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Estimation of agent-based models using sequential Monte Carlo methods

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Cited by:

  1. Lux, Thomas, 2022. "Inference for Nonlinear State Space Models: A Comparison of Different Methods applied to Markov-Switching Multifractal Models," Econometrics and Statistics, Elsevier, vol. 21(C), pages 69-95.
  2. Priscilla Avegliano & Jaime Simão Sichman, 2023. "Equation-Based Versus Agent-Based Models: Why Not Embrace Both for an Efficient Parameter Calibration?," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 26(4), pages 1-3.
  3. Mario Martinoli & Alessio Moneta & Gianluca Pallante, 2022. "Calibration and Validation of Macroeconomic Simulation Models by Statistical Causal Search," LEM Papers Series 2022/33, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  4. Kukacka, Jiri & Jang, Tae-Seok & Sacht, Stephen, 2018. "On the estimation of behavioral macroeconomic models via simulated maximum likelihood," Economics Working Papers 2018-11, Christian-Albrechts-University of Kiel, Department of Economics.
  5. Delli Gatti, Domenico & Grazzini, Jakob, 2020. "Rising to the challenge: Bayesian estimation and forecasting techniques for macroeconomic Agent Based Models," Journal of Economic Behavior & Organization, Elsevier, vol. 178(C), pages 875-902.
  6. Kukacka, Jiri & Kristoufek, Ladislav, 2021. "Does parameterization affect the complexity of agent-based models?," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 324-356.
  7. Ramis Khabibullin & Sergei Seleznev, 2022. "Fast Estimation of Bayesian State Space Models Using Amortized Simulation-Based Inference," Bank of Russia Working Paper Series wps104, Bank of Russia.
  8. Zhiming LONG & Rémy HERRERA, 2020. "Spurious OLS Estimators of Detrending Method by Adding a Linear Trend in Difference-Stationary Processes—A Mathematical Proof and Its Verification by Simulation," Mathematics, MDPI, vol. 8(11), pages 1-19, November.
  9. Filippo Gusella & Engelbert Stockhammer, 2021. "Testing fundamentalist–momentum trader financial cycles: An empirical analysis via the Kalman filter," Metroeconomica, Wiley Blackwell, vol. 72(4), pages 758-797, November.
  10. Filippo Gusella, 2022. "Detecting And Measuring Financial Cycles In Heterogeneous Agents Models: An Empirical Analysis," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 25(02n03), pages 1-22, March.
  11. Platt, Donovan, 2020. "A comparison of economic agent-based model calibration methods," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
  12. Barde, Sylvain, 2020. "Macroeconomic simulation comparison with a multivariate extension of the Markov information criterion," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
  13. Lux, Thomas, 2020. "Bayesian estimation of agent-based models via adaptive particle Markov chain Monte Carlo," Economics Working Papers 2020-01, Christian-Albrechts-University of Kiel, Department of Economics.
  14. Farmer, J. Doyne & Dyer, Joel & Cannon, Patrick & Schmon, Sebastian, 2022. "Black-box Bayesian inference for economic agent-based models," INET Oxford Working Papers 2022-05, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
  15. Corrado Monti & Marco Pangallo & Gianmarco De Francisci Morales & Francesco Bonchi, 2022. "On learning agent-based models from data," Papers 2205.05052, arXiv.org, revised Nov 2022.
  16. Nicolas, Maxime L.D., 2022. "Estimating a model of herding behavior on social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
  17. Domenico Delli Gatti & Filippo Gusella & Giorgio Ricchiuti, 2024. "Endogenous vs Exogenous Instability: An Out-of-Sample Comparison," Working Papers - Economics wp2024_05.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
  18. David Alaminos & M. Belén Salas & Manuel Á. Fernández-Gámez, 2023. "Quantum Monte Carlo simulations for estimating FOREX markets: a speculative attacks experience," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-21, December.
  19. Dyer, Joel & Cannon, Patrick & Farmer, J. Doyne & Schmon, Sebastian M., 2024. "Black-box Bayesian inference for agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 161(C).
  20. Denis Koshelev & Alexey Ponomarenko & Sergei Seleznev, 2023. "Amortized neural networks for agent-based model forecasting," Papers 2308.05753, arXiv.org.
  21. Majewski, Adam A. & Ciliberti, Stefano & Bouchaud, Jean-Philippe, 2020. "Co-existence of trend and value in financial markets: Estimating an extended Chiarella model," Journal of Economic Dynamics and Control, Elsevier, vol. 112(C).
  22. Zila, Eric & Kukacka, Jiri, 2023. "Moment set selection for the SMM using simple machine learning," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 366-391.
  23. Donovan Platt, 2022. "Bayesian Estimation of Economic Simulation Models Using Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 599-650, February.
  24. Ramis Khabibullin & Alexey Ponomarenko, 2022. "An empirical behavioral model of household’s deposit dollarization," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(3), pages 827-847, July.
  25. Nils Bertschinger & Oliver Pfante, 2020. "Early Warning Signs of Financial Market Turmoils," JRFM, MDPI, vol. 13(12), pages 1-24, November.
  26. Zhang, Jinyu & Zhang, Qiaosen & Li, Yong & Wang, Qianchao, 2023. "Sequential Bayesian inference for agent-based models with application to the Chinese business cycle," Economic Modelling, Elsevier, vol. 126(C).
  27. Kononovicius, Aleksejus & Ruseckas, Julius, 2019. "Order book model with herd behavior exhibiting long-range memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 171-191.
  28. Shiono, Takashi, 2021. "Estimation of agent-based models using Bayesian deep learning approach of BayesFlow," Journal of Economic Dynamics and Control, Elsevier, vol. 125(C).
  29. Mitja Steinbacher & Matthias Raddant & Fariba Karimi & Eva Camacho Cuena & Simone Alfarano & Giulia Iori & Thomas Lux, 2021. "Advances in the agent-based modeling of economic and social behavior," SN Business & Economics, Springer, vol. 1(7), pages 1-24, July.
  30. Kukacka, Jiri & Sacht, Stephen, 2023. "Estimation of heuristic switching in behavioral macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
  31. Filippo Gusella & Giorgio Ricchiuti, 2021. "State Space Model to Detect Cycles in Heterogeneous Agents Models," Working Papers - Economics wp2021_10.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
  32. Emna Mnif & Anis Jarboui & M. Kabir Hassan & Khaireddine Mouakhar, 2020. "Big data tools for Islamic financial analysis," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(1), pages 10-21, January.
  33. Filippo Gusella & Giorgio Ricchiuti, 2022. "A State-Space Approach for Time-Series Prediction of an Heterogeneous Agent Model," Working Papers - Economics wp2022_20.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
  34. Du, Kai, 2019. "Investor expectations, earnings management, and asset prices," Journal of Economic Dynamics and Control, Elsevier, vol. 105(C), pages 134-157.
  35. Nils Bertschinger & Iurii Mozzhorin, 2021. "Bayesian estimation and likelihood-based comparison of agent-based volatility models," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(1), pages 173-210, January.
  36. Kononovicius, Aleksejus, 2021. "Supportive interactions in the noisy voter model," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
  37. Tubbenhauer, Tobias & Fieberg, Christian & Poddig, Thorsten, 2021. "Multi-agent-based VaR forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
  38. Aleksejus Kononovicius & Julius Ruseckas, 2018. "Order book model with herd behavior exhibiting long-range memory," Papers 1809.02772, arXiv.org, revised Apr 2019.
  39. Thomas Lux, 2022. "Bayesian Estimation of Agent-Based Models via Adaptive Particle Markov Chain Monte Carlo," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 451-477, August.
  40. Farmer, J. Doyne & Dyer, Joel & Cannon, Patrick & Schmon, Sebastian, 2022. "Calibrating Agent-based Models to Microdata with Graph Neural Networks," INET Oxford Working Papers 2022-30, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
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