Cited by:

    1. Xin-Jie Zhang & Yong Tang & Jason Xiong & Wei-Jia Wang & Yi-Cheng Zhang, 2018. "Dynamics of Cooperation in Minority Games in Alliance Networks," Sustainability, MDPI, vol. 10(12), pages 1-17, December.
    2. Iván Arribas & Amparo Urbano Salvador, 2014. "Local coordination and global congestion in random networks," Discussion Papers in Economic Behaviour 0814, University of Valencia, ERI-CES.
    3. Zhang, Wei & Sun, Yuxin & Feng, Xu & Xiong, Xiong, 2015. "Evolutionary Minority Game with searching behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 694-706.

  2. Chen, Shu-Heng & Chang, Chia-Ling & Wen, Ming-Chang, 2013. "Social networks and macroeconomic stability," Economics Discussion Papers 2013-4, Kiel Institute for the World Economy (IfW Kiel).

    Cited by:

    1. Savioli, Marco & Patuelli, Roberto, 2016. "Social capital, institutions and policymaking," Economics Discussion Papers 2016-26, Kiel Institute for the World Economy (IfW Kiel).
    2. Ketelaar, Paul E. & Janssen, Loes & Vergeer, Maurice & van Reijmersdal, Eva A. & Crutzen, Rik & van ‘t Riet, Jonathan, 2016. "The success of viral ads: Social and attitudinal predictors of consumer pass-on behavior on social network sites," Journal of Business Research, Elsevier, vol. 69(7), pages 2603-2613.
    3. Hanappi, Hardy & Scholz-Waeckerle, Manuel, 2015. "Evolutionary Political Economy: Content and Methods," MPRA Paper 75447, University Library of Munich, Germany.
    4. Lena Gerdes & Bernhard Rengs & Manuel Scholz-Wäckerle, 2022. "Labor and environment in global value chains: an evolutionary policy study with a three-sector and two-region agent-based macroeconomic model," Journal of Evolutionary Economics, Springer, vol. 32(1), pages 123-173, January.
    5. Rengs, Bernhard & Scholz-Wäckerle, Manuel & van den Bergh, Jeroen, 2020. "Evolutionary macroeconomic assessment of employment and innovation impacts of climate policy packages," Journal of Economic Behavior & Organization, Elsevier, vol. 169(C), pages 332-368.
    6. Kurt Kratena, 2015. "Thematic Report: Macroeconomic Models Including Specifically Social and Environmental Aspects. WWWforEurope Deliverable No. 8," WIFO Studies, WIFO, number 58411.
    7. Rengs, Bernhard & Scholz-Waeckerle, Manuel, 2017. "Consumption & Class in Evolutionary Macroeconomics," MPRA Paper 80021, University Library of Munich, Germany.
    8. Bernhard Rengs & Manuel Scholz-Wäckerle, 2019. "Consumption & class in evolutionary macroeconomics," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 229-263, March.
    9. Bernhard Rengs & Manuel Scholz-Wäckerle & Ardjan Gazheli & Miklós Antal & Jeroen C.J.M. van den Bergh, 2015. "Testing Innovation, Employment and Distributional Impacts of Climate Policy Packages in a Macro-evolutionary Systems Setting. WWWforEurope Working Paper No. 83," WIFO Studies, WIFO, number 57891.

  3. Shu-Heng Chen & Sai-Ping Li, 2011. "Econophysics: Bridges over a Turbulent Current," Papers 1107.5373, arXiv.org.

    Cited by:

    1. Pirvu Daniela & Barbuceanu Mircea, 2016. "Recent Contributions Of The Statistical Physics In The Research Of Banking, Stock Exchange And Foreign Exchange Markets," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 2, pages 85-92, April.
    2. Marcel Ausloos & Franck Jovanovic & Christophe Schinckus, 2016. "On the "usual" misunderstandings between econophysics and finance: some clarifications on modelling approaches and efficient market hypothesis," Papers 1606.02045, arXiv.org.
    3. Wen-Jie Xie & Zhi-Qiang Jiang & Gao-Feng Gu & Xiong Xiong & Wei-Xing Zhou, 2015. "Joint multifractal analysis based on the partition function approach: Analytical analysis, numerical simulation and empirical application," Papers 1509.05952, arXiv.org.
    4. Zebende, G.F. & da Silva, M.F. & Machado Filho, A., 2013. "DCCA cross-correlation coefficient differentiation: Theoretical and practical approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1756-1761.
    5. Anabele-Linda Pardi & Mario Paolucci, 2021. "A Chemical Analysis of Hybrid Economic Systems—Tokens and Money," Mathematics, MDPI, vol. 9(20), pages 1-22, October.
    6. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.

  4. Chang, Chia-ling & Chen, Shu-heng, 2011. "Interactions in DSGE models: The Boltzmann-Gibbs machine and social networks approach," Economics Discussion Papers 2011-25, Kiel Institute for the World Economy (IfW Kiel).

    Cited by:

    1. Chen, Shu-Heng & Chang, Chia-Ling & Wen, Ming-Chang, 2013. "Social networks and macroeconomic stability," Economics Discussion Papers 2013-4, Kiel Institute for the World Economy (IfW Kiel).

  5. S. C. Wang & J. J. Tseng & C. C. Tai & K. H. Lai & W. S. Wu & S. H. Chen & S. P. Li, 2007. "Network Topology of an Experimental Futures Exchange," Papers 0705.2551, arXiv.org.

    Cited by:

    1. Wang, Junjie & Zhou, Shuigeng & Guan, Jihong, 2011. "Characteristics of real futures trading networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 398-409.
    2. Lee, Junghoon & Youn, Janghyuk & Chang, Woojin, 2012. "Intraday volatility and network topological properties in the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1354-1360.
    3. Aura Reggiani, 2022. "The Architecture of Connectivity: A Key to Network Vulnerability, Complexity and Resilience," Networks and Spatial Economics, Springer, vol. 22(3), pages 415-437, September.
    4. Peng, Dan & Han, Xiao-Pu & Wei, Zong-Wen & Wang, Bing-Hong, 2015. "Punctuated equilibrium dynamics in human communications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 36-44.
    5. Zhi-Qiang Jiang & Wen-Jie Xie & Xiong Xiong & Wei Zhang & Yong-Jie Zhang & W. -X. Zhou, 2012. "Trading networks, abnormal motifs and stock manipulation," Papers 1301.0007, arXiv.org.
    6. Zhou, Bin & Xie, Jia-Rong & Yan, Xiao-Yong & Wang, Nianxin & Wang, Bing-Hong, 2017. "A model of task-deletion mechanism based on the priority queueing system of Barabási," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 415-421.
    7. Tseng, Jie-Jun & Lin, Chih-Hao & Lin, Chih-Ting & Wang, Sun-Chong & Li, Sai-Ping, 2010. "Statistical properties of agent-based models in markets with continuous double auction mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(8), pages 1699-1707.
    8. Junjie Wang & Shuigeng Zhou & Jihong Guan, 2010. "Characteristics of Real Futures Trading Networks," Papers 1004.4402, arXiv.org, revised Feb 2011.

  6. Tina Yu & Shu-Heng Chen, 2004. "Using Genetic Programming with Lambda Abstraction to Find Technical Trading Rules," Computing in Economics and Finance 2004 200, Society for Computational Economics.

    Cited by:

    1. Thomas S. Coe & Kittipong Laosethakul, 2021. "Applying Technical Trading Rules to Beat Long-Term Investing: Evidence from Asian Markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(4), pages 587-611, December.

  7. Bin-Tzong Chie & Shu-Heng Chen, 2003. "A Functional-Modularity Approach to Preferences," Computing in Economics and Finance 2003 107, Society for Computational Economics.

    Cited by:

    1. Bin-Tzong Chie & Shu-Heng Chen, 2014. "Non-Price Competition in a Modular Economy," ASSRU Discussion Papers 1401, ASSRU - Algorithmic Social Science Research Unit.
    2. Bin-Tzong Chie & Shu-Heng Chen, 2014. "Competition in a New Industrial Economy: Toward an Agent-Based Economic Model of Modularity," Administrative Sciences, MDPI, vol. 4(3), pages 1-27, July.

  8. Ya-Chi Huang & Shu-Heng Chen, 2003. "Simulating the Evolution of Portfolio Behavior in a Multiple-Asset Agent-Based Artificial Stock Market," Computing in Economics and Finance 2003 62, Society for Computational Economics.

    Cited by:

    1. Serge Hayward, 2004. "Heterogeneous Agents Past and Forward Time Horizons in Setting Up a Computational Model," Computing in Economics and Finance 2004 241, Society for Computational Economics.
    2. Serge Hayward, 2005. "The Role of Heterogeneous Agents’ Past and Forward Time Horizons in Formulating Computational Models," Computational Economics, Springer;Society for Computational Economics, vol. 25(1), pages 25-40, February.

  9. Chia-Hsuan Yeh, Shu-Heng Chen, 2001. "The Influence of Market Size in an Artificial Stock Market: The Approach Based on Genetic Programming," Computing in Economics and Finance 2001 74, Society for Computational Economics.

    Cited by:

    1. Brock, W.A. & Hommes, C.H. & Wagener, F.O.O., 2002. "Evolutionary dynamics in markets with many trader types," CeNDEF Working Papers 02-10, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    2. Lux, Thomas & Schornstein, Sascha, 2005. "Genetic learning as an explanation of stylized facts of foreign exchange markets," Journal of Mathematical Economics, Elsevier, vol. 41(1-2), pages 169-196, February.

  10. Shu-Heng Chen & Chung-Chi Liao & Chi-Hsuan Yeh, 2000. "On The Emergent Properties Of Artificial Stock Markets: Some Initial Evidences," Computing in Economics and Finance 2000 328, Society for Computational Economics.

    Cited by:

    1. Shu-Heng Chen & Chung-Chih Liao & Pei-Jung Chou, 2008. "On the plausibility of sunspot equilibria," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 3(1), pages 25-41, June.
    2. Ke-Hung Lai & Shu-Heng Chen & Ya-Chi Huang, 2005. "Bounded Rationality and the Elasticity Puzzle: What Can We Learn from the Agent-Based Computational Consumption Capital Asset Pricing Model?," Computing in Economics and Finance 2005 207, Society for Computational Economics.

  11. Chia-Hsuan Yeh & Shu-Heng Chen, 2000. "Toward An Integration Of Social Learning And Individual Learning In Agent-Based Computational Stock Markets:The Approach Based On Population Genetic Programming," Computing in Economics and Finance 2000 338, Society for Computational Economics.

    Cited by:

    1. Ryuichi YAMAMOTO, 2005. "Evolution with Individual and Social Learning in an Agent-Based Stock Market," Computing in Economics and Finance 2005 228, Society for Computational Economics.

  12. Chih-Chi Ni & Shu-Heng Chen, 1999. "Simulating the Ecology of Oligopoly Games with Genetic Algorithms," Computing in Economics and Finance 1999 1012, Society for Computational Economics.

    Cited by:

    1. Qi, Chun & Tang, John C.S., 2006. "Foreign direct investment: A genetic algorithm approach," Socio-Economic Planning Sciences, Elsevier, vol. 40(2), pages 143-155, June.
    2. Robert Somogyi & Janos Vincze, 2011. "Price Rigidity and Strategic Uncertainty An Agent-based Approach," CERS-IE WORKING PAPERS 1135, Institute of Economics, Centre for Economic and Regional Studies.

  13. Shu-Heng Chen & Chia-Hsuan Yeh, 1999. "Evolving Traders and the Faculty of the Business School: A New Architecture of the Artificial Stock Market," Computing in Economics and Finance 1999 613, Society for Computational Economics.

    Cited by:

    1. Blake LeBaron, 1999. "Evolution and Time Horizons in an Agent-Based Stock Market," Computing in Economics and Finance 1999 1342, Society for Computational Economics.

  14. Shu-Heng Chen & Chia-Hsuan Yeh, "undated". "Toward a Computable Approach to the Efficient Market Hypothesis: An Application of Genetic Programming," Working Papers _011, University of California at Los Angeles, Center for Computable Economics.

    Cited by:

    1. Carl Chiarella & Xue-Zhong He & Duo Wang, 2004. "A Behavioural Asset Pricing Model with a Time-Varying Second Moment," Research Paper Series 141, Quantitative Finance Research Centre, University of Technology, Sydney.
    2. Manahov, Viktor, 2016. "A note on the relationship between high-frequency trading and latency arbitrage," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 281-296.
    3. Xue-Zhong He & Youwei Li, 2008. "Heterogeneity, convergence, and autocorrelations," Quantitative Finance, Taylor & Francis Journals, vol. 8(1), pages 59-79.
    4. Juan Benjamín Duarte Duarte & Juan Manuel Mascare?nas Pérez-Iñigo, 2014. "Comprobación de la eficiencia débil en los principales mercados financieros latinoamericanos," Estudios Gerenciales, Universidad Icesi, November.
    5. He, Xue-Zhong & Li, Youwei, 2007. "Power-law behaviour, heterogeneity, and trend chasing," Journal of Economic Dynamics and Control, Elsevier, vol. 31(10), pages 3396-3426, October.
    6. Chiarella, Carl & He, Xue-Zhong, 2003. "Heterogeneous Beliefs, Risk, And Learning In A Simple Asset-Pricing Model With A Market Maker," Macroeconomic Dynamics, Cambridge University Press, vol. 7(4), pages 503-536, September.
    7. Changqing Luo & Siyuan Fan & Qi Zhang, 2017. "Investigating the Influence of Green Credit on Operational Efficiency and Financial Performance Based on Hybrid Econometric Models," IJFS, MDPI, vol. 5(4), pages 1-19, November.
    8. Kozhan, Roman & Salmon, Mark, 2012. "The information content of a limit order book: The case of an FX market," Journal of Financial Markets, Elsevier, vol. 15(1), pages 1-28.

Articles

  1. Ching Hsu & Tina Yu & Shu-Heng Chen, 2021. "Narrative economics using textual analysis of newspaper data: new insights into the U.S. Silver Purchase Act and Chinese price level in 1928–1936," Journal of Computational Social Science, Springer, vol. 4(2), pages 761-785, November.

    Cited by:

    1. Vyacheslav V. Volchik & Elena V. Fursa & Elena V. Maslyukova, 2021. "Public administration and development of the Russian innovation system," Upravlenets, Ural State University of Economics, vol. 12(5), pages 32-49, November.

  2. Lin, Hung-Wen & Huang, Jing-Bo & Lin, Kun-Ben & Zhang, Joyce & Chen, Shu-Heng, 2020. "Which is the better fourth factor in China? Reversal or turnover?," Pacific-Basin Finance Journal, Elsevier, vol. 62(C).

    Cited by:

    1. Neszveda, Gábor & Till, Gábor & Timár, Barnabás & Varga, Marcell, 2022. "Is short-term reversal driven by liquidity provision in emerging markets? Evidence from China," Finance Research Letters, Elsevier, vol. 50(C).
    2. Li, Yan & Huo, Jiale & Xu, Yongan & Liang, Chao, 2023. "Belief-based momentum indicator and stock market return predictability," Research in International Business and Finance, Elsevier, vol. 64(C).
    3. Li, Yan & Liang, Chao & L.D. Huynh, Toan, 2022. "A new momentum measurement in the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).

  3. Tai, Chung-Ching & Chen, Shu-Heng & Yang, Lee-Xieng, 2018. "Cognitive ability and earnings performance: Evidence from double auction market experiments," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 409-440.

    Cited by:

    1. Bao, Te & Hommes, Cars & Pei, Jiaoying, 2021. "Expectation formation in finance and macroeconomics: A review of new experimental evidence," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    2. Yan Peng & Jason Shachat & Lijia Wei & S. Sarah Zhang, 2024. "Speed traps: algorithmic trader performance under alternative market balances and structures," Experimental Economics, Springer;Economic Science Association, vol. 27(2), pages 325-350, April.
    3. Choi, Syngjoo & Hahn, Kyu Sup & Kim, Byung-Yeon & Lee, Eungik & Lee, Jungmin & Lee, Sokbae, 2024. "North Korean refugees’ implicit bias against South Korea predicts market earnings," Journal of Development Economics, Elsevier, vol. 169(C).
    4. Nicolas Eber & Patrick Roger & Tristan Roger, 2024. "Finance and intelligence: An overview of the literature," Journal of Economic Surveys, Wiley Blackwell, vol. 38(2), pages 503-554, April.
    5. Huong Trang Kim, 2021. "Do managers’ emotional intelligence matter for SMEs’ business practices?," Economics and Business Letters, Oviedo University Press, vol. 10(3), pages 200-207.
    6. Te Bao & Elizaveta Nekrasova & Tibor Neugebauer & Yohanes E. Riyanto, 2022. "Algorithmic trading in experimental markets with human traders: A literature survey," Chapters, in: Sascha Füllbrunn & Ernan Haruvy (ed.), Handbook of Experimental Finance, chapter 23, pages 302-322, Edward Elgar Publishing.

  4. Shu-Heng Chen & Umberto Gostoli, 2017. "Coordination in the El Farol Bar problem: The role of social preferences and social networks," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(1), pages 59-93, April.
    See citations under working paper version above.
  5. Shu-Heng Chen & Ragupathy Venkatachalam, 2017. "Information aggregation and computational intelligence," Evolutionary and Institutional Economics Review, Springer, vol. 14(1), pages 231-252, June.

    Cited by:

    1. Shu-Heng Chen & Bin-Tzong Chie & Ying-Fang Kao & Ragupathy Venkatachalam, 2019. "Agent-Based Modeling of a Non-tâtonnement Process for the Scarf Economy: The Role of Learning," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 305-341, June.
    2. Dirk Nicolas Wagner, 2020. "Economic patterns in a world with artificial intelligence," Evolutionary and Institutional Economics Review, Springer, vol. 17(1), pages 111-131, January.

  6. Shu-Heng Chen & Ragupathy Venkatachalam, 2017. "Agent-based modelling as a foundation for big data," Journal of Economic Methodology, Taylor & Francis Journals, vol. 24(4), pages 362-383, October.

    Cited by:

    1. Claudius Gräbner & Philipp Heimberger & Jakob Kapeller & Bernhard Schütz, 2018. "Structual change in times of increasing openness," FMM Working Paper 39-2018, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    2. Claudius Gräbner & Philipp Heimberger & Jakob Kapeller & Bernhard Schütz, 2020. "Structural change in times of increasing openness: assessing path dependency in European economic integration," Journal of Evolutionary Economics, Springer, vol. 30(5), pages 1467-1495, November.
    3. Zhou, Wei & Zhong, Guang-Yan & Li, Jiang-Cheng, 2022. "Stability of financial market driven by information delay and liquidity in delay agent-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    4. Xiong Xiong & Yian Cui & Xiaocong Yan & Jun Liu & Shaoyi He, 2020. "Cost-benefit analysis of trading strategies in the stock index futures market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-17, December.
    5. Li, Jiang-Cheng & Tao, Chen & Li, Hai-Feng, 2022. "Dynamic forecasting performance and liquidity evaluation of financial market by Econophysics and Bayesian methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).

  7. Shu-Heng Chen & Bin-Tzong Chie & Tong Zhang, 2015. "Network-Based Trust Games: An Agent-Based Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(3), pages 1-5.

    Cited by:

    1. Tong Zhang & Huiting Liu & Pinghan Liang, 2020. "Social Trust Formation and Credit Accessibility—Evidence from Rural Households in China," Sustainability, MDPI, vol. 12(2), pages 1-14, January.
    2. Gao, Lin, 2016. "Trust and Performance: Exploring Socio-Economic Mechanisms in the “Deep” Network Structure with Agent-Based Modeling," MPRA Paper 75214, University Library of Munich, Germany.
    3. Gao, Lin, 2017. "Between Trust and Performance: Exploring Socio-Economic Mechanisms on Directed Weighted Regular Ring with Agent-Based Modeling," MPRA Paper 78428, University Library of Munich, Germany.

  8. Guo, Bin & Zhang, Wei & Chen, Shu-Heng & Zhang, Yongjie, 2015. "The optimal pricing of a market maker in a heterogeneous agent economy," Finance Research Letters, Elsevier, vol. 14(C), pages 178-187.

    Cited by:

    1. Wu, Liang & Yan, Xin & Fu, Zhiming & Zhang, Rui, 2019. "Do investors choose trade-size according to liquidity, empirical evidence from the S&P 500 index future market," Finance Research Letters, Elsevier, vol. 28(C), pages 275-280.

  9. Tseng, Yi-Heng & Chen, Shu-Heng, 2015. "Limit order book transparency and order aggressiveness at the closing call: Lessons from the TWSE 2012 new information disclosure mechanism," Pacific-Basin Finance Journal, Elsevier, vol. 35(PA), pages 241-272.

    Cited by:

    1. Anh Tu Le & Thai-Ha Le & Wai-Man Liu & Kingsley Y. Fong, 2021. "Dynamic limit order placement strategies: survival analysis with a multiple-spell duration model," Annals of Operations Research, Springer, vol. 297(1), pages 241-275, February.
    2. Balachandran, Balasingham & Faff, Robert, 2015. "Corporate governance, firm value and risk: Past, present, and future," Pacific-Basin Finance Journal, Elsevier, vol. 35(PA), pages 1-12.
    3. Hai-Chuan Xu & Wei Chen & Xiong Xiong & Wei Zhang & Wei-Xing Zhou & H Eugene Stanley, 2016. "Limit-order book resiliency after effective market orders: Spread, depth and intensity," Papers 1602.00731, arXiv.org, revised Feb 2017.

  10. Shu-Heng Chen & Ye-Rong Du & Lee-Xieng Yang, 2014. "Cognitive capacity and cognitive hierarchy: a study based on beauty contest experiments," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 9(1), pages 69-105, April.

    Cited by:

    1. Bao, Te & Hommes, Cars & Pei, Jiaoying, 2021. "Expectation formation in finance and macroeconomics: A review of new experimental evidence," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    2. Stefano Galavotti & Luigi Moretti & Paola Valbonesi, 2014. "Sophisticated Bidders In Beauty-Contest Auctions," "Marco Fanno" Working Papers 0187, Dipartimento di Scienze Economiche "Marco Fanno".
    3. Allred, Sarah & Duffy, Sean & Smith, John, 2014. "Cognitive load and strategic sophistication," MPRA Paper 59441, University Library of Munich, Germany.
    4. Patrick Reinwald & Stephan Leitner & Friederike Wall, 2021. "Limited intelligence and performance-based compensation: An agent-based model of the hidden action problem," Papers 2107.03764, arXiv.org.
    5. Oren Bar-Gill & Christoph Engel, 2020. "Property is Dummy Proof: An Experiment," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2020_02, Max Planck Institute for Research on Collective Goods.
    6. Patrick Reinwald & Stephan Leitner & Friederike Wall, 2021. "Effects of limited and heterogeneous memory in hidden-action situations," Papers 2105.12469, arXiv.org.
    7. Brañas-Garza, Pablo & Smith, John, 2016. "Cognitive abilities and economic behavior," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 64(C), pages 1-4.

  11. Chen, Shu-Heng & Chang, Chia-Ling & Tseng, Yi-Heng, 2014. "Social networks, social interaction and macroeconomic dynamics: How much could Ernst Ising help DSGE?," Research in International Business and Finance, Elsevier, vol. 30(C), pages 312-335.

    Cited by:

    1. Chen, Shu-Heng & Chang, Chia-Ling & Wen, Ming-Chang, 2013. "Social networks and macroeconomic stability," Economics Discussion Papers 2013-4, Kiel Institute for the World Economy (IfW Kiel).

  12. Bin-Tzong Chie & Shu-Heng Chen, 2014. "Competition in a New Industrial Economy: Toward an Agent-Based Economic Model of Modularity," Administrative Sciences, MDPI, vol. 4(3), pages 1-27, July.

    Cited by:

    1. Mihail Busu, 2020. "A Market Concentration Analysis of the Biomass Sector in Romania," Resources, MDPI, vol. 9(6), pages 1-10, May.

  13. Chen, Shu-Heng & Chang, Chia-Ling & Wen, Ming-Chang, 2014. "Social networks and macroeconomic stability," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 8, pages 1-40.
    See citations under working paper version above.
  14. Bin-Tzong Chie & Shu-Heng Chen, 2013. "Non-Price Competition in a Modular Economy. An Agent-Based Computational Model," Economia politica, Società editrice il Mulino, issue 3, pages 273-300.

    Cited by:

    1. Bin-Tzong Chie & Shu-Heng Chen, 2014. "Competition in a New Industrial Economy: Toward an Agent-Based Economic Model of Modularity," Administrative Sciences, MDPI, vol. 4(3), pages 1-27, July.
    2. Ben Vermeulen & Andreas Pyka, 2018. "The Role of Network Topology and the Spatial Distribution and Structure of Knowledge in Regional Innovation Policy: A Calibrated Agent-Based Model Study," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 773-808, October.

  15. Chen, Shu-Heng, 2012. "Varieties of agents in agent-based computational economics: A historical and an interdisciplinary perspective," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 1-25.

    Cited by:

    1. Peter Fratrič & Giovanni Sileno & Sander Klous & Tom Engers, 2022. "Manipulation of the Bitcoin market: an agent-based study," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-29, December.
    2. Bao, Te & Hommes, Cars & Pei, Jiaoying, 2021. "Expectation formation in finance and macroeconomics: A review of new experimental evidence," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    3. Lengnick, Matthias & Krug, Sebastian & Wohltmann, Hans-Werner, 2012. "Money creation and financial instability: An agent-based credit network approach," Economics Working Papers 2012-15, Christian-Albrechts-University of Kiel, Department of Economics.
    4. Alexandru Mandes & Peter Winker, 2015. "Complexity and Model Comparison in Agent Based Modeling of Financial Markets," MAGKS Papers on Economics 201528, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    5. Friederike Wall, 2021. "Modeling Managerial Search Behavior based on Simon's Concept of Satisficing," Papers 2104.14002, arXiv.org, revised May 2021.
    6. Kyle Bahr & Masami Nakagawa, 2017. "The effect of bidirectional opinion diffusion on social license to operate," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 19(4), pages 1235-1245, August.
    7. Gräbner, Claudius, 2015. "Formal Approaches to Socio Economic Policy Analysis - Past and Perspectives," MPRA Paper 61348, University Library of Munich, Germany.
    8. Friederike Wall, 2024. "Incomplete incentive contracts in complex task environments: an agent-based simulation with minimal intelligence agents," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 19(3), pages 523-552, July.
    9. John C. Stevenson, 2021. "Population and Inequality Dynamics in Simple Economies," Papers 2101.09817, arXiv.org, revised Aug 2021.
    10. Joseph Palazzo & Roland Geyer & Sangwon Suh, 2020. "A review of methods for characterizing the environmental consequences of actions in life cycle assessment," Journal of Industrial Ecology, Yale University, vol. 24(4), pages 815-829, August.
    11. Marcel Ausloos & Franck Jovanovic & Christophe Schinckus, 2016. "On the "usual" misunderstandings between econophysics and finance: some clarifications on modelling approaches and efficient market hypothesis," Papers 1606.02045, arXiv.org.
    12. Sebastian Krug & Matthias Lengnick & Hans-Werner Wohltmann, 2014. "The impact of Basel III on financial (in)stability: an agent-based credit network approach," Quantitative Finance, Taylor & Francis Journals, vol. 15(12), pages 1917-1932, December.
    13. Gräbner, Claudius, 2016. "Agent-based computational models– a formal heuristic for institutionalist pattern modelling?," Journal of Institutional Economics, Cambridge University Press, vol. 12(1), pages 241-261, March.
    14. Tesfatsion, Leigh, 2021. "Agent-Based Computational Economics: Overview and Brief History," ISU General Staff Papers 202111080800001125, Iowa State University, Department of Economics.
    15. Sinitskaya, Ekaterina, 2014. "Computational modeling of an economy using elements of artificial intelligence," ISU General Staff Papers 201401010800005291, Iowa State University, Department of Economics.
    16. Jiahua Wang & Hongliang Zhu & Dongxin Li, 2018. "Price Dynamics in an Order-Driven Market with Bayesian Learning," Complexity, Hindawi, vol. 2018, pages 1-15, November.
    17. Shu-Heng Chen & Ye-Rong Du & Lee-Xieng Yang, 2014. "Cognitive capacity and cognitive hierarchy: a study based on beauty contest experiments," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 9(1), pages 69-105, April.
    18. Christos Alexakis & Michael Dowling & Konstantinos Eleftheriou & Michael Polemis, 2021. "Textual Machine Learning: An Application to Computational Economics Research," Post-Print hal-03182910, HAL.
    19. Sinitskaya, Ekaterina & Tesfatsion, Leigh, 2015. "Macroeconomies as constructively rational games," ISU General Staff Papers 201501010800001008, Iowa State University, Department of Economics.
    20. Brewer, Paul & Ratan, Anmol, 2019. "Profitability, efficiency, and inequality in double auction markets with snipers," Journal of Economic Behavior & Organization, Elsevier, vol. 164(C), pages 486-499.
    21. Carl Chiarella & Xue-Zhong He & Remco C.J. Zwinkels, 2014. "Heterogeneous Expectations in Asset Pricing: Empirical Evidence from the S&P500," Research Paper Series 344, Quantitative Finance Research Centre, University of Technology, Sydney.
    22. Emiliano Brancaccio & Mauro Gallegati & Raffaele Giammetti, 2022. "Neoclassical influences in agent‐based literature: A systematic review," Journal of Economic Surveys, Wiley Blackwell, vol. 36(2), pages 350-385, April.
    23. Friederike Wall, 2023. "Modeling managerial search behavior based on Simon’s concept of satisficing," Computational and Mathematical Organization Theory, Springer, vol. 29(2), pages 265-299, June.
    24. Iori, G. & Porter, J., 2012. "Agent-Based Modelling for Financial Markets," Working Papers 12/08, Department of Economics, City University London.
    25. Alessio Emanuele Biondo & Domenico Delli Gatti, 2024. "Introduction to the special issue on two editions of the workshop on economic science with heterogeneous interacting agents, $$24.5{\text {th}}$$ 24.5 th Milan, 2021 (wehia 2021) $$25{\text {th}}$$ 25," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 19(4), pages 579-585, October.
    26. Tara Natarajan, 2018. "Formal Methods for Integrated Socioeconomic Analysis: An Introduction to the Special Issue," Forum for Social Economics, Taylor & Francis Journals, vol. 47(1), pages 1-7, January.
    27. Wood, Aaron D. & Mason, Charles F. & Finnoff, David, 2016. "OPEC, the Seven Sisters, and oil market dominance: An evolutionary game theory and agent-based modeling approach," Journal of Economic Behavior & Organization, Elsevier, vol. 132(PB), pages 66-78.
    28. 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.
    29. Viktoria V. Akberdina & Andrey I. Volodin & Roman V. Gubarev & Evgeniy I. Dzyuba & Fanil’ S. Fayzullin, 2020. "Models of public investment management at regional level," Upravlenets, Ural State University of Economics, vol. 11(1), pages 45-56, March.
    30. Alexandre Truc & Muriel Dal Pont Legrand, 2024. "Agent-Based Models: Impact and Interdisciplinary Influences in Economics," GREDEG Working Papers 2024-19, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    31. Wood, Aaron D. & Berry, Kevin, 2024. "COVID-19 transmission in a resource dependent community with heterogeneous populations: An agent-based modeling approach," Economics & Human Biology, Elsevier, vol. 52(C).
    32. Weijun Zeng & Minqiang Li & Nan Feng, 2017. "The effects of heterogeneous interaction and risk attitude adaptation on the evolution of cooperation," Journal of Evolutionary Economics, Springer, vol. 27(3), pages 435-459, July.
    33. Patrick Reinwald & Stephan Leitner & Friederike Wall, 2021. "Effects of limited and heterogeneous memory in hidden-action situations," Papers 2105.12469, arXiv.org.
    34. Andrew Todd & Peter Beling & William Scherer, 2016. "Crossed and Locked Quotes in a Multi-Market Simulation," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-19, March.

  16. Michael Kampouridis & Shu-Heng Chen & Edward Tsang, 2012. "Microstructure Dynamics And Agent-Based Financial Markets: Can Dinosaurs Return?," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 15(supp0), pages 1-27.

    Cited by:

    1. Andre Veski & Kaire Põder, 2016. "Strategies in the Tallinn School Choice Mechanism," Research in Economics and Business: Central and Eastern Europe, Tallinn School of Economics and Business Administration, Tallinn University of Technology, vol. 8(1).

  17. Kampouridis, Michael & Chen, Shu-Heng & Tsang, Edward, 2012. "Market fraction hypothesis: A proposed test," International Review of Financial Analysis, Elsevier, vol. 23(C), pages 41-54.

    Cited by:

    1. Chen, Shu-Heng & Chang, Chia-Ling & Tseng, Yi-Heng, 2014. "Social networks, social interaction and macroeconomic dynamics: How much could Ernst Ising help DSGE?," Research in International Business and Finance, Elsevier, vol. 30(C), pages 312-335.
    2. Ya-Chi Huang & Chueh-Yung Tsao, 2018. "Discovering Traders’ Heterogeneous Behavior in High-Frequency Financial Data," Computational Economics, Springer;Society for Computational Economics, vol. 51(4), pages 821-846, April.

  18. Shu-Heng Chen & Yi-Lin Hsieh, 2011. "Reinforcement Learning in Experimental Asset Markets," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 37(1), pages 109-133.

    Cited by:

    1. Bao, Te & Hommes, Cars & Pei, Jiaoying, 2021. "Expectation formation in finance and macroeconomics: A review of new experimental evidence," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    2. Chen, Shu-Heng, 2012. "Varieties of agents in agent-based computational economics: A historical and an interdisciplinary perspective," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 1-25.
    3. He, Xue-Zhong & Lin, Shen, 2022. "Reinforcement Learning Equilibrium in Limit Order Markets," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).

  19. Binner, Jane & Chen, Shu-Heng & Lai, Ke-Hung & Mullineux, Andrew & Swofford, James L., 2011. "Do the ASEAN countries and Taiwan form a common currency area?," Journal of International Money and Finance, Elsevier, vol. 30(7), pages 1429-1435.

    Cited by:

    1. Andy Mullineux, 2015. "Implications Of The Eurozone Crisis For Monetary Unions In Sub-Saharan Africa," The African Finance Journal, Africagrowth Institute, vol. 17(1), pages 21-40.
    2. Jamshaid ur Rehman & Tasneem Zafar & Shabbir Ahmad & Aftab Anwar, 2022. "In Search of Common Currency Anchor for ASEAN+3+3 Countries," Journal of Policy Research (JPR), Research Foundation for Humanity (RFH), vol. 8(3), pages 237-264, September.

  20. Shu‐Heng Chen & Shu G. Wang, 2011. "Emergent Complexity In Agent‐Based Computational Economics," Journal of Economic Surveys, Wiley Blackwell, vol. 25(3), pages 527-546, July.

    Cited by:

    1. Özge Dilaver & Robert Jump & Paul Levine, 2016. "Agent-based Macroeconomics and Dynamic Stochastic General Equilibrium Models: Where do we go from here?," School of Economics Discussion Papers 0116, School of Economics, University of Surrey.
    2. Christopher Boyer & B. Brorsen, 2014. "Implications of a Reserve Price in an Agent-Based Common-Value Auction," Computational Economics, Springer;Society for Computational Economics, vol. 43(1), pages 33-51, January.
    3. Timothy J. Foxon & Jonathan Köhler & Jonathan Michie & Christine Oughton, 2013. "Towards a new complexity economics for sustainability," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 37(1), pages 187-208.

  21. Jie-Jun Tseng & Sai-Ping Li & Shu-Heng Chen & Sun-Chong Wang, 2009. "Emergence Of Scale-Free Networks In Markets," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 12(01), pages 87-97.

    Cited by:

    1. Chen, Shu-Heng, 2012. "Varieties of agents in agent-based computational economics: A historical and an interdisciplinary perspective," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 1-25.
    2. Zhi-Qiang Jiang & Wen-Jie Xie & Xiong Xiong & Wei Zhang & Yong-Jie Zhang & W. -X. Zhou, 2012. "Trading networks, abnormal motifs and stock manipulation," Papers 1301.0007, arXiv.org.
    3. Fabio Della Rossa & Lorenzo Giannini & Pietro DeLellis, 2020. "Herding or wisdom of the crowd? Controlling efficiency in a partially rational financial market," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-16, September.

  22. Chen, Shu-Heng & Huang, Ya-Chi, 2008. "Risk preference, forecasting accuracy and survival dynamics: Simulations based on a multi-asset agent-based artificial stock market," Journal of Economic Behavior & Organization, Elsevier, vol. 67(3-4), pages 702-717, September.

    Cited by:

    1. Kluger, Brian D. & McBride, Mark E., 2011. "Intraday trading patterns in an intelligent autonomous agent-based stock market," Journal of Economic Behavior & Organization, Elsevier, vol. 79(3), pages 226-245, August.
    2. Ascensión Andina-Díaz & José A. García-Martínez & Antonio Parravano, 2019. "The market for scoops: a dynamic approach," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(2), pages 175-206, June.
    3. Olivier Brandouy & Philippe Mathieu & Iryna Veryzhenko, 2012. "Risk Aversion Impact on Investment Strategy Performance: A Multi Agent-Based Analysis," Post-Print hal-00826144, HAL.
    4. Hai-Chuan Xu & Wei Zhang & Xiong Xiong & Wei-Xing Zhou, 2014. "Wealth share analysis with "fundamentalist/chartist" heterogeneous agents," Papers 1405.5939, arXiv.org.
    5. Ya-Chi Huang, 2017. "Exploring issues of market inefficiency by the role of forecasting accuracy in survivability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(2), pages 167-191, July.
    6. Rangan Gupta & Lardo Stander & Andrea Vaona, 2023. "Openness and growth: Is the relationship non‐linear?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 3071-3099, July.
    7. 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.
    8. Iryna Veryzhenko, 2021. "Who gains and who loses on stock markets? Risk preferences and timing matter," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(2), pages 143-155, April.
    9. Carl Chiarella & Roberto Dieci & Xue-Zhong He & Kai Li, 2013. "An evolutionary CAPM under heterogeneous beliefs," Annals of Finance, Springer, vol. 9(2), pages 185-215, May.
    10. Schmitt, Noemi & Westerhoff, Frank, 2014. "Speculative behavior and the dynamics of interacting stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 45(C), pages 262-288.
    11. Yang, ChunXia & Hu, Sen & Xia, BingYing, 2012. "The endogenous dynamics of financial markets: Interaction and information dissemination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(12), pages 3513-3525.
    12. Xue-Zhong He & Kai Li & Chuncheng Wang, 2018. "Time-varying economic dominance in financial markets: A bistable dynamics approach," Published Paper Series 2018-1, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    13. 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.
    14. Ke-Hung Lai & Shu-Heng Chen & Ya-Chi Huang, 2005. "Bounded Rationality and the Elasticity Puzzle: What Can We Learn from the Agent-Based Computational Consumption Capital Asset Pricing Model?," Computing in Economics and Finance 2005 207, Society for Computational Economics.
    15. Kai Li, 2014. "Asset Price Dynamics with Heterogeneous Beliefs and Time Delays," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2014, January-A.
    16. Ibrahim Filiz & Jan René Judek & Marco Lorenz & Markus Spiwoks, 2021. "Sticky Stock Market Analysts," JRFM, MDPI, vol. 14(12), pages 1-27, December.

  23. Chen, Shu-Heng & Chie, Bin-Tzong, 2008. "Lottery markets design, micro-structure, and macro-behavior: An ACE approach," Journal of Economic Behavior & Organization, Elsevier, vol. 67(2), pages 463-480, August.

    Cited by:

    1. Coronel-Brizio, H.F. & Hernández-Montoya, A.R. & Rapallo, F. & Scalas, E., 2008. "Statistical auditing and randomness test of lotto k/N-type games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(25), pages 6385-6390.
    2. Gabrielyan, Gnel & Just, David R., 2017. "Economic Factors Affecting Lottery Sales: An Examination of Maine State Lottery Sales," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258419, Agricultural and Applied Economics Association.
    3. Kent Grote & Victor Matheson, 2011. "The Economics of Lotteries: A Survey of the Literature," Working Papers 1109, College of the Holy Cross, Department of Economics.
    4. G. Fagiolo & A. Roventini, 2009. "On the Scientific Status of Economic Policy: A Tale of Alternative Paradigms," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 6.
    5. Rose Baker & David Forrest & Levi Pérez, 2016. "The compatriot win effect on national sales of a multicountry lottery," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 65(4), pages 603-618, August.
    6. Alexis DIRER, 2010. "Equilibrium Lottery Games and Preferences Under Risk," LEO Working Papers / DR LEO 550, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    7. Michael Coon & Gwyneth Whieldon, 2016. "Elasticity of Demand and Optimal Prize Distribution for Instant Lottery Games," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 44(4), pages 457-469, December.

  24. Shu-Heng Chen & Chung-Chih Liao & Pei-Jung Chou, 2008. "On the plausibility of sunspot equilibria," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 3(1), pages 25-41, June.

    Cited by:

    1. Chen, Shu-Heng & Gostoli, Umberto, 2013. "Coordination in the El Farol Bar problem: The role of social preferences and social networks," Economics Discussion Papers 2013-20, Kiel Institute for the World Economy (IfW Kiel).

  25. Jason M Barr & Troy Tassier & Leanne J Ussher & Blake LeBaron & Shu-Heng Chen & Shyam Sunder, 2008. "The Future of Agent-Based Research in Economics: A Panel Discussion, Eastern Economic Association Annual Meetings, Boston, March 7, 20081," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 34(4), pages 550-565.

    Cited by:

    1. Borrill, Paul L. & Tesfatsion, Leigh, 2011. "Agent-based modeling: the right mathematics for the social sciences?," ISU General Staff Papers 201106290700001090, Iowa State University, Department of Economics.
    2. Jason M. Barr, 2019. "Domenico Delli Gatti, Giorgio Fagiolo, Mauro Gallegati, Matteo Richiardi and Alberto Russo (eds): Agent-Based Models in Economics: A Toolkit," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 45(3), pages 477-480, June.
    3. Tesfatsion, Leigh, 2011. "Agent-based Modeling and Institutional Design," ISU General Staff Papers 201101010800001471, Iowa State University, Department of Economics.

  26. S. C. Wang & J. J. Tseng & C. C. Tai & K. H. Lai & W. S. Wu & S. H. Chen & S. P. Li, 2008. "Network topology of an experimental futures exchange," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 62(1), pages 105-111, March.
    See citations under working paper version above.
  27. Shu-Heng Chen & Chung-Ching Tai, 2006. "Republication: On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach," Computational Economics, Springer;Society for Computational Economics, vol. 28(4), pages 313-331, November.

    Cited by:

    1. Chen, Shu-Heng & Chie, Bin-Tzong, 2008. "Lottery markets design, micro-structure, and macro-behavior: An ACE approach," Journal of Economic Behavior & Organization, Elsevier, vol. 67(2), pages 463-480, August.

  28. Shu-Heng Chen & Chung-Ching Tai, 2006. "On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach," Computational Economics, Springer;Society for Computational Economics, vol. 28(1), pages 51-69, August.

    Cited by:

    1. Chen, Shu-Heng & Chie, Bin-Tzong, 2008. "Lottery markets design, micro-structure, and macro-behavior: An ACE approach," Journal of Economic Behavior & Organization, Elsevier, vol. 67(2), pages 463-480, August.

  29. Shu-Heng Chen, 2006. "Graphs, Networks And Ace," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 2(03), pages 299-314.

    Cited by:

    1. Chen, Shu-Heng, 2012. "Varieties of agents in agent-based computational economics: A historical and an interdisciplinary perspective," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 1-25.
    2. Shu-Heng Chen & Sai-Ping Li, 2011. "Econophysics: Bridges over a Turbulent Current," Papers 1107.5373, arXiv.org.

  30. Jane M. Binner & Alicia M. Gazely & Shu‐Heng Chen & Bin‐Tzong Chie, 2004. "Financial Innovation and Divisia Money in Taiwan: Comparative Evidence from Neural Network and Vector Error‐Correction Forecasting Models," Contemporary Economic Policy, Western Economic Association International, vol. 22(2), pages 213-224, April.

    Cited by:

    1. Makram El-Shagi & Kiril Tochkov, 2021. "Divisia Monetary Aggregates for Russia: Money Demand, GDP Nowcasting, and the Price Puzzle," CFDS Discussion Paper Series 2021/1, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
    2. Khan, Rana Ejaz Ali & Hye, Qazi Muhammad Adnan, 2011. "Financial Liberalization And Demand For Money: A Case of Pakistan," MPRA Paper 34795, University Library of Munich, Germany.
    3. Panayotis G. Michaelides & Efthymios G. Tsionas & Angelos T. Vouldis & Konstantinos N. Konstantakis & Panagiotis Patrinos, 2018. "A Semi-Parametric Non-linear Neural Network Filter: Theory and Empirical Evidence," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 637-675, March.
    4. Yong Qin & Zeshui Xu & Xinxin Wang & Marinko Skare, 2024. "Artificial Intelligence and Economic Development: An Evolutionary Investigation and Systematic Review," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 1736-1770, March.
    5. Jane M. Binner & logan J. Kelly, 2017. "Modelling Money Shocks in a Small Open Economy: The Case of Taiwan," Manchester School, University of Manchester, vol. 85, pages 104-120, September.
    6. James, Gregory A., 2005. "Money demand and financial liberalization in Indonesia," Journal of Asian Economics, Elsevier, vol. 16(5), pages 817-829, October.
    7. Masudul Hasan Adil & Neeraj Hatekar & Pravakar Sahoo, 2020. "The Impact of Financial Innovation on the Money Demand Function: An Empirical Verification in India," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 14(1), pages 28-61, February.
    8. Jane Binner & Rakesh Bissoondeeal & Thomas Elger & Alicia Gazely & Andrew Mullineux, 2005. "A comparison of linear forecasting models and neural networks: an application to Euro inflation and Euro Divisia," Applied Economics, Taylor & Francis Journals, vol. 37(6), pages 665-680.
    9. Rosita Capurro & Michele Galeotti & Stefano Garzella, 2018. ""Mondo reale-tradizionale" e "mondo digitale", strategie aziendali e web intelligence: il futuro del controllo e della gestione delle informazioni," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2018(2 Suppl.), pages 83-111.
    10. Farzan Aminian & E. Suarez & Mehran Aminian & Daniel Walz, 2006. "Forecasting Economic Data with Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 28(1), pages 71-88, August.
    11. Shahid IQBAL & Maqbool H. SIAL, 2016. "Projections of Inflation Dynamics for Pakistan: GMDH Approach," Journal of Economics and Political Economy, KSP Journals, vol. 3(3), pages 536-559, September.

  31. Shu-Heng Chen & Chung-Ching Tai, 2003. "Trading Restrictions, Price Dynamics And Allocative Efficiency In Double Auction Markets: Analysis Based On Agent-Based Modeling And Simulations," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 6(03), pages 283-302.

    Cited by:

    1. Shu-Heng Chen & Chung-Ching Tai, 2006. "Republication: On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach," Computational Economics, Springer;Society for Computational Economics, vol. 28(4), pages 313-331, November.
    2. Yeh, Chia-Hsuan, 2008. "The effects of intelligence on price discovery and market efficiency," Journal of Economic Behavior & Organization, Elsevier, vol. 68(3-4), pages 613-625, December.
    3. Chen, Shu-Heng, 2012. "Varieties of agents in agent-based computational economics: A historical and an interdisciplinary perspective," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 1-25.
    4. Chia-Hsuan Yeh, 2007. "The role of intelligence in time series properties," Computational Economics, Springer;Society for Computational Economics, vol. 30(2), pages 95-123, September.
    5. Shu-Heng Chen & Chung-Ching Tai, 2006. "On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach," Computational Economics, Springer;Society for Computational Economics, vol. 28(1), pages 51-69, August.
    6. Marta Posada & Adolfo López-Paredes, 2007. "How to Choose the Bidding Strategy in Continuous Double Auctions: Imitation Versus Take-The-Best Heuristics," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(1), pages 1-6.

  32. Jane M. Binner & Alicia M. Gazely & Shu-Heng Chen, 2002. "Financial innovation and Divisia monetary indices in Taiwan: a neural network approach," The European Journal of Finance, Taylor & Francis Journals, vol. 8(2), pages 238-247, June.

    Cited by:

    1. Panayotis G. Michaelides & Efthymios G. Tsionas & Angelos T. Vouldis & Konstantinos N. Konstantakis & Panagiotis Patrinos, 2018. "A Semi-Parametric Non-linear Neural Network Filter: Theory and Empirical Evidence," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 637-675, March.
    2. Alicia Gazely & Jane Binner & Graham Kendall, 2004. "Co-evolution vs. Neural Networks; An Evaluation of UK Risky Money," Computing in Economics and Finance 2004 258, Society for Computational Economics.
    3. Jane Binner & Rakesh Bissoondeeal & Thomas Elger & Alicia Gazely & Andrew Mullineux, 2005. "A comparison of linear forecasting models and neural networks: an application to Euro inflation and Euro Divisia," Applied Economics, Taylor & Francis Journals, vol. 37(6), pages 665-680.
    4. Farzan Aminian & E. Suarez & Mehran Aminian & Daniel Walz, 2006. "Forecasting Economic Data with Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 28(1), pages 71-88, August.

  33. Chen, Shu-Heng & Yeh, Chia-Hsuan, 2002. "On the emergent properties of artificial stock markets: the efficient market hypothesis and the rational expectations hypothesis," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 217-239, October.

    Cited by:

    1. Dieci, Roberto & Foroni, Ilaria & Gardini, Laura & He, Xue-Zhong, 2006. "Market mood, adaptive beliefs and asset price dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 29(3), pages 520-534.
    2. Carl Chiarella & Xue-Zhong He & Duo Wang, 2004. "A Behavioural Asset Pricing Model with a Time-Varying Second Moment," Research Paper Series 141, Quantitative Finance Research Centre, University of Technology, Sydney.
    3. Xue-Zhong He, 2003. "Asset Pricing, Volatility and Market Behaviour: A Market Fraction Approach," Research Paper Series 95, Quantitative Finance Research Centre, University of Technology, Sydney.
    4. Xue-Zhong He & Youwei Li, 2017. "The adaptiveness in stock markets: testing the stylized facts in the DAX 30," Journal of Evolutionary Economics, Springer, vol. 27(5), pages 1071-1094, November.
    5. Donald Lien & Y. K. Tse & Xibin Zhang, 2003. "Structural change and lead-lag relationship between the Nikkei spot index and futures price: a genetic programming approach," Quantitative Finance, Taylor & Francis Journals, vol. 3(2), pages 136-144.
    6. Roy L. Hayes & Peter A. Beling & William T. Scherer, 2013. "Action-based feature representation for reverse engineering trading strategies," Environment Systems and Decisions, Springer, vol. 33(3), pages 413-426, September.
    7. Alexandru Mandes & Peter Winker, 2015. "Complexity and Model Comparison in Agent Based Modeling of Financial Markets," MAGKS Papers on Economics 201528, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    8. Xue-Zhong He & Youwei Li, 2005. "Long Memory, Heterogeneity and Trend Chasing," Research Paper Series 148, Quantitative Finance Research Centre, University of Technology, Sydney.
    9. Kluger, Brian D. & McBride, Mark E., 2011. "Intraday trading patterns in an intelligent autonomous agent-based stock market," Journal of Economic Behavior & Organization, Elsevier, vol. 79(3), pages 226-245, August.
    10. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2001. "Microscopic Models of Financial Markets," Papers cond-mat/0110354, arXiv.org.
    11. Lucy F. Ackert & Bryan K. Church & Richard Deaves, 2003. "Emotion and financial markets," Economic Review, Federal Reserve Bank of Atlanta, vol. 88(Q2), pages 33-41.
    12. Chiarella, Carl & Dieci, Roberto & Gardini, Laura, 2006. "Asset price and wealth dynamics in a financial market with heterogeneous agents," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1755-1786.
    13. Goodman, James, 2014. "Evidence for ecological learning and domain specificity in rational asset pricing and market efficiency," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 48(C), pages 27-39.
    14. Syeda Tayyaba Ijaz & Rabia Komal, 2015. "Role Of Hurst Exponent In Prediction Of Market Efficiency In Kse-100 Index," IBT Journal of Business Studies (JBS), Ilma University, Faculty of Management Science, vol. 11(2), pages 41-54.
    15. Georges, Christophre, 2006. "Learning with misspecification in an artificial currency market," Journal of Economic Behavior & Organization, Elsevier, vol. 60(1), pages 70-84, May.
    16. Xue-Zhong He & Youwei Li, 2008. "Heterogeneity, convergence, and autocorrelations," Quantitative Finance, Taylor & Francis Journals, vol. 8(1), pages 59-79.
    17. Carl Chiarella & Xue-Zhong He & Duo Wang, 2004. "Statistical Properties of a Heterogeneous Asset Price Model with Time-Varying Second Moment," Research Paper Series 142, Quantitative Finance Research Centre, University of Technology, Sydney.
    18. Yeh, Chia-Hsuan, 2008. "The effects of intelligence on price discovery and market efficiency," Journal of Economic Behavior & Organization, Elsevier, vol. 68(3-4), pages 613-625, December.
    19. Urquhart, Andrew & Hudson, Robert, 2013. "Efficient or adaptive markets? Evidence from major stock markets using very long run historic data," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 130-142.
    20. He, Xue-Zhong & Li, Youwei, 2007. "Power-law behaviour, heterogeneity, and trend chasing," Journal of Economic Dynamics and Control, Elsevier, vol. 31(10), pages 3396-3426, October.
    21. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Kiel Working Papers 1426, Kiel Institute for the World Economy (IfW Kiel).
    22. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Economics Working Papers 2008-08, Christian-Albrechts-University of Kiel, Department of Economics.
    23. Ackert, Lucy F. & Church, Bryan K. & Zhang, Ping, 2008. "What affects the market's ability to adjust for optimistic forecast bias? Evidence from experimental asset markets," Journal of Economic Behavior & Organization, Elsevier, vol. 66(2), pages 358-372, May.
    24. Alfarano, Simone & Lux, Thomas & Wagner, Friedrich, 2008. "Time variation of higher moments in a financial market with heterogeneous agents: An analytical approach," Journal of Economic Dynamics and Control, Elsevier, vol. 32(1), pages 101-136, January.
    25. Alfarano, Simone & Lux, Thomas, 2006. "A minimal noise trader model with realistic time series properties," Economics Working Papers 2006-11, Christian-Albrechts-University of Kiel, Department of Economics.
    26. Benink, Harald A. & Gordillo, José Luis & Pardo, Juan Pablo & Stephens, Christopher R., 2010. "Market efficiency and learning in an artificial stock market: A perspective from Neo-Austrian economics," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 668-688, September.
    27. Shimokawa, Tetsuya & Suzuki, Kyoko & Misawa, Tadanobu, 2007. "An agent-based approach to financial stylized facts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(1), pages 207-225.
    28. Vinod Cheriyan & Anton J. Kleywegt, 2016. "A dynamical systems model of price bubbles and cycles," Quantitative Finance, Taylor & Francis Journals, vol. 16(2), pages 309-336, February.
    29. Georges, Christophre & Wallace, John C., 2009. "Learning Dynamics And Nonlinear Misspecification In An Artificial Financial Market," Macroeconomic Dynamics, Cambridge University Press, vol. 13(5), pages 625-655, November.
    30. Emiliano Brancaccio & Mauro Gallegati & Raffaele Giammetti, 2022. "Neoclassical influences in agent‐based literature: A systematic review," Journal of Economic Surveys, Wiley Blackwell, vol. 36(2), pages 350-385, April.
    31. Youwei Li & Xue-Zhong (Tony) He, 2005. "Heterogeneity, Profitability and Autocorrelations," Computing in Economics and Finance 2005 244, Society for Computational Economics.
    32. Annarita COLASANTE & Antonio PALESTRINI & Alberto RUSSO & Mauro GALLEGATI, 2015. "Adaptive Expectations with Correction Bias: Evidence from the lab," Working Papers 409, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    33. Colasante, Annarita & Palestrini, Antonio & Russo, Alberto & Gallegati, Mauro, 2017. "Adaptive expectations versus rational expectations: Evidence from the lab," International Journal of Forecasting, Elsevier, vol. 33(4), pages 988-1006.
    34. Lux, Thomas & Alfarano, Simone, 2016. "Financial power laws: Empirical evidence, models, and mechanisms," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 3-18.
    35. Alfarano, Simone & Lux, Thomas, 2007. "A Noise Trader Model As A Generator Of Apparent Financial Power Laws And Long Memory," Macroeconomic Dynamics, Cambridge University Press, vol. 11(S1), pages 80-101, November.
    36. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2007. "Agent-based Models of Financial Markets," Papers physics/0701140, arXiv.org.
    37. Ladley, Daniel & Lensberg, Terje & Palczewski, Jan & Schenk-Hoppé, Klaus Reiner, 2015. "Fragmentation and stability of markets," Journal of Economic Behavior & Organization, Elsevier, vol. 119(C), pages 466-481.
    38. Harald A. Benink & Jose Luis Gordillo & Juan Pablo Pardo & Christopher R. Stephens, 2004. "A Study of Neo-Austrian Economics using an Artificial Stock Market," Finance 0411038, University Library of Munich, Germany.
    39. Alexandru Mandes, 2014. "Order Placement in a Continuous Double Auction Agent Based Model," MAGKS Papers on Economics 201443, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    40. Lux, Thomas, 2006. "Financial power laws: Empirical evidence, models, and mechanism," Economics Working Papers 2006-12, Christian-Albrechts-University of Kiel, Department of Economics.
    41. Zhu, Mei & Chiarella, Carl & He, Xue-Zhong & Wang, Duo, 2009. "Does the market maker stabilize the market?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(15), pages 3164-3180.
    42. 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).
    43. Manahov, Viktor & Urquhart, Andrew, 2021. "The efficiency of Bitcoin: A strongly typed genetic programming approach to smart electronic Bitcoin markets," International Review of Financial Analysis, Elsevier, vol. 73(C).

  34. Chen, Shu-Heng & Yeh, Chia-Hsuan, 2001. "Evolving traders and the business school with genetic programming: A new architecture of the agent-based artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 363-393, March.

    Cited by:

    1. Frank H. Westerhoff, 2009. "Exchange Rate Dynamics: A Nonlinear Survey," Chapters, in: J. Barkley Rosser Jr. (ed.), Handbook of Research on Complexity, chapter 11, Edward Elgar Publishing.
    2. Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, University Library of Munich, Germany, revised 15 Aug 2002.
    3. 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.
    4. Pyo, Dong-Jin, 2014. "A Multi-Factor Model of Heterogeneous Traders in a Dynamic Stock Market," Staff General Research Papers Archive 37358, Iowa State University, Department of Economics.
    5. Mario A Bertella & Felipe R Pires & Ling Feng & Harry Eugene Stanley, 2014. "Confidence and the Stock Market: An Agent-Based Approach," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-9, January.
    6. Donald Lien & Y. K. Tse & Xibin Zhang, 2003. "Structural change and lead-lag relationship between the Nikkei spot index and futures price: a genetic programming approach," Quantitative Finance, Taylor & Francis Journals, vol. 3(2), pages 136-144.
    7. Taisei Kaizoji, 2003. "Speculative bubbles and fat tail phenomena in a heterogeneous agent model," Papers nlin/0312040, arXiv.org.
    8. Alexandru Mandes & Peter Winker, 2015. "Complexity and Model Comparison in Agent Based Modeling of Financial Markets," MAGKS Papers on Economics 201528, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    9. Blake LeBaron, 1999. "Evolution and Time Horizons in an Agent-Based Stock Market," Computing in Economics and Finance 1999 1342, Society for Computational Economics.
    10. Guglielmo Maria Caporale & Antoaneta Serguieva & Hao Wu, 2009. "Financial contagion: evolutionary optimization of a multinational agent‐based model," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 16(1‐2), pages 111-125, January.
    11. Chen, Shu-Heng & Yeh, Chia-Hsuan, 2002. "On the emergent properties of artificial stock markets: the efficient market hypothesis and the rational expectations hypothesis," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 217-239, October.
    12. 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.
    13. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2001. "Microscopic Models of Financial Markets," Papers cond-mat/0110354, arXiv.org.
    14. 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.
    15. Yu, Song-min & Fan, Ying & Zhu, Lei & Eichhammer, Wolfgang, 2020. "Modeling the emission trading scheme from an agent-based perspective: System dynamics emerging from firms’ coordination among abatement options," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1113-1128.
    16. Yeh, Chia-Hsuan & Yang, Chun-Yi, 2010. "Examining the effectiveness of price limits in an artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 34(10), pages 2089-2108, October.
    17. Llacay, Bàrbara & Peffer, Gilbert, 2017. "Impact of value-at-risk models on market stability," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 223-256.
    18. Syeda Tayyaba Ijaz & Rabia Komal, 2015. "Role Of Hurst Exponent In Prediction Of Market Efficiency In Kse-100 Index," IBT Journal of Business Studies (JBS), Ilma University, Faculty of Management Science, vol. 11(2), pages 41-54.
    19. Shu-Heng Chen & Chung-Ching Tai, 2006. "Republication: On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach," Computational Economics, Springer;Society for Computational Economics, vol. 28(4), pages 313-331, November.
    20. Pyo, Dong-Jin, 2015. "Animal spirits and stock market dynamics," ISU General Staff Papers 201501010800005596, Iowa State University, Department of Economics.
    21. Georges, Christophre, 2006. "Learning with misspecification in an artificial currency market," Journal of Economic Behavior & Organization, Elsevier, vol. 60(1), pages 70-84, May.
    22. Yeh, Chia-Hsuan, 2008. "The effects of intelligence on price discovery and market efficiency," Journal of Economic Behavior & Organization, Elsevier, vol. 68(3-4), pages 613-625, December.
    23. Tesfatsion, Leigh, 2021. "Agent-Based Computational Economics: Overview and Brief History," ISU General Staff Papers 202111080800001125, Iowa State University, Department of Economics.
    24. Dong-Jin Pyo, 2017. "A multi-factor model of heterogeneous traders in a dynamic stock market," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1416902-141, January.
    25. Chia-Hsuan Yeh & Chun-Yi Yang, 2013. "Do price limits hurt the market?," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 125-153, April.
    26. Casari, Marco, 2008. "Markets in equilibrium with firms out of equilibrium: A simulation study," Journal of Economic Behavior & Organization, Elsevier, vol. 65(2), pages 261-276, February.
    27. Raja Mazhar Hameed & Abdul Rafae Mazhar Raja & Nida Zahid, 2023. "Herding Spillover among the Stock Markets: Pakistan & China Covering Covid-19 and Its Repercussions," Journal of Policy Research (JPR), Research Foundation for Humanity (RFH), vol. 9(2), pages 257-267.
    28. Florian Hauser & Jürgen Huber & Bob Kaempff, 2015. "Costly Information in Markets with Heterogeneous Agents: A Model with Genetic Programming," Computational Economics, Springer;Society for Computational Economics, vol. 46(2), pages 205-229, August.
    29. Noemi Schmitt & Frank Westerhoff, 2017. "Herding behaviour and volatility clustering in financial markets," Quantitative Finance, Taylor & Francis Journals, vol. 17(8), pages 1187-1203, August.
    30. Kyubin Yim & Gabjin Oh & Seunghwan Kim, 2016. "Understanding Financial Market States Using an Artificial Double Auction Market," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-15, March.
    31. Elena G. Irwin, 2010. "New Directions For Urban Economic Models Of Land Use Change: Incorporating Spatial Dynamics And Heterogeneity," Journal of Regional Science, Wiley Blackwell, vol. 50(1), pages 65-91, February.
    32. Georges, Christophre & Wallace, John C., 2009. "Learning Dynamics And Nonlinear Misspecification In An Artificial Financial Market," Macroeconomic Dynamics, Cambridge University Press, vol. 13(5), pages 625-655, November.
    33. Manahov, Viktor & Hudson, Robert & Gebka, Bartosz, 2014. "Does high frequency trading affect technical analysis and market efficiency? And if so, how?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 28(C), pages 131-157.
    34. Binghui Wu & Tingting Duan, 2019. "Nonlinear Dynamics Characteristic of Risk Contagion in Financial Market Based on Agent Modeling and Complex Network," Complexity, Hindawi, vol. 2019, pages 1-12, June.
    35. Schmitt, Noemi & Schwartz, Ivonne & Westerhoff, Frank H., 2020. "Heterogeneous speculators and stock market dynamics: A simple agent-based computational model," BERG Working Paper Series 160, Bamberg University, Bamberg Economic Research Group.
    36. Emiliano Brancaccio & Mauro Gallegati & Raffaele Giammetti, 2022. "Neoclassical influences in agent‐based literature: A systematic review," Journal of Economic Surveys, Wiley Blackwell, vol. 36(2), pages 350-385, April.
    37. Shu-Heng Chan & Shu G. Wang, 2010. "Emergent Complexity in Agent-Based Computational Economics," ASSRU Discussion Papers 1017, ASSRU - Algorithmic Social Science Research Unit.
    38. Noemi Schmitt & Frank Westerhoff, 2017. "Heterogeneity, spontaneous coordination and extreme events within large-scale and small-scale agent-based financial market models," Journal of Evolutionary Economics, Springer, vol. 27(5), pages 1041-1070, November.
    39. Jaqueson K. Galimberti & Sergio da Silva, 2012. "An empirical case against the use of genetic-based learning classifier systems as forecasting devices," Economics Bulletin, AccessEcon, vol. 32(1), pages 354-369.
    40. 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.
    41. Floortje Alkemade & Han Poutré & Hans Amman, 2006. "Robust Evolutionary Algorithm Design for Socio-economic Simulation," Computational Economics, Springer;Society for Computational Economics, vol. 28(4), pages 355-370, November.
    42. Kopp, Thomas & Salecker, Jan, 2020. "How traders influence their neighbours: Modelling social evolutionary processes and peer effects in agricultural trade networks," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
    43. Ryuichi YAMAMOTO, 2005. "Evolution with Individual and Social Learning in an Agent-Based Stock Market," Computing in Economics and Finance 2005 228, Society for Computational Economics.
    44. Thomas Kopp & Jan Salecker, 2018. "Modelling Social Evolutionary Processes and Peer Effects in Agricultural Trade Networks: the Rubber Value Chain in Indonesia," Papers 1811.11476, arXiv.org.
    45. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2007. "Agent-based Models of Financial Markets," Papers physics/0701140, arXiv.org.
    46. Sergiy Gerasymchuk, 2008. "Asset return and wealth dynamics with reference dependent preferences and heterogeneous beliefs," Working Papers 160, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    47. Wlademir Prates & Newton Da Costa Jr & Manuel Rocha Armada & Sergio Da Silva, 2019. "Propensity to sell stocks in an artificial stock market," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-12, April.
    48. Songtao Wu & Jianmin He & Chao Wang, 2017. "Effects of Common Factors on Dynamics of Stocks Traded by Investors with Limited Information Capacity," Discrete Dynamics in Nature and Society, Hindawi, vol. 2017, pages 1-15, September.
    49. Shu-Heng Chen & Chung-Ching Tai, 2006. "On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach," Computational Economics, Springer;Society for Computational Economics, vol. 28(1), pages 51-69, August.
    50. Valentyn Panchenko & Sergiy Gerasymchuk & Oleg V. Pavlov, 2007. "Asset price dynamics with small world interactions under hetereogeneous beliefs," Working Papers 149, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    51. Luca Grilli & Domenico Santoro, 2022. "Forecasting financial time series with Boltzmann entropy through neural networks," Computational Management Science, Springer, vol. 19(4), pages 665-681, October.
    52. Boer-Sorban, K. & Kaymak, U. & de Bruin, A., 2005. "A Modular Agent-Based Environment for Studying Stock Markets," ERIM Report Series Research in Management ERS-2005-017-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    53. Thomas Holtfort, 2019. "From standard to evolutionary finance: a literature survey," Management Review Quarterly, Springer, vol. 69(2), pages 207-232, June.
    54. Taisei Kaizoji, 2003. "Intermittent chaos in a model of financial markets with heterogeneous agents," Papers nlin/0312065, arXiv.org.
    55. Ke-Hung Lai & Shu-Heng Chen & Ya-Chi Huang, 2005. "Bounded Rationality and the Elasticity Puzzle: What Can We Learn from the Agent-Based Computational Consumption Capital Asset Pricing Model?," Computing in Economics and Finance 2005 207, Society for Computational Economics.
    56. Shu‐Heng Chen & Shu G. Wang, 2011. "Emergent Complexity In Agent‐Based Computational Economics," Journal of Economic Surveys, Wiley Blackwell, vol. 25(3), pages 527-546, July.
    57. Tesfatsion, Leigh S., 2001. "Introduction to the Special Issue on Agent-Based Computational Economics," Staff General Research Papers Archive 1915, Iowa State University, Department of Economics.
    58. Min Zheng & Duo Wang & Xue-Zhong He, 2009. "Asymmetry of technical analysis and market price volatility," Published Paper Series 2009-6, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    59. Alexandru Mandes, 2014. "Order Placement in a Continuous Double Auction Agent Based Model," MAGKS Papers on Economics 201443, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    60. Blake LeBaron & Ryuichi Yamamoto, 2008. "The Impact of Imitation on Long Memory in an Order-Driven Market," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 34(4), pages 504-517.
    61. Chung-Yuan Huang & Chun-Liang Lee, 2014. "Influences of Agents with a Self-Reputation Awareness Component in an Evolutionary Spatial IPD Game," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-12, June.
    62. Zhu, Jiahua & Bao, Te & Chia, Wai Mun, 2021. "Evolutionary selection of forecasting and quantity decision rules in experimental asset markets," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 363-404.
    63. 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.
    64. Blake LeBaron, 2011. "Active and Passive Learning in Agent-based Financial Markets," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 37(1), pages 35-43.
    65. Zhu, Mei & Chiarella, Carl & He, Xue-Zhong & Wang, Duo, 2009. "Does the market maker stabilize the market?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(15), pages 3164-3180.
    66. 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).
    67. Manahov, Viktor & Urquhart, Andrew, 2021. "The efficiency of Bitcoin: A strongly typed genetic programming approach to smart electronic Bitcoin markets," International Review of Financial Analysis, Elsevier, vol. 73(C).
    68. Kopp, T. & Salecker, J., 2018. "Identifying Influential Traders by Agent Based Modelling," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277130, International Association of Agricultural Economists.
    69. Boer-Sorban, K. & de Bruin, A. & Kaymak, U., 2005. "On the Design of Artificial Stock Markets," ERIM Report Series Research in Management ERS-2005-001-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

  35. Chen, Shu-Heng & Lux, Thomas & Marchesi, Michele, 2001. "Testing for non-linear structure in an artificial financial market," Journal of Economic Behavior & Organization, Elsevier, vol. 46(3), pages 327-342, November.

    Cited by:

    1. García Ruiz Reyna Susana & Cruz Aké Salvador & Venegas Martínez Francisco, 2014. "Una medida de eficiencia de mercado: Un enfoque de teoría de la información," Contaduría y Administración, Accounting and Management, vol. 59(4), pages 137-166, octubre-d.
    2. Hayashi, Katsuhiko & Kaizoji, Taisei & Pichl, Lukáš, 2007. "Correlation patterns of NIKKEI index constituents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(1), pages 16-21.
    3. Troy Tassier, 2013. "Handbook of Research on Complexity, by J. Barkley Rosser, Jr. and Edward Elgar," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 39(1), pages 132-133.
    4. Thomas Lux, 2009. "Applications of Statistical Physics in Finance and Economics," Chapters, in: J. Barkley Rosser Jr. (ed.), Handbook of Research on Complexity, chapter 9, Edward Elgar Publishing.
    5. Thomas Theobald, 2012. "Agent-based risk management - A regulatory approach to financial markets," IMK Working Paper 95-2012, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    6. Xue-Zhong He & Youwei Li, 2005. "Long Memory, Heterogeneity and Trend Chasing," Research Paper Series 148, Quantitative Finance Research Centre, University of Technology, Sydney.
    7. Chen, Shu-Heng & Yeh, Chia-Hsuan, 2002. "On the emergent properties of artificial stock markets: the efficient market hypothesis and the rational expectations hypothesis," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 217-239, October.
    8. Li, Y. & Donkers, A.C.D. & Melenberg, B., 2006. "The Econometric Analysis of Microscopic Simulation Models," Discussion Paper 2006-99, Tilburg University, Center for Economic Research.
    9. 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.
    10. Sylvain Mignot & Gabriele Tedeschi & Annick Vignes, 2012. "An Agent Based Model of Switching: The Case of Boulogne S/mer Fish Market," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(2), pages 1-3.
    11. Frank Westerhoff, 2003. "Multi-Asset Market Dynamics," Computing in Economics and Finance 2003 88, Society for Computational Economics.
    12. Constantinos VORLOW & Antonios ANTONIOU & Catherine KYRTSOU, 2004. "Surrogate Data Analysis and Stochastic Chaotic Modelling: Application to Stock Exchange Returns Series," Computing in Economics and Finance 2004 27, Society for Computational Economics.
    13. He, Xue-Zhong & Li, Youwei, 2015. "Testing of a market fraction model and power-law behaviour in the DAX 30," Journal of Empirical Finance, Elsevier, vol. 31(C), pages 1-17.
    14. Pichl, Lukáš & Kaizoji, Taisei & Yamano, Takuya, 2007. "Stylized facts in internal rates of return on stock index and its derivative transactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 219-227.
    15. Georges, Christophre, 2006. "Learning with misspecification in an artificial currency market," Journal of Economic Behavior & Organization, Elsevier, vol. 60(1), pages 70-84, May.
    16. Yeh, Chia-Hsuan, 2008. "The effects of intelligence on price discovery and market efficiency," Journal of Economic Behavior & Organization, Elsevier, vol. 68(3-4), pages 613-625, December.
    17. Catherine Kyrtsou & Michel Terraza, 2003. "Is it Possible to Study Chaotic and ARCH Behaviour Jointly? Application of a Noisy Mackey–Glass Equation with Heteroskedastic Errors to the Paris Stock Exchange Returns Series," Computational Economics, Springer;Society for Computational Economics, vol. 21(3), pages 257-276, June.
    18. Mariano Matilla-García & Manuel Ruiz Marín & Mohammed Dore & Rina Ojeda, 2014. "Nonparametric correlation integral–based tests for linear and nonlinear stochastic processes," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 37(1), pages 181-193, April.
    19. He, Xue-Zhong & Li, Youwei, 2007. "Power-law behaviour, heterogeneity, and trend chasing," Journal of Economic Dynamics and Control, Elsevier, vol. 31(10), pages 3396-3426, October.
    20. Vivien Lespagnol & Juliette Rouchier, 2018. "Trading Volume and Price Distortion: An Agent-Based Model with Heterogenous Knowledge of Fundamentals," Computational Economics, Springer;Society for Computational Economics, vol. 51(4), pages 991-1020, April.
    21. Andrea Morone, 2002. "Financial Market in the Laboratory," Computing in Economics and Finance 2002 151, Society for Computational Economics.
    22. Lux, Thomas & Schornstein, Sascha, 2005. "Genetic learning as an explanation of stylized facts of foreign exchange markets," Journal of Mathematical Economics, Elsevier, vol. 41(1-2), pages 169-196, February.
    23. Hwang, Keunho & Kang, Jangkoo & Ryu, Doojin, 2010. "Phase-transition behavior in the emerging market: Evidence from the KOSPI200 futures market," International Review of Financial Analysis, Elsevier, vol. 19(1), pages 35-46, January.
    24. Kyrtsou, Catherine & Terraza, Michel, 2002. "Stochastic chaos or ARCH effects in stock series?: A comparative study," International Review of Financial Analysis, Elsevier, vol. 11(4), pages 407-431.
    25. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Kiel Working Papers 1426, Kiel Institute for the World Economy (IfW Kiel).
    26. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Economics Working Papers 2008-08, Christian-Albrechts-University of Kiel, Department of Economics.
    27. Catherine Kyrtsou & Michel Terraza, 2008. "Seasonal Mackey-Glass-GARCH process and short-term dynamics," Discussion Paper Series 2008_09, Department of Economics, University of Macedonia, revised Sep 2008.
    28. Luis Goncalves de Faria, 2022. "An Agent-Based Model With Realistic Financial Time Series: A Method for Agent-Based Models Validation," Papers 2206.09772, arXiv.org.
    29. Alfarano, Simone & Lux, Thomas, 2006. "A minimal noise trader model with realistic time series properties," Economics Working Papers 2006-11, Christian-Albrechts-University of Kiel, Department of Economics.
    30. Menkhoff, Lukas & Rebitzky, Rafael R. & Schröder, Michael, 2009. "Heterogeneity in exchange rate expectations: Evidence on the chartist-fundamentalist approach," Journal of Economic Behavior & Organization, Elsevier, vol. 70(1-2), pages 241-252, May.
    31. Shimokawa, Tetsuya & Suzuki, Kyoko & Misawa, Tadanobu, 2007. "An agent-based approach to financial stylized facts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(1), pages 207-225.
    32. Kyubin Yim & Gabjin Oh & Seunghwan Kim, 2016. "Understanding Financial Market States Using an Artificial Double Auction Market," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-15, March.
    33. Andreas Krause, 2000. "Microstructure Effects on Daily Return Volatility in Financial Markets," Papers cond-mat/0011295, arXiv.org.
    34. Chen, Shu-Heng & Yeh, Chia-Hsuan, 2001. "Evolving traders and the business school with genetic programming: A new architecture of the agent-based artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 363-393, March.
    35. Shu-Heng Chen & Chia-Hsuan Yeh, 1999. "Evolving Traders and the Faculty of the Business School: A New Architecture of the Artificial Stock Market," Computing in Economics and Finance 1999 613, Society for Computational Economics.
    36. Hendrik J. Blok, 2000. "On the nature of the stock market: Simulations and experiments," Papers cond-mat/0010211, arXiv.org.
    37. Bernardo Alves Furtado & Gustavo Onofre Andre~ao, 2022. "Machine Learning Simulates Agent-Based Model Towards Policy," Papers 2203.02576, arXiv.org, revised Nov 2022.
    38. Norman Ehrentreich, 2002. "The Santa Fe Artificial Stock Market Re-Examined - Suggested Corrections," Computational Economics 0209001, University Library of Munich, Germany.
    39. 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.
    40. Jiang, Jiaqi & Gu, Rongbao, 2016. "Using Rényi parameter to improve the predictive power of singular value decomposition entropy on stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 254-264.
    41. Belaire-Franch, Jorge, 2004. "Testing for non-linearity in an artificial financial market: a recurrence quantification approach," Journal of Economic Behavior & Organization, Elsevier, vol. 54(4), pages 483-494, August.
    42. Amilon, Henrik, 2008. "Estimation of an adaptive stock market model with heterogeneous agents," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 342-362, March.
    43. Lux, Thomas & Alfarano, Simone, 2016. "Financial power laws: Empirical evidence, models, and mechanisms," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 3-18.
    44. Silver, Steven D. & Raseta, Marko & Bazarova, Alina, 2023. "Stochastic resonance in the recovery of signal from agent price expectations," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    45. Chen, Yanhua & Pantelous, Athanasios A., 2022. "The U.S.-China trade conflict impacts on the Chinese and U.S. stock markets: A network-based approach," Finance Research Letters, Elsevier, vol. 46(PB).
    46. Alfarano, Simone & Lux, Thomas, 2007. "A Noise Trader Model As A Generator Of Apparent Financial Power Laws And Long Memory," Macroeconomic Dynamics, Cambridge University Press, vol. 11(S1), pages 80-101, November.
    47. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2007. "Agent-based Models of Financial Markets," Papers physics/0701140, arXiv.org.
    48. Sergiy Gerasymchuk, 2008. "Asset return and wealth dynamics with reference dependent preferences and heterogeneous beliefs," Working Papers 160, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    49. Lux, Thomas, 2008. "Applications of statistical physics in finance and economics," Kiel Working Papers 1425, Kiel Institute for the World Economy (IfW Kiel).
    50. Valentyn Panchenko & Sergiy Gerasymchuk & Oleg V. Pavlov, 2007. "Asset price dynamics with small world interactions under hetereogeneous beliefs," Working Papers 149, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    51. Feldman, Todd, 2010. "Portfolio manager behavior and global financial crises," Journal of Economic Behavior & Organization, Elsevier, vol. 75(2), pages 192-202, August.
    52. Boer-Sorban, K. & Kaymak, U. & de Bruin, A., 2005. "A Modular Agent-Based Environment for Studying Stock Markets," ERIM Report Series Research in Management ERS-2005-017-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    53. BRATIAN Vasile & BUCUR Amelia, 2017. "The Development And The Current Status Of The Capital Market Hypotheses: A Few Benchmarks," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 69(1), pages 22-28, April.
    54. Ali Moeini & Mehdi Ahrari & Saeed Sadat Madarshahi3, 2007. "Investigating Chaos in Tehran Stock Exchange Index," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 12(1), pages 103-120, winter.
    55. Arvid Oskar Ivar Hoffmann & Wander Jager & J. H. Von Eije, 2007. "Social Simulation of Stock Markets: Taking It to the Next Level," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(2), pages 1-7.
    56. Philip Z. Maymin, 2010. "Schizophrenic Representative Investors," Papers 1004.4592, arXiv.org.
    57. Lux, Thomas, 2006. "Financial power laws: Empirical evidence, models, and mechanism," Economics Working Papers 2006-12, Christian-Albrechts-University of Kiel, Department of Economics.
    58. Antonio Doria, Francisco, 2011. "J.B. Rosser Jr. , Handbook of Research on Complexity, Edward Elgar, Cheltenham, UK--Northampton, MA, USA (2009) 436 + viii pp., index, ISBN 978 1 84542 089 5 (cased)," Journal of Economic Behavior & Organization, Elsevier, vol. 78(1-2), pages 196-204, April.
    59. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.
    60. Catherine Kyrtsou & Michel Terraza, 2000. "Is It Possible To Study Jointly Chaotic And Arch Behaviour? Application Of A Noisy Mackey-Glass Equation With Heteroskedastic Errors To The Paris Stock Exchange," Computing in Economics and Finance 2000 Z226, Society for Computational Economics.
    61. Vivien Lespagnol & Juliette Rouchier, 2018. "Trading Volume and Price Distortion: An Agent-Based Model with Heterogenous Knowledge of Fundamentals," Post-Print hal-02084910, HAL.
    62. Boer-Sorban, K. & de Bruin, A. & Kaymak, U., 2005. "On the Design of Artificial Stock Markets," ERIM Report Series Research in Management ERS-2005-001-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

  36. Shu-Heng Chen & Chia-Hsuan Yeh, 2000. "Simulating economic transition processes by genetic programming," Annals of Operations Research, Springer, vol. 97(1), pages 265-286, December.

    Cited by:

    1. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
    2. Tongkui Yu & Shu-Heng Chen, 2021. "Realizable Utility Maximization as a Mechanism for the Stability of Competitive General Equilibrium in a Scarf Economy," Computational Economics, Springer;Society for Computational Economics, vol. 58(1), pages 133-167, June.

  37. Chen, Shu-Heng & Yeh, Chia-Hsuan, 1997. "Toward a computable approach to the efficient market hypothesis: An application of genetic programming," Journal of Economic Dynamics and Control, Elsevier, vol. 21(6), pages 1043-1063, June.
    See citations under working paper version above.

Chapters

  1. Shu-Heng Chen & Kuo-Chuan Shih & Chung-Ching Tai, 2012. "Can Artificial Traders Learn and Err Like Human Traders? A New Direction for Computational Intelligence in Behavioral Finance," Springer Optimization and Its Applications, in: Michael Doumpos & Constantin Zopounidis & Panos M. Pardalos (ed.), Financial Decision Making Using Computational Intelligence, edition 127, chapter 0, pages 35-69, Springer.

    Cited by:

    1. Tai, Chung-Ching & Chen, Shu-Heng & Yang, Lee-Xieng, 2018. "Cognitive ability and earnings performance: Evidence from double auction market experiments," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 409-440.

  2. Bin-Tzong Chie & Shu-Heng Chen, 2010. "Social Interactions and Innovation: Simulation Based on an Agent-Based Modular Economy," Lecture Notes in Economics and Mathematical Systems, in: Marco Li Calzi & Lucia Milone & Paolo Pellizzari (ed.), Progress in Artificial Economics, pages 127-138, Springer.

    Cited by:

    1. Bin-Tzong Chie & Shu-Heng Chen, 2014. "Non-Price Competition in a Modular Economy," ASSRU Discussion Papers 1401, ASSRU - Algorithmic Social Science Research Unit.

  3. Shu-Heng Chen & Tzu-Wen Kuo & Kong-Mui Hoi, 2008. "Genetic Programming and Financial Trading: How Much About "What We Know"," Springer Optimization and Its Applications, in: Constantin Zopounidis & Michael Doumpos & Panos M. Pardalos (ed.), Handbook of Financial Engineering, pages 99-154, Springer.

    Cited by:

    1. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Empirical modelling of survey-based expectations for the design of economic indicators in five European regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 205-227, May.
    2. Sorić, Petar & Lolić, Ivana & Claveria, Oscar & Monte, Enric & Torra, Salvador, 2019. "Unemployment expectations: A socio-demographic analysis of the effect of news," Labour Economics, Elsevier, vol. 60(C), pages 64-74.
    3. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "A new approach for the quantification of qualitative measures of economic expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2685-2706, November.

  4. Shu-Heng Chen & Bin-Tzong Chie, 2006. "A Functional Modularity Approach to Agent-based Modeling of the Evolution of Technology," Lecture Notes in Economics and Mathematical Systems, in: Akira Namatame & Taisei Kaizouji & Yuuji Aruka (ed.), The Complex Networks of Economic Interactions, pages 165-178, Springer.

    Cited by:

    1. Bin-Tzong Chie & Shu-Heng Chen, 2014. "Non-Price Competition in a Modular Economy," ASSRU Discussion Papers 1401, ASSRU - Algorithmic Social Science Research Unit.
    2. Bin-Tzong Chie & Shu-Heng Chen, 2014. "Competition in a New Industrial Economy: Toward an Agent-Based Economic Model of Modularity," Administrative Sciences, MDPI, vol. 4(3), pages 1-27, July.
    3. Ben Vermeulen & Andreas Pyka, 2018. "The Role of Network Topology and the Spatial Distribution and Structure of Knowledge in Regional Innovation Policy: A Calibrated Agent-Based Model Study," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 773-808, October.

  5. Shu-Heng Chen & Jenn-Shyong Kuo & Chu-Chia Lin, 1996. "From the Hayek Hypothesis to Animal Spirits: The Phase Transition Based on Competitive Experimental Market," Palgrave Macmillan Books, in: Daniel Vaz & Kumaraswamy Velupillai (ed.), Inflation, Institutions and Information, chapter 12, pages 290-318, Palgrave Macmillan.

    Cited by:

    1. Shu-Heng Chen & Chung-Ching Tai, 2003. "Trading Restrictions, Price Dynamics And Allocative Efficiency In Double Auction Markets: Analysis Based On Agent-Based Modeling And Simulations," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 6(03), pages 283-302.

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