Heterogeneous speculators and stock market dynamics: a simple agent-based computational model

References

• Alfi, V., M. Cristelli, L. Pietronero, and A. Zaccaria. 2009. “Minimal Agent Based Model for Financial Markets I.” The European Physical Journal B 67: 385–397. doi: 10.1140/epjb/e2009-00028-4
   Web of Science ®Google Scholar
• Anufriev, M., T. Bao, and J. Tuinstra. 2016. “Microfoundations for Switching Behavior in Heterogeneous Agent Models: an Experiment.” Journal of Economic Behavior and Organization 129: 74–99. doi: 10.1016/j.jebo.2016.06.002
   Web of Science ®Google Scholar
• Arthur, B., J. Holland, B. LeBaron, R. Palmer, and P. Tayler. 1997. “Asset Pricing Under Endogenous Expectations in an Artificial Stock Market.” In The Economy as an Evolving Complex System II, edited by B. Arthur, S. Durlauf, and D. Lane, 15–44. Addison-Wesley: Addison-Wesley, Reading.
   Google Scholar
• Aymanns, C., F. Caccioli, D. Farmer, and V. Tan. 2016. “Taming the Basel Leverage Cycle.” Journal of Financial Stability 27: 263–277. doi: 10.1016/j.jfs.2016.02.004
   Web of Science ®Google Scholar
• Aymanns, C., D. Farmer, A. Kleinnijenhuis, and T. Wetzer. 2018. “Models of Financial Stability and Their Application in Stress Tests.” In Handbook of Computational Economics: Heterogeneous Agent Modeling, edited by C. Hommes, and B. LeBaron, 329–391. Amsterdam: North-Holland.
   Google Scholar
• Beja, A., and M. Goldman. 1980. “On the Dynamic Behaviour of Prices in Disequilibrium.” The Journal of Finance 35: 235–248. doi: 10.1111/j.1540-6261.1980.tb02151.x
   Web of Science ®Google Scholar
• Bertschinger, N., and I. Mozzhorin. 2020. “Bayesian Estimation and Likelihood-Based Comparison of Agent-Based Volatility Models.” Journal of Economic Interaction and Coordination. doi:10.1007/s11403-020-00289-z.
   Web of Science ®Google Scholar
• Black, F. 1986. “Noise.” The Journal of Finance 41: 528–543. doi: 10.1111/j.1540-6261.1986.tb04513.x
   Web of Science ®Google Scholar
• Blaurock, I., N. Schmitt, and F. Westerhoff. 2018. “Market Entry Waves and Volatility Out-Bursts in Stock Markets.” Journal of Economic Behavior and Organization 153: 19–37. doi: 10.1016/j.jebo.2018.03.022
   Web of Science ®Google Scholar
• Bouchaud, J.-P., S. Ciliberti, Y. Lemperiere, A. Majewski, P. Seager, and K. Sin Ronia. 2017. Black was Right: Price is Within a Factor 2 of Value. SSRN https://ssrn.com/abstract=3070850.
   Google Scholar
• Brock, W., and C. Hommes. 1998. “Heterogeneous Beliefs and Routes to Chaos in a Simple Asset Pricing Model.” Journal of Economic Dynamics and Control 22: 1235–1274. doi: 10.1016/S0165-1889(98)00011-6
   Web of Science ®Google Scholar
• Chang, I., and D. Stauffer. 1999. “Fundamental Judgement in Cont-Bouchaud Herding Model of Financial Fluctuations.” Physica A: Statistical Mechanics and its Applications 264: 294–298. doi: 10.1016/S0378-4371(98)00441-5
   Google Scholar
• Chen, S.-H., and C.-H. Yeh. 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 25: 363–393. doi: 10.1016/S0165-1889(00)00030-0
   Web of Science ®Google Scholar
• Chiarella, C. 1992. “The Dynamics of Speculative Behavior.” Annals of Operations Research 37: 101–123. doi: 10.1007/BF02071051
   Google Scholar
• Chiarella, C., and G. Iori. 2002. “A Simulation Analysis of the Microstructure of Double Auction Markets.” Quantitative Finance 2: 346–353. doi: 10.1088/1469-7688/2/5/303
   Google Scholar
• Cont, R. 2001. “Empirical Properties of Asset Returns: Stylized Facts and Statistical Issues.” Quantitative Finance 1: 223–236. doi: 10.1080/713665670
   Web of Science ®Google Scholar
• Cont, R., and J.-P. Bouchaud. 2000. “Herd Behavior and Aggregate Fluctuations in Financial Markets.” Macroeconomic Dynamics 4: 170–196. doi: 10.1017/S1365100500015029
   Web of Science ®Google Scholar
• Daniels, M., D. Farmer, L. Gillemot, G. Iori, and E. Smith. 2003. “Quantitative Model of Price Diffusion and Market Friction Based on Trading as a Mechanistic Random Process.” Physical Review Letters 90: 108102. doi: 10.1103/PhysRevLett.90.108102
   PubMed Web of Science ®Google Scholar
• Day, R., and W. Huang. 1990. “Bulls, Bears and Market Sheep.” Journal of Economic Behavior and Organization 14: 299–329. doi: 10.1016/0167-2681(90)90061-H
   Web of Science ®Google Scholar
• De Grauwe, P., H. Dewachter, and M. Embrechts. 1993. Exchange Rate Theory: Chaotic Models of Foreign Exchange Markets. Oxford: Blackwell.
   Google Scholar
• Delli Gatti, D., G. Fagiolo, M. Gallegati, M. Richiardi, and A. Russo. 2018. Agent-Based Models in Economics: A Toolkit. Cambridge: Cambridge University Press.
   Google Scholar
• Demirer, R., G. Demos, R. Gupta, and D. Sornette. 2019. “On the Predictability of Stock Market Bubbles: Evidence from LPPLS Confidence Multi-Scale Indicators.” Quantitative Finance 19: 843–858. doi: 10.1080/14697688.2018.1524154
   Web of Science ®Google Scholar
• Dieci, R., and X.-Z. He. 2018. “Heterogeneous Agent Models in Finance.” In Handbook of Computational Economics: Heterogeneous Agent Modeling, edited by C. Hommes, and B. LeBaron, 257–328. Amsterdam: North-Holland.
   Google Scholar
• Dieci, R., N. Schmitt, and F. Westerhoff. 2018. “Interactions between Stock, Bond and Housing Markets.” Journal of Economic Dynamics and Control 91: 43–70. doi: 10.1016/j.jedc.2018.05.001
   Web of Science ®Google Scholar
• Diem, C., A. Pichler, and S. Thurner. 2020. “What is the Minimal Systemic Risk in Financial Exposure Networks?” Journal of Economic Dynamics and Control 116: 103900. doi: 10.1016/j.jedc.2020.103900
   Web of Science ®Google Scholar
• Fagiolo, G., M. Guerini, F. Lamperti, A. Moneta, and A. Roventini. 2017. “Validation of Agent-Based Models in Economics and Finance.” In Computer Simulation Validation, edited by C. Beisbart, and N. Saam, 763–787. Berlin: Springer.
   Google Scholar
• Fama, E. 1989. “Perspectives on October 1987, or, What Did we Learn from the Crash?” In Black Monday and the Future of Financial Markets, edited by R. Kampuis, R. Kormendi, and J. Watson, 71–82. Homewood: Irwin.
   Google Scholar
• Farmer, D., L. Gillemot, G. Iori, S. Krishnamurthy, E. Smith, and M. Daniels. 2005b. “A Random Order Placement Model of Price Formation in the Continuous Double Auction.” In The Economy as an Evolving Complex System, III: Current Perspectives and Future Directions, edited by L. Blume, and S. Durlauf, 133–173. Oxford: Oxford University Press.
   Google Scholar
• Farmer, D., and S. Joshi. 2002. “The Price Dynamics of Common Trading Strategies.” Journal of Economic Behavior and Organization 49: 149–171. doi: 10.1016/S0167-2681(02)00065-3
   Web of Science ®Google Scholar
• Farmer, D., P. Patelli, and I. Zovko. 2005a. “The Predictive Power of Zero Intelligence in Financial Markets.” Proceedings of the National Academy of Sciences 102: 2254–2259. doi: 10.1073/pnas.0409157102
   PubMed Web of Science ®Google Scholar
• Franke, R., and F. Westerhoff. 2012. “Structural Stochastic Volatility in Asset Pricing Dynamics: Estimation and Model Contest.” Journal of Economic Dynamics and Control 36: 1193–1211. doi: 10.1016/j.jedc.2011.10.004
   Web of Science ®Google Scholar
• Franke, R., and F. Westerhoff. 2016. “Why a Simple Herding Model May Generate the Stylized Facts of Daily Returns: Explanation and Estimation.” Journal of Economic Interaction and Coordination 11: 1–34. doi: 10.1007/s11403-014-0140-6
   Web of Science ®Google Scholar
• Galbraith, J. K. 1994. A Short History of Financial Suphoria. London: Penguin Books.
   Google Scholar
• Gode, D., and S. Sunder. 1993. “Allocative Efficiency of Markets with Zero-Intelligence Traders: Market as a Partial Substitute for Individual Rationality.” Journal of Political Economy 101: 119–137. doi: 10.1086/261868
   Web of Science ®Google Scholar
• Gode, D., and S. Sunder. 1997. “What Makes Markets Allocationally Efficient?” The Quarterly Journal of Economics 112: 603–630. doi: 10.1162/003355397555307
   Web of Science ®Google Scholar
• Gomber, P., and K. Zimmermann. 2018. “Algorithmic Trading in Practice.” In The Oxford Handbook on Computational Economics and Finance, edited by S.-H. Chen, M. Kaboudan, and Y.-R. Du, 311–332. Oxford: Oxford University Press.
   Google Scholar
• Gopikrishnan, P., V. Plerou, L. Amaral, M. Meyer, and E. Stanley. 1999. “Scaling of the Distributions of Fluctuations of Financial Market Indices.” Physical Review E 60: 5305–5316. doi: 10.1103/PhysRevE.60.5305
   PubMed Web of Science ®Google Scholar
• Graham, B., and D. Dodd. 1951. Security Analysis. New York: McGraw-Hill.
   Google Scholar
• Greenwald, B., and J. Stein. 1991. “Transactional Risk, Market Crashes, and the Role of Circuit Breakers.” The Journal of Business 64: 443–462. doi: 10.1086/296547
   Web of Science ®Google Scholar
• Guerini, M., and A. Moneta. 2017. “A Method for Agent-Based Models Validation.” Journal of Economic Dynamics and Control 82: 125–141. doi: 10.1016/j.jedc.2017.06.001
   Web of Science ®Google Scholar
• Harris, L. 1998. “Circuit Breakers and Program Trading Limits: What Have we Learned?” In Brookings-Wharton Papers on Financial Services, edited by R. Litan, and A. Santomero, 17–64. Washington: Brookings Institution Press.
   Google Scholar
• Hill, B. 1975. “A Simple General Approach to Inference About the Tail of a Distribution.” The Annals of Statistics 3: 1163–1174. doi: 10.1214/aos/1176343247
   Web of Science ®Google Scholar
• Hommes, C. 2011. “The Heterogeneous Expectations Hypothesis: Some Evidence from the Lab.” Journal of Economic Dynamics and Control 35: 1–24. doi: 10.1016/j.jedc.2010.10.003
   Web of Science ®Google Scholar
• Iori, G. 2002. “A Microsimulation of Traders Activity in the Stock Market: The Role of Heterogeneity, Agents’ Interactions and Trade Frictions.” Journal of Economic Behavior and Organization 49: 269–285. doi: 10.1016/S0167-2681(01)00164-0
   Web of Science ®Google Scholar
• Iori, G., and J. Porter. 2018. “Agent-based Modeling for Financial Markets.” In The Oxford Handbook of Computational Economics and Finance, edited by S.-H. Chen, M. Kaboudan, and Y.-R. Du, 635–666. Oxford: Oxford University Press.
   Google Scholar
• Jacob Leal, S., and M. Napoletano. 2019. “Market Stability vs. Market Resilience: Regulatory Policies Experiments in an Agent-Based Model with Low- and High-Frequency Trading.” Journal of Economic Behavior and Organization 157: 15–41. doi: 10.1016/j.jebo.2017.04.013
   Web of Science ®Google Scholar
• Jacob Leal, S., M. Napoletano, A. Roventini, and G. Fagiolo. 2016. “Rock Around the Clock: An Agent-Based Model of Low- and High-Frequency Trading.” Journal of Evolutionary Economics 26: 49–76. doi: 10.1007/s00191-015-0418-4
   Web of Science ®Google Scholar
• Keynes, J. M. 1936. The General Theory of Employment, Interest, and Money. New York: Harcourt, Brace and Company.
   Google Scholar
• Kim, Y., and J. Yang. 2004. “What Makes Circuit Breakers Attractive to Financial Markets? A Survey.” Financial Markets, Institutions and Instruments 13: 109–146. doi: 10.1111/j.0963-8008.2004.00074.x
   Google Scholar
• Kindleberger, C., and R. Aliber. 2011. Manias, Panics, and Crashes: A History of Financial Crises. New Jersey: Wiley.
   Google Scholar
• Kukacka, J., and L. Kristoufek. 2020. “Do ‘Complex’ Financial Models Really Lead to Complex Dynamics? Agent-Based Models and Multifractality.” Journal of Economic Dynamics and Control 113: 103855. doi: 10.1016/j.jedc.2020.103855
   Web of Science ®Google Scholar
• Ladley, D. 2012. “Zero Intelligence in Economics and Finance.” The Knowledge Engineering Review 27: 273–286. doi: 10.1017/S0269888912000173
   Web of Science ®Google Scholar
• Ladley, D. 2020. “The High Frequency Trade Off between Speed and Sophistication.” Journal of Economic Dynamics and Control 116: 103912. doi: 10.1016/j.jedc.2020.103912
   Web of Science ®Google Scholar
• Ladley, D., T. Lensberg, J. Palczewski, and K. R. Schenk-Hoppe. 2015. “Fragmentation and Stability of Markets.” Journal of Economic Behavior and Organization 119: 466–481. doi: 10.1016/j.jebo.2015.09.013
   Web of Science ®Google Scholar
• Lamperti, F., A. Roventini, and A. Sani. 2018. “Agent-Based Model Calibration Using Machine Learning Surrogates.” Journal of Economic Dynamics and Control 90: 366–389. doi: 10.1016/j.jedc.2018.03.011
   Web of Science ®Google Scholar
• LeBaron, B., B. Arthur, and R. Palmer. 1999. “Time Series Properties of an Artificial Stock Market.” Journal of Economic Dynamics and Control 23: 1487–1516. doi: 10.1016/S0165-1889(98)00081-5
   Web of Science ®Google Scholar
• Lo, A., H. Mamaysky, and J. Wang. 2000. “Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation.” The Journal of Finance 55: 1705–1765. doi: 10.1111/0022-1082.00265
   Web of Science ®Google Scholar
• Lux, T. 1995. “Herd Behaviour, Bubbles and Crashes.” The Economic Journal 105: 881–896. doi: 10.2307/2235156
   Web of Science ®Google Scholar
• Lux, T., and M. Ausloos. 2002. “Market Fluctuations I: Scaling, Multiscaling, and Their Possible Origins.” In Science of Disaster: Climate Disruptions, Heart Attacks, and Market Crashes, edited by A. Bunde, J. Kropp, and H. Schellnhuber, 373–410. Berlin: Springer.
   Google Scholar
• Lux, T., and R. Zwinkels. 2018. “Empirical Validation of Agent-Based Models.” In Handbook of Computational Economics: Heterogeneous Agent Modeling, edited by C. Hommes, and B. LeBaron, 437–482. Amsterdam: North-Holland.
   Google Scholar
• Majewski, A., S. Ciliberti, and J.-P. Bouchaud. 2020. “Co-Existence of Trend and Value in Financial Markets: Estimating an Extended Chiarella Model.” Journal of Economic Dynamics and Control 112: 103791. doi: 10.1016/j.jedc.2019.103791
   Web of Science ®Google Scholar
• Mantegna, R., and E. Stanley. 2000. An Introduction to Econophysics. Cambridge: Cambridge University Press.
   Google Scholar
• Manzan, S., and F. Westerhoff. 2005. “Representativeness of News and Exchange Rate Dynamics.” Journal of Economic Dynamics and Control 29: 677–689. doi: 10.1016/j.jedc.2003.08.008
   Web of Science ®Google Scholar
• Menkhoff, L., and M. Taylor. 2007. “The Obstinate Passion of Foreign Exchange Professionals: Technical Analysis.” Journal of Economic Literature 45: 936–972. doi: 10.1257/jel.45.4.936
   Web of Science ®Google Scholar
• Murphy, J. 1999. Technical Analysis of Financial Markets. New York: New York Institute of Finance.
   Google Scholar
• Palmer, R., B. Arthur, J. Holland, B. LeBaron, and P. Tayler. 1994. “Artificial Economic Life: A Simple Model of a Stock Market.” Physica D: Nonlinear Phenomena 75: 264–274. doi: 10.1016/0167-2789(94)90287-9
   Web of Science ®Google Scholar
• Platt, D. 2020. “A Comparison of Economic Agent-Based Model Calibration Methods.” Journal of Economic Dynamics and Control 113: 103859. doi: 10.1016/j.jedc.2020.103859
   Web of Science ®Google Scholar
• Plerou, V., P. Gopikrishnan, L. Amaral, M. Meyer, and E. Stanley. 1999. “Scaling of the Distribution of Price Fluctuations of Individual Companies.” Physical Review E 60: 6519–6529. doi: 10.1103/PhysRevE.60.6519
   PubMed Web of Science ®Google Scholar
• Poledna, S., S. Thurner, D. Farmer, and J. Geanakoplos. 2014. “Leverage-Induced Systemic Risk Under Basle II and Other Credit Risk Policies.” Journal of Banking and Finance 42: 199–212. doi: 10.1016/j.jbankfin.2014.01.038
   Web of Science ®Google Scholar
• Raberto, M., S. Cincotti, S. Focardi, and M. Marchesi. 2001. “Agent-Based Simulation of a Financial Market.” Physica A: Statistical Mechanics and its Applications 299: 319–327. doi: 10.1016/S0378-4371(01)00312-0
   Web of Science ®Google Scholar
• Schmitt, N. 2020. “Heterogeneous Expectations and Asset Price Dynamics.” Macroeconomic Dynamics. doi:10.1017/S1365100519000774.
   Web of Science ®Google Scholar
• Schmitt, N., F. Tramontana, and F. Westerhoff. 2020. “Nonlinear Asset-Price Dynamics and Stabilization Policies.” Nonlinear Dynamics. doi:10.1007/s11071-020-05828-8.
   Google Scholar
• Schmitt, N., and F. Westerhoff. 2017a. “Heterogeneity, Spontaneous Coordination and Extreme Events Within Large-Scale and Small-Scale Agent-Based Financial Market Models.” Journal of Evolutionary Economics 27: 1041–1070. doi: 10.1007/s00191-017-0504-x
   Web of Science ®Google Scholar
• Schmitt, N., and F. Westerhoff. 2017b. “Herding Behaviour and Volatility Clustering in Financial Markets.” Quantitative Finance 17: 1187–1203. doi: 10.1080/14697688.2016.1267391
   Web of Science ®Google Scholar
• Schmitt, N., and F. Westerhoff. 2017c. “On the Bimodality of the Distribution of the S&P 500’s Distortion: Empirical Evidence and Theoretical Explanations.” Journal of Economic Dynamics and Control 80: 34–53. doi: 10.1016/j.jedc.2017.05.002
   Web of Science ®Google Scholar
• Shiller, R. 2015. Irrational Exuberance. Princeton: Princeton University Press.
   Google Scholar
• Sifat, I., and A. Mohamad. 2019. “Circuit Breakers As Market Stability Levers: A Survey of Research, Praxis, and Challenges.” International Journal of Finance and Economics 24: 1130–1169. doi: 10.1002/ijfe.1709
   Web of Science ®Google Scholar
• Sng, H., Y. Zhang, and H. Zheng. 2020. “Margin Trade, Short Sales and Financial Stability.” Journal of Economic Interaction and Coordination 15: 673–702. doi: 10.1007/s11403-019-00256-3
   Web of Science ®Google Scholar
• Stanek, F., and J. Kukacka. 2018. “The Impact of the Tobin Tax in a Heterogeneous Agent Model of the Foreign Exchange Market.” Computational Economics 51: 865–892. doi: 10.1007/s10614-017-9649-9
   Web of Science ®Google Scholar
• Stauffer, D., and N. Jan. 2000. “Sharp Peaks in the Percolation Model for the Stock Markets.” Physica A: Statistical Mechanics and its Applications 277: 215–219. doi: 10.1016/S0378-4371(99)00587-7
   Google Scholar
• Stauffer, D., and T. Penna. 1998. “Crossover in the Cont-Bouchaud Percolation Model for Market Fluctuations.” Physica A: Statistical Mechanics and its Applications 256: 284–290. doi: 10.1016/S0378-4371(98)00223-4
   Web of Science ®Google Scholar
• Stauffer, D., and D. Sornette. 1999. “Self-Organized Percolation Model for Stock Market Fluctuation.” Physica A: Statistical Mechanics and its Applications 271: 496–506. doi: 10.1016/S0378-4371(99)00290-3
   Google Scholar
• Vassiliadis, V., and G. Dounias. 2018. “Algorithmic Trading Based on Biologically Inspired Algorithms.” In The Oxford Handbook on Computational Economics and Finance, edited by S.-H. Chen, M. Kaboudan, and Y.-R. Du, 295–310. Oxford: Oxford University Press.
   Google Scholar
• Westerhoff, F. 2003. “Speculative Markets and the Effectiveness of Price Limits.” Journal of Economic Dynamics and Control 28: 493–508. doi: 10.1016/S0165-1889(02)00185-9
   Web of Science ®Google Scholar
• Westerhoff, F. 2006. “Technical Analysis Based on Price-Volume Signals and the Power of Trading Breaks.” International Journal of Theoretical and Applied Finance 9: 227–244. doi: 10.1142/S0219024906003512
   Google Scholar
• Westerhoff, F. 2008. “The Use of Agent-Based Financial Market Models to Test the Effectiveness of Regulatory Policies.” Jahrbücher für Nationalökonomie und Statistik (Journal of Economics and Statistics) 228: 195–227.
   Web of Science ®Google Scholar
• Westerhoff, F., and R. Franke. 2018. “Agent-Based Models for Policy Analysis: Two Illustrative Examples.” In The Oxford Handbook of Computational Economics and Finance, edited by S.-H. Chen, M. Kaboudan, and Y.-R. Du, 520–558. Oxford: Oxford University Press.
   Google Scholar
• Westphal, R., and D. Sornette. 2020. “Market Impact and Performance of Arbitrageurs of Financial Bubbles in an Agent-Based Model.” Journal of Economic Behavior and Organization 171: 1–23. doi: 10.1016/j.jebo.2020.01.004
   Web of Science ®Google Scholar
• Xing, G., and D. Ladley. 2019. Noise Trading and Market Stability. SSRN https://ssrn.com/abstract=3415141.
   Google Scholar
• Yeh, C.-H., and C.-Y. Yang. 2010. “Examining the Effectiveness of Price Limits in an Artificial Stock Market.” Journal of Economic Dynamics and Control 34: 2089–2108. doi: 10.1016/j.jedc.2010.05.015
   Web of Science ®Google Scholar
• Yeh, C.-H., and C.-Y. Yang. 2013. “Do Price Limits Hurt the Market?” Journal of Economic Interaction and Coordination 8: 125–153. doi: 10.1007/s11403-012-0107-4
   Web of Science ®Google Scholar
• Zeeman, E. C. 1974. “On the Unstable Behaviour of Stock Exchanges.” Journal of Mathematical Economics 1: 39–49. doi: 10.1016/0304-4068(74)90034-2
   Google Scholar
• Zhang, Q., D. Sornette, and H. Zhang. 2019. “Anticipating Critical Transitions of the Housing Market: New Evidence from China.” The European Journal of Finance 25: 1251–1276. doi: 10.1080/1351847X.2019.1588763
   Web of Science ®Google Scholar