IDEAS home Printed from https://ideas.repec.org/f/c/pal340.html
   My authors  Follow this author

Simone Alfarano

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. Steinbacher, Mitja & Raddant, Matthias & Karimi, Fariba & Camacho-Cuena, Eva & Alfarano, Simone & Iori, Giulia & Lux, Thomas, 2021. "Advances in the Agent-Based Modeling of Economic and Social Behavior," MPRA Paper 107317, University Library of Munich, Germany.

    Cited by:

    1. 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).
    2. M. Raddant & T. Di Matteo, 2023. "A Look at Financial Dependencies by Means of Econophysics and Financial Economics," Papers 2302.08208, arXiv.org.
    3. Mustafa Alassad & Muhammad Nihal Hussain & Nitin Agarwal, 2023. "Developing an agent-based model to minimize spreading of malicious information in dynamic social networks," Computational and Mathematical Organization Theory, Springer, vol. 29(3), pages 487-502, September.
    4. Baxter Williams & Daniel Bishop & Patricio Gallardo & J. Geoffrey Chase, 2023. "Demand Side Management in Industrial, Commercial, and Residential Sectors: A Review of Constraints and Considerations," Energies, MDPI, vol. 16(13), pages 1-28, July.
    5. Paola D'Orazio & Jessica Reale & Anh Duy Pham, 2023. "Climate-induced liquidity crises: interbank exposures and macroprudential implications," Chemnitz Economic Papers 059, Department of Economics, Chemnitz University of Technology.
    6. Midha, Joshua, 2024. "Assessing Emerging Markets through Transactional Dynamics: A New Multi-Dimensional Valuation Framework," SocArXiv d8jkt, Center for Open Science.
    7. Nicolas Cofre & Magdalena Mosionek-Schweda, 2023. "A simulated electronic market with speculative behaviour and bubble formation," Papers 2311.12247, arXiv.org.
    8. Rizzati, Massimiliano & Landoni, Matteo, 2024. "A systematic review of agent-based modelling in the circular economy: Insights towards a general model," Structural Change and Economic Dynamics, Elsevier, vol. 69(C), pages 617-631.
    9. Michele Vodret & Iacopo Mastromatteo & Bence Tóth & Michael Benzaquen, 2023. "Microfounding GARCH models and beyond: a Kyle-inspired model with adaptive agents," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(3), pages 599-625, July.

  2. Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2020. "Survival and the ergodicity of corporate profitability," BERG Working Paper Series 162, Bamberg University, Bamberg Economic Research Group.

    Cited by:

    1. Jan Schulz & Daniel M. Mayerhoffer, 2022. "A Network Approach to Consumption," Papers 2203.14259, arXiv.org, revised Apr 2022.
    2. Mundt, Philipp & Cantner, Uwe & Inoue, Hiroyasu & Savin, Ivan & Vannuccini, Simone, 2021. "Market selection in global value chains," BERG Working Paper Series 170, Bamberg University, Bamberg Economic Research Group.
    3. David Vidal-Tomás & Alba Ruiz-Buforn & Omar Blanco-Arroyo & Simone Alfarano, 2022. "A Cross-Sectional Analysis of Growth and Profit Rate Distribution: The Spanish Case," Mathematics, MDPI, vol. 10(6), pages 1-20, March.
    4. Sahm, Marco, 2022. "Optimal accuracy of unbiased Tullock contests with two heterogeneous players," BERG Working Paper Series 175, Bamberg University, Bamberg Economic Research Group.

  3. Ruiz-Buforn, Alba & Camacho-Cuena, Eva & Morone, Andrea & Alfarano, Simone, 2020. "Overweighting of public information in financial markets: A lesson from the lab," MPRA Paper 98472, University Library of Munich, Germany.

    Cited by:

    1. Rocco Caferra & Gabriele Tedeschi & Andrea Morone, 2023. "Agents interaction and price dynamics: evidence from the laboratory," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(2), pages 251-274, April.
    2. Rocco Caferra & Simone Nuzzo & Andrea Morone, 2023. "“Less is more” or “more is better”? The effect of asymmetric information distribution on market efficiency and wealth inequality," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(2), pages 233-250, April.
    3. Alba Ruiz-Buforn & Simone Alfarano & Eva Camacho-Cuena & Andrea Morone, 2022. "Single vs. multiple disclosures in an experimental asset market with information acquisition," The European Journal of Finance, Taylor & Francis Journals, vol. 28(13-15), pages 1513-1539, October.
    4. Simone Alfarano & Albert Banal-Estañol & Eva Camacho & Giulia Iori & Burcu Kapar & Rohit Rahi, 2024. "Centralized vs Decentralized Markets: The Role of Connectivity," Working Papers 1420, Barcelona School of Economics.
    5. Pignataro, Giuseppe & Raggi, Davide & Pancotto, Francesca, 2024. "On the role of fundamentals, private signals, and beauty contests to predict exchange rates," International Journal of Forecasting, Elsevier, vol. 40(2), pages 687-705.

  4. Alfarano, Simone & Banal-Estanol, Albert & Camacho-Cuena, Eva & Iori, Giulia & Kapar, Burcu, 2020. "Centralized vs decentralized markets in the laboratory: The role of connectivity," MPRA Paper 99129, University Library of Munich, Germany.

    Cited by:

    1. Alba Ruiz-Buforn & Simone Alfarano & Eva Camacho-Cuena & Andrea Morone, 2022. "Single vs. multiple disclosures in an experimental asset market with information acquisition," The European Journal of Finance, Taylor & Francis Journals, vol. 28(13-15), pages 1513-1539, October.

  5. Annarita Colasante & Simone Alfarano & Eva Camacho-Cuena, 2019. "Heuristic Switching Model and Exploration-Explotation Algorithm to describe long-run expectations in LtFEs: A comparison," Working Papers 2019/02, Economics Department, Universitat Jaume I, Castellón (Spain).

    Cited by:

    1. Domenico Delli Gatti & Filippo Gusella & Giorgio Ricchiuti, 2024. "Endogenous vs Exogenous Instability: An Out-of-Sample Comparison," CESifo Working Paper Series 11082, CESifo.

  6. Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2019. "Exploiting ergodicity in forecasts of corporate profitability," BERG Working Paper Series 147, Bamberg University, Bamberg Economic Research Group.

    Cited by:

    1. Ellis Scharfenaker, 2020. "Statistical Equilibrium Methods in Analytical Political Economy," Working Paper Series, Department of Economics, University of Utah 2020_05, University of Utah, Department of Economics.
    2. Arata, Yoshiyuki & Mundt, Philipp, 2019. "Topology and formation of production input interlinkages: Evidence from Japanese microdata," BERG Working Paper Series 152, Bamberg University, Bamberg Economic Research Group.
    3. Scharfenaker, Ellis, 2020. "Implications of quantal response statistical equilibrium," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    4. March, Christoph & Sahm, Marco, 2019. "The Perks of Being in the Smaller Team: Incentives in Overlapping Contests," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203509, Verein für Socialpolitik / German Economic Association.
    5. Proaño, Christian R. & Lojak, Benjamin, 2020. "Animal spirits, risk premia and monetary policy at the zero lower bound," Journal of Economic Behavior & Organization, Elsevier, vol. 171(C), pages 221-233.
    6. Jan Schulz & Daniel M. Mayerhoffer, 2022. "A Network Approach to Consumption," Papers 2203.14259, arXiv.org, revised Apr 2022.
    7. Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2020. "Survival and the ergodicity of corporate profitability," BERG Working Paper Series 162, Bamberg University, Bamberg Economic Research Group.
    8. Mundt, Philipp & Cantner, Uwe & Inoue, Hiroyasu & Savin, Ivan & Vannuccini, Simone, 2021. "Market selection in global value chains," BERG Working Paper Series 170, Bamberg University, Bamberg Economic Research Group.
    9. Sahm, Marco, 2022. "Optimal accuracy of unbiased Tullock contests with two heterogeneous players," BERG Working Paper Series 175, Bamberg University, Bamberg Economic Research Group.
    10. Francesco Menoncin & Paolo Panteghini & Luca Regis, 2021. "Optimal Firm's Dividend and Capital Structure for Mean Reverting Profitability," CESifo Working Paper Series 9407, CESifo.

  7. Annarita Colasante & Simone Alfarano & Eva Camacho-Cuena, 2018. "The term structure of cross-sectional dispersion of expectations in a Learning-to-Forecast Experiment," Working Papers 2018/02, Economics Department, Universitat Jaume I, Castellón (Spain).

    Cited by:

    1. Simone Alfarano & Eva Camacho-Cuena & Annarita Colasante & Alba Ruiz-Buforn, 2024. "The effect of time-varying fundamentals in learning-to-forecast experiments," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 19(4), pages 619-647, October.
    2. Domenico Delli Gatti & Filippo Gusella & Giorgio Ricchiuti, 2024. "Endogenous vs Exogenous Instability: An Out-of-Sample Comparison," CESifo Working Paper Series 11082, CESifo.
    3. Colasante, Annarita & Alfarano, Simone & Camacho-Cuena, Eva, 2019. "Heuristic Switching Model and Exploration-Explotation Algorithm to describe long-run expectations in LtFEs: a comparison," MPRA Paper 92391, University Library of Munich, Germany.
    4. Pignataro, Giuseppe & Raggi, Davide & Pancotto, Francesca, 2024. "On the role of fundamentals, private signals, and beauty contests to predict exchange rates," International Journal of Forecasting, Elsevier, vol. 40(2), pages 687-705.
    5. Toshiaki Akinaga & Takanori Kudo & Kenju Akai, 2023. "Interaction between price and expectations in the jar-guessing experimental market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(3), pages 491-532, July.

  8. Ruiz-Buforn, Alba & Alfarano, Simone & Camacho-Cuena, Eva & Morone, Andrea, 2018. "Crowding out effect and traders' overreliance on public information in financial markets: a lesson from the lab," MPRA Paper 88866, University Library of Munich, Germany.

    Cited by:

    1. Ruiz-Buforn, Alba & Alfarano, Simone & Camacho-Cuena, Eva, 2019. "Price distortions and public information: theory, experiments and simulations," MPRA Paper 93288, University Library of Munich, Germany.
    2. Ruiz-Buforn, Alba & Alfarano, Simone & Morone, Andrea, 2019. "Welfare effects of public information in a laboratory financial market," MPRA Paper 95424, University Library of Munich, Germany.

  9. David Vidal-Tomás & Simone Alfarano, 2018. "An agent based early warning indicator for financial market instability," Working Papers 2018/12, Economics Department, Universitat Jaume I, Castellón (Spain).

    Cited by:

    1. Vidal-Tomás, David, 2022. "Which cryptocurrency data sources should scholars use?," International Review of Financial Analysis, Elsevier, vol. 81(C).
    2. Steinbacher, Mitja & Raddant, Matthias & Karimi, Fariba & Camacho-Cuena, Eva & Alfarano, Simone & Iori, Giulia & Lux, Thomas, 2021. "Advances in the Agent-Based Modeling of Economic and Social Behavior," MPRA Paper 107317, University Library of Munich, Germany.
    3. Gangwal, Utkarsh & Dong, Shangjia, 2022. "Critical facility accessibility rapid failure early-warning detection and redundancy mapping in urban flooding," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    4. Goodell, John W. & Kumar, Satish & Rao, Purnima & Verma, Shubhangi, 2023. "Emotions and stock market anomalies: A systematic review," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    5. Oh, Sebeom & Ku, Hyejin & Jun, Doobae, 2022. "A comparative analysis of housing prices in different cities using the Black–Scholes and Jump Diffusion models," Finance Research Letters, Elsevier, vol. 46(PA).
    6. Caferra, Rocco & Vidal-Tomás, David, 2021. "Who raised from the abyss? A comparison between cryptocurrency and stock market dynamics during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 43(C).

  10. Blanco-Arroyo, Omar & Ruiz-Buforn, Alba & Vidal-Tomás, David & Alfarano, Simone, 2018. "On the determination of the granular size of the economy," MPRA Paper 87599, University Library of Munich, Germany.

    Cited by:

    1. Santiago Camara, 2022. "Granular Linkages, Supplier Cost Shocks & Export Performance," Working Papers 153, Red Nacional de Investigadores en Economía (RedNIE).
    2. Jozef Konings & Galiya Sagyndykova & Venkat Subramanian & Astrid Volckaert, 2021. "The granular economy of Kazakhstan," Working Papers 2021/01, Nazarbayev University, Graduate School of Business.
    3. Murilo Silva & Sergio Da Silva, 2020. "The Brazilian granular business cycle," Economics Bulletin, AccessEcon, vol. 40(1), pages 463-472.
    4. Maia, Adriano & Oliveira, Guilherme De & Matsushita, Raul & Da Silva, Sergio, 2021. "The granularity of the Brazilian banking market," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    5. Svetlana Popova, 2019. "Idiosyncratic shocks: estimation and the impact on aggregate fluctuations," Bank of Russia Working Paper Series wps46, Bank of Russia.
    6. Leon Esquierro & Sergio Da Silva, 2024. "Is the Brazilian labor market granular?," Economics Bulletin, AccessEcon, vol. 44(2), pages 576-585.
    7. Blanco-Arroyo, Omar & Ruiz-Buforn, Alba & Vidal-Tomás, David & Alfarano, Simone, 2019. "Empresas granulares y desagregación regional: un análisis del caso español [Granular firms and regional disaggregation: an analysis of the Spanish case]," MPRA Paper 93913, University Library of Munich, Germany.
    8. Alfarano, Simone & Blanco-Arroyo, Omar, 2022. "Banking sector concentration, credit shocks and aggregate fluctuations," Economics Letters, Elsevier, vol. 218(C).
    9. David Vidal-Tomás & Alba Ruiz-Buforn & Omar Blanco-Arroyo & Simone Alfarano, 2022. "A Cross-Sectional Analysis of Growth and Profit Rate Distribution: The Spanish Case," Mathematics, MDPI, vol. 10(6), pages 1-20, March.
    10. Jozef Konings & Galiya Sagyndykova & Venkat Subramanian & Astrid Volckaert, 2023. "The granular nature of emerging market economies: The case of Kazakhstan," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 31(2), pages 429-464, April.
    11. Carlos Melo Gouveia & Cristina Manteu & Sónia Cabral, 2020. "The granularity of Portuguese firm-level exports," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    12. Adriano Maia & Guilherme De Oliveira & Raul Matsushita & Sergio Da Silva, 2023. "Granular banks and corporate investment," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(3), pages 586-599, September.
    13. Alfarano, Simone & Blanco-Arroyo, Omar, 2022. "Banking Sector Concentration, Credit Supply Shocks and Aggregate Fluctuations," MPRA Paper 111972, University Library of Munich, Germany.

  11. Annarita Colasante & Simone Alfarano & Eva Camacho-Cuena & Mauro Gallegati, 2017. "Long-run expectations in a Learning-to-Forecast Experiment: A Simulation Approach," Working Papers 2017/03, Economics Department, Universitat Jaume I, Castellón (Spain).

    Cited by:

    1. Annarita Colasante & Simone Alfarano & Eva Camacho-Cuena, 2019. "The term structure of cross-sectional dispersion of expectations in a Learning-to-Forecast Experiment," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(3), pages 491-520, September.
    2. Evans, George W. & Hommes, Cars & McGough, Bruce & Salle, Isabelle, 2022. "Are long-horizon expectations (de-)stabilizing? Theory and experiments," Journal of Monetary Economics, Elsevier, vol. 132(C), pages 44-63.
    3. Breunig, Christoph & Grabova, Iuliia & Haan, Peter & Weinhardt, Felix & Weizsäcker, Georg, 2019. "Long-run Expectations of Households," Rationality and Competition Discussion Paper Series 218, CRC TRR 190 Rationality and Competition.
    4. 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).
    5. Domenico Delli Gatti & Filippo Gusella & Giorgio Ricchiuti, 2024. "Endogenous vs Exogenous Instability: An Out-of-Sample Comparison," CESifo Working Paper Series 11082, CESifo.
    6. Mikhail Anufriev & Aleksei Chernulich & Jan Tuinstra, 2020. "Asset Price Volatility and Investment Horizons: An Experimental Investigation," Working Papers 20200053, New York University Abu Dhabi, Department of Social Science, revised Aug 2020.
    7. Colasante, Annarita & Alfarano, Simone & Camacho-Cuena, Eva, 2019. "Heuristic Switching Model and Exploration-Explotation Algorithm to describe long-run expectations in LtFEs: a comparison," MPRA Paper 92391, University Library of Munich, Germany.
    8. Bao, Te & Füllbrunn, Sascha & Pei, Jiaoying & Zong, Jichuan, 2024. "Reading the market? Expectation coordination and theory of mind," Journal of Economic Behavior & Organization, Elsevier, vol. 219(C), pages 510-527.
    9. Zhou Lu & Te Bao & Xiaohua Yu, 2021. "Gender and Bubbles in Experimental Markets with Positive and Negative Expectation Feedback," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1307-1326, April.
    10. Biondo, Alessio Emanuele, 2017. "Learning to forecast, risk aversion, and microstructural aspects of financial stability," Economics Discussion Papers 2017-104, Kiel Institute for the World Economy (IfW Kiel).

  12. Annarita Colasante & Simone Alfarano & Eva Camacho-Cuena & Mauro Gallegati, 2016. "Long-run expectations in a Learning-to-Forecast Experiment," Working Papers 2016/26, Economics Department, Universitat Jaume I, Castellón (Spain).

    Cited by:

    1. Anita (A.G.) Kopanyi-Peuker & Matthias Weber, 2018. "Experience Does not Eliminate Bubbles: Experimental Evidence," Tinbergen Institute Discussion Papers 18-092/II, Tinbergen Institute.
    2. Annarita Colasante & Simone Alfarano & Eva Camacho-Cuena, 2019. "The term structure of cross-sectional dispersion of expectations in a Learning-to-Forecast Experiment," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(3), pages 491-520, September.
    3. Colasante, Annarita & Alfarano, Simone & Camacho Cuena, Eva & Gallegati, Mauro, 2017. "Long-run expectations in a Learning-to-Forecast-Experiment: a simulation approach," MPRA Paper 77618, University Library of Munich, Germany.
    4. Biondo, Alessio Emanuele, 2018. "Learning to forecast, risk aversion, and microstructural aspects of financial stability," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 12, pages 1-21.
    5. 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).
    6. Simone Alfarano & Eva Camacho-Cuena & Annarita Colasante & Alba Ruiz-Buforn, 2024. "The effect of time-varying fundamentals in learning-to-forecast experiments," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 19(4), pages 619-647, October.
    7. Domenico Delli Gatti & Filippo Gusella & Giorgio Ricchiuti, 2024. "Endogenous vs Exogenous Instability: An Out-of-Sample Comparison," CESifo Working Paper Series 11082, CESifo.
    8. Colasante, Annarita & Alfarano, Simone & Camacho-Cuena, Eva, 2019. "Heuristic Switching Model and Exploration-Explotation Algorithm to describe long-run expectations in LtFEs: a comparison," MPRA Paper 92391, University Library of Munich, Germany.
    9. Pignataro, Giuseppe & Raggi, Davide & Pancotto, Francesca, 2024. "On the role of fundamentals, private signals, and beauty contests to predict exchange rates," International Journal of Forecasting, Elsevier, vol. 40(2), pages 687-705.
    10. Makarewicz, Tomasz, 2021. "Traders, forecasters and financial instability: A model of individual learning of anchor-and-adjustment heuristics," Journal of Economic Behavior & Organization, Elsevier, vol. 190(C), pages 626-673.
    11. Makarewicz, Tomasz, 2019. "Traders, forecasters and financial instability: A model of individual learning of anchor-and-adjustment heuristics," BERG Working Paper Series 141, Bamberg University, Bamberg Economic Research Group.
    12. Zhou Lu & Te Bao & Xiaohua Yu, 2021. "Gender and Bubbles in Experimental Markets with Positive and Negative Expectation Feedback," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1307-1326, April.
    13. Morone, Andrea & Caferra, Rocco, 2020. "Inequalities in financial markets: Evidences from a laboratory experiment," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 88(C).

  13. Omar Blanco & Simone Alfarano, 2016. "Granularity of the business cycle fluctuations: The Spanish case," Working Papers 2016/25, Economics Department, Universitat Jaume I, Castellón (Spain).

    Cited by:

    1. Jozef Konings & Galiya Sagyndykova & Venkat Subramanian & Astrid Volckaert, 2021. "The granular economy of Kazakhstan," Working Papers 2021/01, Nazarbayev University, Graduate School of Business.
    2. Carlos Melo Gouveia & Cristina Manteu & Sónia Cabral, 2020. "The granularity of Portuguese firm-level exports," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    3. Tatsuro Senga & Iacopo Varotto, 2018. "Idiosyncratic shocks and the role of granularity in business cycle," 2018 Meeting Papers 1012, Society for Economic Dynamics.

  14. Marko Petrovic & Andrea Teglio & Simone Alfarano, 2016. "The role of bank credit allocation: Evidence from the Spanish economy," Working Papers 2016/17, Economics Department, Universitat Jaume I, Castellón (Spain).

    Cited by:

    1. Marko Petrovic & Bulent Ozel & Andrea Teglio & Marco Raberto & Silvano Cincotti, 2017. "Eurace Open: An agent-based multi-country model," Working Papers 2017/09, Economics Department, Universitat Jaume I, Castellón (Spain).

  15. Alfarano, Simone & Camacho, Eva & Morone, Andrea, 2015. "Do investors rely too much on public information to be justified by its accuracy? An experimental study," FinMaP-Working Papers 30, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.

    Cited by:

    1. Nuzzo, Simone & Morone, Andrea, 2017. "Asset markets in the lab: A literature review," Journal of Behavioral and Experimental Finance, Elsevier, vol. 13(C), pages 42-50.
    2. Rocco Caferra & Simone Nuzzo & Andrea Morone, 2023. "“Less is more” or “more is better”? The effect of asymmetric information distribution on market efficiency and wealth inequality," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(2), pages 233-250, April.
    3. Zonna, Davide, 2016. "Sprechi di cibo e tentativi di riduzione. Un caso sperimentale [Avoiding food waste. A field experiment]," MPRA Paper 76097, University Library of Munich, Germany.
    4. Barreda Tarrazona, Iván J. & Grimalda, Gianluca & Morone, Andrea & Nuzzo, Simone & Teglio, Andrea, 2017. "Centralizing information improves market efficiency more than increasing information: Results from experimental asset markets," Kiel Working Papers 2072, Kiel Institute for the World Economy (IfW Kiel).
    5. Merl, Robert, 2022. "Literature review of experimental asset markets with insiders," Journal of Behavioral and Experimental Finance, Elsevier, vol. 33(C).

  16. Philipp Mundt & Mishael Milakovic & Simone Alfarano, 2014. "Gibrat's law redux: Think profitability instead of growth," Working Papers 2014/02, Economics Department, Universitat Jaume I, Castellón (Spain).

    Cited by:

    1. Schmitt, Noemi & Tuinstra, Jan & Westerhoff, Frank, 2017. "Side effects of nonlinear profit taxes in an evolutionary market entry model: Abrupt changes, coexisting attractors and hysteresis problems," Journal of Economic Behavior & Organization, Elsevier, vol. 135(C), pages 15-38.
    2. Ellis Scharfenaker, 2020. "Statistical Equilibrium Methods in Analytical Political Economy," Working Paper Series, Department of Economics, University of Utah 2020_05, University of Utah, Department of Economics.
    3. Herold, Florian & Kuzmics, Christoph, 2016. "The evolution of taking roles," BERG Working Paper Series 115, Bamberg University, Bamberg Economic Research Group.
    4. March, Christoph & Sahm, Marco, 2017. "Asymmetric discouragement in asymmetric contests," Economics Letters, Elsevier, vol. 151(C), pages 23-27.
    5. Oh, Ilfan, 2019. "Autonomy of profit rate distribution and its dynamics from firm size measures: A statistical equilibrium approach," BERG Working Paper Series 146, Bamberg University, Bamberg Economic Research Group.
    6. González-Díaz, Julio & Herold, Florian & Domínguez, Diego, 2016. "Strategic sequential voting," BERG Working Paper Series 113, Bamberg University, Bamberg Economic Research Group.
    7. Schmitt, Noemi & Westerhoff, Frank, 2015. "Evolutionary competition and profit taxes: market stability versus tax burden," BERG Working Paper Series 104, Bamberg University, Bamberg Economic Research Group.
    8. Bexheti, Abdylmenaf & Mustafi, Besime, 2015. "Impact of public funding of education on economic growth in Macedonia," BERG Working Paper Series 98, Bamberg University, Bamberg Economic Research Group.
    9. Scharfenaker, Ellis, 2020. "Implications of quantal response statistical equilibrium," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    10. Lojak, Benjamin, 2016. "Sentiment-driven investment, non-linear corporate debt dynamics and co-existing business cycle regimes," BERG Working Paper Series 112, Bamberg University, Bamberg Economic Research Group.
    11. Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2020. "Survival and the ergodicity of corporate profitability," BERG Working Paper Series 162, Bamberg University, Bamberg Economic Research Group.
    12. Chien-Nan Chen & Chengli Tien & Bernard Gan, 2019. "The postentry performance of business groups’ new venture affiliates," Australian Journal of Management, Australian School of Business, vol. 44(2), pages 325-343, May.
    13. Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2020. "Exploiting ergodicity in forecasts of corporate profitability," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    14. David Vidal-Tomás & Alba Ruiz-Buforn & Omar Blanco-Arroyo & Simone Alfarano, 2022. "A Cross-Sectional Analysis of Growth and Profit Rate Distribution: The Spanish Case," Mathematics, MDPI, vol. 10(6), pages 1-20, March.
    15. Williams, Michael A. & Baek, Grace & Park, Leslie Y. & Zhao, Wei, 2016. "Global evidence on the distribution of economic profit rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 356-363.
    16. Sahm, Marco, 2017. "Are sequential round-robin tournaments discriminatory?," BERG Working Paper Series 121, Bamberg University, Bamberg Economic Research Group.
    17. Dräger, Lena & Proaño, Christian R., 2015. "Cross-border banking and business cycles in asymmetric currency unions," BERG Working Paper Series 105, Bamberg University, Bamberg Economic Research Group.
    18. Proaño, Christian R. & Lojak, Benjamin, 2015. "Debt stabilization and macroeconomic volatility in monetary unions under heterogeneous sovereign risk perceptions," BERG Working Paper Series 106, Bamberg University, Bamberg Economic Research Group.
    19. Sahm, Marco, 2016. "Advance-purchase financing of projects with few buyers," BERG Working Paper Series 118, Bamberg University, Bamberg Economic Research Group.
    20. Fatoke-Dato, Mafaïzath A., 2015. "Impact of income shock on children's schooling and labor in a West African country," BERG Working Paper Series 102, Bamberg University, Bamberg Economic Research Group.
    21. Jan Schulz & Daniel M. Mayerhoffer, 2021. "Equal chances, unequal outcomes? Network-based evolutionary learning and the industrial dynamics of superstar firms," Journal of Business Economics, Springer, vol. 91(9), pages 1357-1385, November.
    22. Fatoke-Dato, Mafaïzath A., 2015. "Impact of an educational demand-and-supply policy on girls' education in West Africa: Heterogeneity in income, school environment and ethnicity," BERG Working Paper Series 101, Bamberg University, Bamberg Economic Research Group.
    23. Schmitt, Noemi & Westerhoff, Frank, 2016. "Herding behavior and volatility clustering in financial markets," BERG Working Paper Series 107, Bamberg University, Bamberg Economic Research Group.
    24. Sahm, Marco, 2017. "Risk aversion and prudence in contests," BERG Working Paper Series 120, Bamberg University, Bamberg Economic Research Group.
    25. Arata, Yoshiyuki, 2019. "Firm growth and Laplace distribution: The importance of large jumps," Journal of Economic Dynamics and Control, Elsevier, vol. 103(C), pages 63-82.
    26. Meyer, Dietmar & Shera, Adela, 2015. "Remittances' impact on the labor supply and on the deficit of current account," BERG Working Paper Series 97, Bamberg University, Bamberg Economic Research Group.

  17. Giacomo Livan & Simone Alfarano & Mishael Milakovic & Enrico Scalas, 2014. "A spectral perspective on excess volatility," Working Papers 2014/13, Economics Department, Universitat Jaume I, Castellón (Spain).

    Cited by:

    1. Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2020. "Survival and the ergodicity of corporate profitability," BERG Working Paper Series 162, Bamberg University, Bamberg Economic Research Group.
    2. Chakrabarti, Arnab & Chakrabarti, Anindya S., 2020. "Fractional Differencing: (In)stability of Spectral Structure and Risk Measures of Financial Networks," IIMA Working Papers WP 2020-07-01, Indian Institute of Management Ahmedabad, Research and Publication Department.

  18. Alfarano, Simone & Förster, Niels & Milaković, Mishael & Mundt, Philipp, 2013. "The real versus the financial economy: A global tale of stability versus volatility," Economics Discussion Papers 2013-8, Kiel Institute for the World Economy (IfW Kiel).

    Cited by:

    1. Livan, Giacomo & Alfarano, Simone & Milakovic, Mishael & Scalas, Enrico, 2014. "A spectral perspective on excess volatility," FinMaP-Working Papers 12, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    2. Philipp Mundt & Mishael Milakovic & Simone Alfarano, 2014. "Gibrat's law redux: Think profitability instead of growth," Working Papers 2014/02, Economics Department, Universitat Jaume I, Castellón (Spain).
    3. David Vidal-Tomás & Alba Ruiz-Buforn & Omar Blanco-Arroyo & Simone Alfarano, 2022. "A Cross-Sectional Analysis of Growth and Profit Rate Distribution: The Spanish Case," Mathematics, MDPI, vol. 10(6), pages 1-20, March.

  19. Einar Jón Erlingsson & Simone Alfarano & Marco Raberto & Hlynur Stefánssonn, 2012. "On the distributional properties of size, profit and growth of Icelandic firms," Working Papers 2012/01, Economics Department, Universitat Jaume I, Castellón (Spain).

    Cited by:

    1. Thomas Brenner & Matthias Duschl, 2018. "Modeling Firm and Market Dynamics: A Flexible Model Reproducing Existing Stylized Facts on Firm Growth," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 745-772, October.
    2. Williams, Michael A. & Pinto, Brijesh P. & Park, David, 2015. "Global evidence on the distribution of firm growth rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 102-107.
    3. Oh, Ilfan, 2019. "Autonomy of profit rate distribution and its dynamics from firm size measures: A statistical equilibrium approach," BERG Working Paper Series 146, Bamberg University, Bamberg Economic Research Group.
    4. Delmar, Frédéric & Wallin, Jonas & Nofal, Ahmed Maged, 2022. "Modeling new-firm growth and survival with panel data using event magnitude regression," Journal of Business Venturing, Elsevier, vol. 37(5).
    5. Anna Maria Fiori, 2020. "On firm size distribution: statistical models, mechanisms, and empirical evidence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(3), pages 447-482, September.
    6. Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2020. "Exploiting ergodicity in forecasts of corporate profitability," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    7. Marko Petrović & Andrea Teglio & Simone Alfarano, 2022. "Credit allocation and the financial crisis: evidence from Spanish companies," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(4), pages 1069-1114, October.
    8. David Vidal-Tomás & Alba Ruiz-Buforn & Omar Blanco-Arroyo & Simone Alfarano, 2022. "A Cross-Sectional Analysis of Growth and Profit Rate Distribution: The Spanish Case," Mathematics, MDPI, vol. 10(6), pages 1-20, March.
    9. Halvarsson, Daniel, 2013. "Identifying High-Growth Firms," Ratio Working Papers 215, The Ratio Institute.
    10. Metzig, Cornelia & Gordon, Mirta B., 2014. "A model for scaling in firms’ size and growth rate distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 398(C), pages 264-279.
    11. Mundt, Philipp & Förster, Niels & Alfarano, Simone & Milaković, Mishael, 2014. "The real versus the financial economy: A global tale of stability versus volatility," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 8, pages 1-26.
    12. Williams, Michael A. & Baek, Grace & Park, Leslie Y. & Zhao, Wei, 2016. "Global evidence on the distribution of economic profit rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 356-363.
    13. Silvano Cincotti & Marco Raberto & Andrea Teglio, 2022. "Why do we need agent-based macroeconomics?," Review of Evolutionary Political Economy, Springer, vol. 3(1), pages 5-29, April.
    14. Matthias Duschl & Shi-Shu Peng, 2013. "Chinese firm dynamics and the role of ownership type A conditional estimation approach of the Asymmetric Exponential Power (AEP) density," Papers on Economics and Evolution 2014-01, Philipps University Marburg, Department of Geography.
    15. Jan Schulz & Daniel M. Mayerhoffer, 2021. "Equal chances, unequal outcomes? Network-based evolutionary learning and the industrial dynamics of superstar firms," Journal of Business Economics, Springer, vol. 91(9), pages 1357-1385, November.
    16. ARATA Yoshiyuki, 2014. "Firm Growth and Laplace Distribution: The importance of large jumps," Discussion papers 14033, Research Institute of Economy, Trade and Industry (RIETI).

  20. Alfarano, Simone & Milakovic, Mishael & Raddant, Matthias, 2011. "A Note on institutional hierarchy and volatility in financial markets," MPRA Paper 30902, University Library of Munich, Germany.

    Cited by:

    1. Adri'an Carro & Ra'ul Toral & Maxi San Miguel, 2016. "The noisy voter model on complex networks," Papers 1602.06935, arXiv.org, revised Apr 2016.
    2. Song-min Yu & Lei Zhu, 2017. "Impact of Firms’ Observation Network on the Carbon Market," Energies, MDPI, vol. 10(8), pages 1-14, August.
    3. David Vidal-Tomás & Simone Alfarano, 2020. "An agent-based early warning indicator for financial market instability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 49-87, January.
    4. Kononovicius, A. & Gontis, V., 2014. "Control of the socio-economic systems using herding interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 80-84.
    5. Zhang, Junhuan, 2018. "Influence of individual rationality on continuous double auction markets with networked traders," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 353-392.
    6. Matthias Raddant & Mishael Milaković & Laura Birg, 2017. "Persistence in corporate networks," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(2), pages 249-276, July.
    7. Aleksejus Kononovicius, 2017. "Empirical Analysis and Agent-Based Modeling of the Lithuanian Parliamentary Elections," Complexity, Hindawi, vol. 2017, pages 1-15, November.
    8. Aleksejus Kononovicius & Vygintas Gontis, 2014. "Herding interactions as an opportunity to prevent extreme events in financial markets," Papers 1409.8024, arXiv.org, revised May 2015.
    9. Gonzalo Bohorquez & John Cartlidge, 2024. "Simulation of Social Media-Driven Bubble Formation in Financial Markets using an Agent-Based Model with Hierarchical Influence Network," Papers 2409.00742, arXiv.org.
    10. Adri'an Carro & Ra'ul Toral & Maxi San Miguel, 2015. "Markets, herding and response to external information," Papers 1506.03708, arXiv.org, revised Jun 2015.
    11. Adrián Carro & Raúl Toral & Maxi San Miguel, 2015. "Markets, Herding and Response to External Information," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-28, July.
    12. Adri'an Carro & Ra'ul Toral & Maxi San Miguel, 2013. "Signal amplification in an agent-based herding model," Papers 1302.6477, arXiv.org, revised Sep 2015.
    13. Junhuan Zhang & Peter McBurney & Katarzyna Musial, 2018. "Convergence of trading strategies in continuous double auction markets with boundedly-rational networked traders," Review of Quantitative Finance and Accounting, Springer, vol. 50(1), pages 301-352, January.

  21. Milakovic, Mishael & Alfarano, Simone & Lux, Thomas, 2011. "The small core of the German corporate board network: New evidence from 2010," Kiel Working Papers 1740, Kiel Institute for the World Economy (IfW Kiel).

    Cited by:

    1. Carlo Drago & Roberto Ricciuti & Paolo Santella, 2015. "An Attempt to Disperse the Italian Interlocking Directorship Network: Analyzing the Effects of the 2011 Reform," Working Papers 2015.82, Fondazione Eni Enrico Mattei.
    2. Giglio, Ricardo & Lux, Thomas, 2016. "The core of the global corporate network," FinMaP-Working Papers 59, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.

  22. Milakovic, Mishael & Alfarano, Simone & Lux, Thomas, 2011. "The small core of the German corporate board network: New evidence from 2010," Kiel Working Papers 1740, Kiel Institute for the World Economy (IfW Kiel).

    Cited by:

    1. Carlo Drago & Roberto Ricciuti & Paolo Santella, 2015. "An Attempt to Disperse the Italian Interlocking Directorship Network: Analyzing the Effects of the 2011 Reform," Working Papers 2015.82, Fondazione Eni Enrico Mattei.
    2. Giglio, Ricardo & Lux, Thomas, 2016. "The core of the global corporate network," FinMaP-Working Papers 59, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.

  23. G. Livan & S. Alfarano & E. Scalas, 2011. "The fine structure of spectral properties for random correlation matrices: an application to financial markets," Papers 1102.4076, arXiv.org.

    Cited by:

    1. Antti J Tanskanen & Jani Lukkarinen & Kari Vatanen, 2018. "Random selection of factors preserves the correlation structure in a linear factor model to a high degree," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-22, December.
    2. Raddant, Matthias & Wagner, Friedrich, 2014. "Transitions in the stock markets of the US, UK, and Germany," Kiel Working Papers 1979, Kiel Institute for the World Economy (IfW Kiel).
    3. M. Raddant & T. Di Matteo, 2023. "A Look at Financial Dependencies by Means of Econophysics and Financial Economics," Papers 2302.08208, arXiv.org.
    4. Livan, Giacomo & Alfarano, Simone & Milakovic, Mishael & Scalas, Enrico, 2014. "A spectral perspective on excess volatility," FinMaP-Working Papers 12, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    5. Giacomo Livan & Jun-ichi Inoue & Enrico Scalas, 2012. "On the non-stationarity of financial time series: impact on optimal portfolio selection," Papers 1205.0877, arXiv.org, revised Jul 2012.
    6. Riccardo Marcaccioli & Giacomo Livan, 2019. "Maximum Entropy approach to multivariate time series randomization," Papers 1907.04925, arXiv.org, revised Jun 2020.
    7. Marcaccioli, Riccardo & Livan, Giacomo, 2020. "Maximum entropy approach to multivariate time series randomization," LSE Research Online Documents on Economics 115284, London School of Economics and Political Science, LSE Library.
    8. Raddant, Matthias & Wagner, Friedrich, 2013. "Phase transition in the S&P stock market," Kiel Working Papers 1846, Kiel Institute for the World Economy (IfW Kiel).
    9. Bury, Thomas, 2014. "Predicting trend reversals using market instantaneous state," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 404(C), pages 79-91.
    10. Thomas Bury, 2014. "Collective behaviours in the stock market -- A maximum entropy approach," Papers 1403.5179, arXiv.org, revised Mar 2014.
    11. Thomas Bury, 2013. "Predicting trend reversals using market instantaneous state," Papers 1310.8169, arXiv.org, revised Mar 2014.
    12. Fricke, Daniel, 2012. "Trading strategies in the overnight money market: Correlations and clustering on the e-MID trading platform," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(24), pages 6528-6542.
    13. Giacomo Livan & Luca Rebecchi, 2012. "Asymmetric correlation matrices: an analysis of financial data," Papers 1201.6535, arXiv.org, revised Apr 2012.
    14. Anshul Verma & Orazio Angelini & Tiziana Di Matteo, 2019. "A new set of cluster driven composite development indicators," Papers 1911.11226, arXiv.org, revised Mar 2020.
    15. Longfeng Zhao & Wei Li & Andrea Fenu & Boris Podobnik & Yougui Wang & H. Eugene Stanley, 2017. "The q-dependent detrended cross-correlation analysis of stock market," Papers 1705.01406, arXiv.org, revised Jun 2017.
    16. Yi†Hui Zhou & J. S. Marron & Fred A. Wright, 2018. "Eigenvalue significance testing for genetic association," Biometrics, The International Biometric Society, vol. 74(2), pages 439-447, June.
    17. Anshul Verma & Riccardo Junior Buonocore & Tiziana di Matteo, 2017. "A cluster driven log-volatility factor model: a deepening on the source of the volatility clustering," Papers 1712.02138, arXiv.org, revised May 2018.
    18. Gerardo-Giorda, Luca & Germano, Guido & Scalas, Enrico, 2015. "Large scale simulation of synthetic markets," LSE Research Online Documents on Economics 67563, London School of Economics and Political Science, LSE Library.

  24. Simone Alfarano & Thomas Lux, 2011. "Extreme value theory as a theoretical background for power law behavior," Working Papers 2011/02, Economics Department, Universitat Jaume I, Castellón (Spain).

    Cited by:

    1. 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.
    2. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.
    3. Omar Blanco & Simone Alfarano, 2016. "Granularity of the business cycle fluctuations: The Spanish case," Working Papers 2016/25, Economics Department, Universitat Jaume I, Castellón (Spain).
    4. Laurent Gauthier, 2024. "Digital Humanities, Complexity Sciences and the Modeling of Ancient Greek Culture," Working Papers hal-03315002, HAL.

  25. Simone Alfarano & Andrea Morone & Eva Camacho, 2011. "The role of public and private information in a laboratory financial market," Working Papers. Serie AD 2011-06, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).

    Cited by:

    1. Nuzzo, Simone & Morone, Andrea, 2017. "Asset markets in the lab: A literature review," Journal of Behavioral and Experimental Finance, Elsevier, vol. 13(C), pages 42-50.
    2. Romain Baeriswyl & Camille Cornand, 2016. "The predominant role of signal precision in experimental beauty contest," Post-Print halshs-01236276, HAL.
    3. Alanoud Al-Maadid & Guglielmo Maria Caporale & Fabio Spagnolo & Nicola Spagnolo, 2018. "The Impact of Business and Political News on the GCC Stock Markets," CESifo Working Paper Series 7353, CESifo.
    4. Andrea Morone & Giovanni Ferri, 2008. "The Effect of Rating Agencies on Herd Behaviour," SERIES 0022, Dipartimento di Economia e Finanza - Università degli Studi di Bari "Aldo Moro", revised Nov 2008.
    5. Adriana Gabriela Breaban & Juan Carlos Matallín-Sáez & Iván Barreda-Tarrazona & Mª Rosario Balaguer-Franch, 2012. "The demand for structured products: an experimental approach," Working Papers 2012/15, Economics Department, Universitat Jaume I, Castellón (Spain).
    6. Alfarano, Simone & Camacho, Eva & Petrovic, Marko & Provenzano, Giulia, 2014. "The Interplay between Public and Private Information in Asset Markets: Theoretical and Experimental Approaches," FinMaP-Working Papers 9, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    7. Andrea Morone & Simone Nuzzo, 2019. "Market efficiency, trading institutions and information mirages: evidence from a laboratory asset market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(2), pages 317-344, June.
    8. Kene Boun My & Camille Cornand & Rodolphe dos Santos Ferreira, 2017. "Speculation Rather than Enterprise ? Keyness Beauty Contest Revisited in Theory and Experiment," Post-Print hal-02510843, HAL.
    9. Morone, Andrea & Nuzzo, Simone, 2016. "Do Markets (Institutions) Drive Out Lemmings or Vice Versa?," MPRA Paper 74322, University Library of Munich, Germany.
    10. Camille Cornand & Frank Heinemann, 2015. "Macro-expérimentation autour des fonctions des banques centrales," Post-Print halshs-01232455, HAL.
    11. Andrea Morone & Simone Nuzzo, 2016. "Market Efficiency, Trading Institutions and Information Mirages: Evidence from an Experimental Asset Market," EERI Research Paper Series EERI RP 2016/17, Economics and Econometrics Research Institute (EERI), Brussels.
    12. Philipp Hornung & Ulrike Leopold-Wildburger & Roland Mestel & Stefan Palan, 2015. "Insider behavior under different market structures: experimental evidence on trading patterns, manipulation, and profitability," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 23(2), pages 357-373, June.
    13. Camille Cornand & Frank Heinemann, 2014. "Experiments on Monetary Policy and Central Banking," Research in Experimental Economics, in: Experiments in Macroeconomics, volume 17, pages 167-227, Emerald Group Publishing Limited.
    14. Barreda Tarrazona, Iván J. & Grimalda, Gianluca & Morone, Andrea & Nuzzo, Simone & Teglio, Andrea, 2017. "Centralizing information improves market efficiency more than increasing information: Results from experimental asset markets," Kiel Working Papers 2072, Kiel Institute for the World Economy (IfW Kiel).
    15. Owen Powell & Natalia Shestakova, 2017. "Experimental asset markets: behavior and bubbles," Chapters, in: Morris Altman (ed.), Handbook of Behavioural Economics and Smart Decision-Making, chapter 21, pages 375-391, Edward Elgar Publishing.

  26. Alfarano, Simone & Milakovic, Mishael, 2010. "Identification of Interaction Effects in Survey Expectations: A Cautionary Note," MPRA Paper 26002, University Library of Munich, Germany.

    Cited by:

    1. Schmitt, Noemi & Tuinstra, Jan & Westerhoff, Frank, 2017. "Side effects of nonlinear profit taxes in an evolutionary market entry model: Abrupt changes, coexisting attractors and hysteresis problems," Journal of Economic Behavior & Organization, Elsevier, vol. 135(C), pages 15-38.
    2. Juan G Brida & Bibiana Lanzilotta & Lucia I Rosich, 2021. "On the empirical relations between producers expectations and economic growth," Economics Bulletin, AccessEcon, vol. 41(3), pages 1970-1982.
    3. Juan Gabriel Brida & Bibiana Lanzilotta & Lucía Rosich, 2019. "Common trends in producers’ expectations, the nonlinear linkage with Uruguayan GDP and its implications in economic growth forecasting," Documentos de Trabajo (working papers) 19-28, Instituto de Economía - IECON.
    4. Schmitt, Noemi & Westerhoff, Frank, 2015. "Evolutionary competition and profit taxes: market stability versus tax burden," BERG Working Paper Series 104, Bamberg University, Bamberg Economic Research Group.
    5. Bexheti, Abdylmenaf & Mustafi, Besime, 2015. "Impact of public funding of education on economic growth in Macedonia," BERG Working Paper Series 98, Bamberg University, Bamberg Economic Research Group.
    6. Bibiana Lanzilotta Mernies, 2016. "Taxonomia y Dinamica de las Expectativas Economicas de los Empresarios Industriales en Uruguay. Un Analisis de Conglomerados," Revista de Economía del Rosario, Universidad del Rosario, vol. 17(2), pages 229-256, February.
    7. Franke, Reiner & Westerhoff, Frank, 2011. "Why a simple herding model may generate the stylized facts of daily returns: Explanation and estimation," BERG Working Paper Series 83, Bamberg University, Bamberg Economic Research Group.
    8. Franke, Reiner & Westerhoff, Frank, 2012. "Structural stochastic volatility in asset pricing dynamics: Estimation and model contest," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1193-1211.
    9. Dräger, Lena & Proaño, Christian R., 2015. "Cross-border banking and business cycles in asymmetric currency unions," BERG Working Paper Series 105, Bamberg University, Bamberg Economic Research Group.
    10. Proaño, Christian R. & Lojak, Benjamin, 2015. "Debt stabilization and macroeconomic volatility in monetary unions under heterogeneous sovereign risk perceptions," BERG Working Paper Series 106, Bamberg University, Bamberg Economic Research Group.
    11. Imami, Drini & Lami, Endrit & Kächelein, Holger, 2011. "Political cycles in income from privatization: The case of Albania," BERG Working Paper Series 77, Bamberg University, Bamberg Economic Research Group.
    12. Fatoke-Dato, Mafaïzath A., 2015. "Impact of income shock on children's schooling and labor in a West African country," BERG Working Paper Series 102, Bamberg University, Bamberg Economic Research Group.
    13. Fatoke-Dato, Mafaïzath A., 2015. "Impact of an educational demand-and-supply policy on girls' education in West Africa: Heterogeneity in income, school environment and ethnicity," BERG Working Paper Series 101, Bamberg University, Bamberg Economic Research Group.
    14. Schmitt, Noemi & Westerhoff, Frank, 2016. "Herding behavior and volatility clustering in financial markets," BERG Working Paper Series 107, Bamberg University, Bamberg Economic Research Group.
    15. Seregi, János & Lelovics, Zsuzsanna & Balogh, László, 2012. "The social welfare function of forests in the light of the theory of public goods," BERG Working Paper Series 87, Bamberg University, Bamberg Economic Research Group.
    16. Meyer, Dietmar & Shera, Adela, 2015. "Remittances' impact on the labor supply and on the deficit of current account," BERG Working Paper Series 97, Bamberg University, Bamberg Economic Research Group.

  27. Alfarano, Simone & Lux, Thomas & Wagner, Friedrich, 2010. "Excess Volatility and Herding in an Artificial Financial Market: Analytical Approach and Estimation," MPRA Paper 24719, University Library of Munich, Germany.

    Cited by:

    1. Sandrine Jacob Leal & Mauro Napoletano, 2016. "Market Stability vs. Market Resilience: Regulatory Policies Experiments in an Agent Based Model with Low- and High-Frequency Trading," LEM Papers Series 2016/15, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    2. Alfarano, Simone & Lux, Thomas & Wagner, Friedrich, 2006. "Estimation of a simple agent-based model of financial markets: An application to Australian stock and foreign exchange data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(1), pages 38-42.

  28. Alfarano, Simone & Milaković, Mishael & Raddant, Matthias, 2009. "Network hierarchy in Kirman's ant model: fund investment can create systemic risk," Economics Working Papers 2009-09, Christian-Albrechts-University of Kiel, Department of Economics.

    Cited by:

    1. Chen, Shu-heng & Chang, Chia-ling, 2012. "Interactions in the New Keynesian DSGE models: The Boltzmann-Gibbs machine and social networks approach," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-32.
    2. Irle, Albrecht & Kauschke, Jonas & Lux, Thomas & Milaković, Mishael, 2010. "Switching rates and the asymptotic behavior of herding models," Kiel Working Papers 1595, Kiel Institute for the World Economy (IfW Kiel).
    3. 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).

  29. Alfarano, Simone & Milaković, Mishael, 2008. "Does Classical Competition Explain the Statistical Features of Firm Growth?," Economics Working Papers 2008-03, Christian-Albrechts-University of Kiel, Department of Economics.

    Cited by:

    1. Erlingsson, Einar Jón & Alfarano, Simone & Raberto, Marco & Stefánsson, Hlynur, 2012. "On the distributional properties of size, pro fit and growth of Icelandic firms," MPRA Paper 35857, University Library of Munich, Germany.
    2. Williams, Michael A. & Pinto, Brijesh P. & Park, David, 2015. "Global evidence on the distribution of firm growth rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 102-107.
    3. Jangho Yang, 2018. "Information Theoretic Approaches In Economics," Journal of Economic Surveys, Wiley Blackwell, vol. 32(3), pages 940-960, July.
    4. Paulo L. dos Santos, 2017. "The Principle of Social Scaling," Complexity, Hindawi, vol. 2017, pages 1-9, December.
    5. Paulo L. dos Santos & Jangho Yang, 2018. "Arbitrage, Information, and the Competitive Organization of Distributions of Profitability," Working Papers 1803, New School for Social Research, Department of Economics.
    6. Oh, Ilfan, 2019. "Autonomy of profit rate distribution and its dynamics from firm size measures: A statistical equilibrium approach," BERG Working Paper Series 146, Bamberg University, Bamberg Economic Research Group.
    7. Eliazar, Iddo & Sokolov, Igor M., 2010. "Maximization of statistical heterogeneity: From Shannon’s entropy to Gini’s index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3023-3038.
    8. Eliazar, Iddo, 2017. "Inequality spectra," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 824-847.
    9. Eliazar, Iddo & Cohen, Morrel H., 2015. "A pentatonic classification of extreme events," Chaos, Solitons & Fractals, Elsevier, vol. 74(C), pages 3-14.
    10. Sylvain Barde, 2012. "Back to the future: economic rationality and maximum entropy prediction," Studies in Economics 1202, School of Economics, University of Kent.
    11. Scharfenaker, Ellis, 2020. "Implications of quantal response statistical equilibrium," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    12. Scharfenaker, Ellis & dos Santos, Paulo L., 2015. "The distribution and regulation of Tobin’s q," Economics Letters, Elsevier, vol. 137(C), pages 191-194.
    13. Cohen, Morrel H. & Eliazar, Iddo I., 2013. "Econophysical visualization of Adam Smith’s invisible hand," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 813-823.
    14. Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2020. "Exploiting ergodicity in forecasts of corporate profitability," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    15. Giulio Bottazzi & Angelo Secchi, 2011. "A new class of asymmetric exponential power densities with applications to economics and finance," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 20(4), pages 991-1030, August.
    16. Paulo dos Santos, 2016. "The Principle of Social Scaling," Working Papers 1606, New School for Social Research, Department of Economics.
    17. David Vidal-Tomás & Alba Ruiz-Buforn & Omar Blanco-Arroyo & Simone Alfarano, 2022. "A Cross-Sectional Analysis of Growth and Profit Rate Distribution: The Spanish Case," Mathematics, MDPI, vol. 10(6), pages 1-20, March.
    18. Halvarsson, Daniel, 2013. "Identifying High-Growth Firms," Ratio Working Papers 215, The Ratio Institute.
    19. Mundt, Philipp & Förster, Niels & Alfarano, Simone & Milaković, Mishael, 2014. "The real versus the financial economy: A global tale of stability versus volatility," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 8, pages 1-26.
    20. Paulo L. dos Santos & Jangho Yang, 2019. "The persistent and informative distribution of returns on capital," Economics and Business Letters, Oviedo University Press, vol. 8(3), pages 156-165.
    21. Gregor Semieniuk & Ellis Scharfenaker, 2014. "A Bayesian Latent Variable Mixture Model for Filtering Firm Profit Rate," SCEPA working paper series. 2014-1, Schwartz Center for Economic Policy Analysis (SCEPA), The New School.
    22. Eliazar, Iddo, 2014. "From entropy-maximization to equality-maximization: Gauss, Laplace, Pareto, and Subbotin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 479-492.
    23. Matthias Duschl & Thomas Brenner, 2013. "Characteristics of regional industry-specific employment growth rates' distributions," Papers in Regional Science, Wiley Blackwell, vol. 92(2), pages 249-270, June.
    24. Cosimo Abbate & Alessandro Sapio, 2016. "Gazelles and muppets in the City: Stock market listing, risk sharing, and firm growth quantiles," LEM Papers Series 2016/33, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    25. Jan Schulz & Daniel M. Mayerhoffer, 2021. "Equal chances, unequal outcomes? Network-based evolutionary learning and the industrial dynamics of superstar firms," Journal of Business Economics, Springer, vol. 91(9), pages 1357-1385, November.
    26. Sylvain Barde, 2015. "Back to the Future: Economic Self-Organisation and Maximum Entropy Prediction," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 337-358, February.
    27. Wagner, Friedrich & Milaković, Mishael & Alfarano, Simone, 2010. "Firm profitability and the network of organizational capabilities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4769-4775.
    28. Matthias Duschl & Thomas Brenner, 2011. "Characteristics of Regional Industry-specific Employment Growth – Empirical Evidence for Germany," Working Papers on Innovation and Space 2011-07, Philipps University Marburg, Department of Geography.
    29. Irle, Albrecht & Milaković, Mishael & Alfarano, Simone & Kauschke, Jonas, 2008. "A Statistical Equilibrium Model of Competitive Firms," Economics Working Papers 2008-10, Christian-Albrechts-University of Kiel, Department of Economics.
    30. Mundt, Philipp & Oh, Ilfan, 2019. "Asymmetric competition, risk, and return distribution," BERG Working Paper Series 145, Bamberg University, Bamberg Economic Research Group.
    31. Eliazar, Iddo I. & Cohen, Morrel H., 2013. "On the physical interpretation of statistical data from black-box systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(13), pages 2924-2939.
    32. Mundt, Philipp & Oh, Ilfan, 2019. "Asymmetric competition, risk, and return distribution," Economics Letters, Elsevier, vol. 179(C), pages 29-32.

  30. Milaković, Mishael & Alfarano, Simone & Lux, Thomas, 2008. "The small core of the German corporate board network," Kiel Working Papers 1446, Kiel Institute for the World Economy (IfW Kiel).

    Cited by:

    1. Matthias Raddant & Hiroshi Takahashi, 2022. "Corporate boards, interorganizational ties and profitability: the case of Japan," Empirical Economics, Springer, vol. 62(3), pages 1365-1406, March.
    2. Carlo Drago & Roberto Ricciuti & Paolo Santella, 2015. "An Attempt to Disperse the Italian Interlocking Directorship Network: Analyzing the Effects of the 2011 Reform," Working Papers 2015.82, Fondazione Eni Enrico Mattei.
    3. Giglio, Ricardo & Lux, Thomas, 2016. "The core of the global corporate network," FinMaP-Working Papers 59, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    4. Giulia Rotundo & Anna D’Arcangelis, 2014. "Network of companies: an analysis of market concentration in the Italian stock market," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(4), pages 1893-1910, July.
    5. Tetsuji Okazaki & Michiru Sawada, 2012. "Interbank networks in prewar Japan: structure and implications," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 21(2), pages 463-506, April.
    6. Ricardo Giglio & Thomas Lux, 2021. "The Core of the Global Corporate Network," Networks and Spatial Economics, Springer, vol. 21(3), pages 681-705, September.
    7. Sankowska, Anna & Siudak, Dariusz, 2016. "The small world phenomenon and assortative mixing in Polish corporate board and director networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 309-315.
    8. Raddant, Matthias & Takahashi, Hiroshi, 2019. "The Japanese corporate board network," Kiel Working Papers 2130, Kiel Institute for the World Economy (IfW Kiel).
    9. Kai Jäger, 2017. "Studies on Issues in Political Economy since the Global Financial Crisis," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 71.
    10. Matthias Raddant & Mishael Milaković & Laura Birg, 2017. "Persistence in corporate networks," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(2), pages 249-276, July.
    11. Drago, Carlo & Ricciuti, Roberto, 2017. "Communities detection as a tool to assess a reform of the Italian interlocking directorship network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 91-104.
    12. Leonardo Bargigli & Renato Giannetti, 2015. "The Italian Corporate System: SOEs, Private Firms and Institutions in a Network Perspective (1952-1983)," Working Papers - Economics wp2015_01.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    13. Kai Jäger, 2013. "Sources of Franco-German corporate support for the euro: The effects of business network centrality and political connections," European Union Politics, , vol. 14(1), pages 115-139, March.
    14. Lucia Bellenzier & Rosanna Grassi, 2014. "Interlocking directorates in Italy: persistent links in network dynamics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 9(2), pages 183-202, October.
    15. Aki-Hiro Sato, 2012. "Inference of Extreme Synchrony with an Entropy Measure on a Bipartite Network," Papers 1207.4860, arXiv.org, revised Oct 2013.
    16. Milaković, Mishael & Raddant, Matthias & Birg, Laura, 2009. "Persistence of a network core in the time evolution of interlocking directorates," Economics Working Papers 2009-10, Christian-Albrechts-University of Kiel, Department of Economics.
    17. Ettore Croci & Rosanna Grassi, 2014. "The economic effect of interlocking directorates in Italy: new evidence using centrality measures," Computational and Mathematical Organization Theory, Springer, vol. 20(1), pages 89-112, March.

  31. Milaković, Mishael & Alfarano, Simone & Lux, Thomas, 2008. "The small core of the German corporate board network," Kiel Working Papers 1446, Kiel Institute for the World Economy (IfW Kiel).

    Cited by:

    1. Matthias Raddant & Hiroshi Takahashi, 2022. "Corporate boards, interorganizational ties and profitability: the case of Japan," Empirical Economics, Springer, vol. 62(3), pages 1365-1406, March.
    2. Carlo Drago & Roberto Ricciuti & Paolo Santella, 2015. "An Attempt to Disperse the Italian Interlocking Directorship Network: Analyzing the Effects of the 2011 Reform," Working Papers 2015.82, Fondazione Eni Enrico Mattei.
    3. Giglio, Ricardo & Lux, Thomas, 2016. "The core of the global corporate network," FinMaP-Working Papers 59, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    4. Giulia Rotundo & Anna D’Arcangelis, 2014. "Network of companies: an analysis of market concentration in the Italian stock market," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(4), pages 1893-1910, July.
    5. Tetsuji Okazaki & Michiru Sawada, 2012. "Interbank networks in prewar Japan: structure and implications," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 21(2), pages 463-506, April.
    6. Ricardo Giglio & Thomas Lux, 2021. "The Core of the Global Corporate Network," Networks and Spatial Economics, Springer, vol. 21(3), pages 681-705, September.
    7. Sankowska, Anna & Siudak, Dariusz, 2016. "The small world phenomenon and assortative mixing in Polish corporate board and director networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 309-315.
    8. Raddant, Matthias & Takahashi, Hiroshi, 2019. "The Japanese corporate board network," Kiel Working Papers 2130, Kiel Institute for the World Economy (IfW Kiel).
    9. Kai Jäger, 2017. "Studies on Issues in Political Economy since the Global Financial Crisis," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 71.
    10. Matthias Raddant & Mishael Milaković & Laura Birg, 2017. "Persistence in corporate networks," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(2), pages 249-276, July.
    11. Drago, Carlo & Ricciuti, Roberto, 2017. "Communities detection as a tool to assess a reform of the Italian interlocking directorship network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 91-104.
    12. Leonardo Bargigli & Renato Giannetti, 2015. "The Italian Corporate System: SOEs, Private Firms and Institutions in a Network Perspective (1952-1983)," Working Papers - Economics wp2015_01.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    13. Kai Jäger, 2013. "Sources of Franco-German corporate support for the euro: The effects of business network centrality and political connections," European Union Politics, , vol. 14(1), pages 115-139, March.
    14. Lucia Bellenzier & Rosanna Grassi, 2014. "Interlocking directorates in Italy: persistent links in network dynamics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 9(2), pages 183-202, October.
    15. Aki-Hiro Sato, 2012. "Inference of Extreme Synchrony with an Entropy Measure on a Bipartite Network," Papers 1207.4860, arXiv.org, revised Oct 2013.
    16. Milaković, Mishael & Raddant, Matthias & Birg, Laura, 2009. "Persistence of a network core in the time evolution of interlocking directorates," Economics Working Papers 2009-10, Christian-Albrechts-University of Kiel, Department of Economics.
    17. Ettore Croci & Rosanna Grassi, 2014. "The economic effect of interlocking directorates in Italy: new evidence using centrality measures," Computational and Mathematical Organization Theory, Springer, vol. 20(1), pages 89-112, March.

  32. Irle, Albrecht & Milaković, Mishael & Alfarano, Simone & Kauschke, Jonas, 2008. "A Statistical Equilibrium Model of Competitive Firms," Economics Working Papers 2008-10, Christian-Albrechts-University of Kiel, Department of Economics.

    Cited by:

    1. Halvarsson, Daniel, 2019. "Asymmetric Double Pareto Distributions: Maximum Likelihood Estimation with Application to the Growth Rate Distribution of Firms," Ratio Working Papers 327, The Ratio Institute.
    2. Y. Malevergne & A. Saichev & D. Sornette, 2010. "Zipf's law and maximum sustainable growth," Papers 1012.0199, arXiv.org.
    3. Christian Kleiber, 2014. "The Generalized Lognormal Distribution and the Stieltjes Moment Problem," Journal of Theoretical Probability, Springer, vol. 27(4), pages 1167-1177, December.
    4. Erlingsson, Einar Jón & Alfarano, Simone & Raberto, Marco & Stefánsson, Hlynur, 2012. "On the distributional properties of size, pro fit and growth of Icelandic firms," MPRA Paper 35857, University Library of Munich, Germany.
    5. Theodosio, Bruno Miller & Weber, Jan, 2023. "Back to the classics: R-evolution towards statistical equilibria," ifso working paper series 28, University of Duisburg-Essen, Institute for Socioeconomics (ifso).
    6. Ellis Scharfenaker, 2020. "Statistical Equilibrium Methods in Analytical Political Economy," Working Paper Series, Department of Economics, University of Utah 2020_05, University of Utah, Department of Economics.
    7. Oriol Valles Codina, 2020. "Economic Production as Life: A Classical Approach to Computational Social Science," Working Papers 2001, New School for Social Research, Department of Economics.
    8. Jangho Yang, 2018. "Information Theoretic Approaches In Economics," Journal of Economic Surveys, Wiley Blackwell, vol. 32(3), pages 940-960, July.
    9. Flavio Calvino & Daniele Giachini & Mattia Guerini, 2020. "The age distribution of business firms," Working Papers halshs-03040286, HAL.
    10. Anwar Shaikh, 2019. "The Econ in Econophysics," Working Papers 1913, New School for Social Research, Department of Economics.
    11. Paulo L. dos Santos & Jangho Yang, 2018. "Arbitrage, Information, and the Competitive Organization of Distributions of Profitability," Working Papers 1803, New School for Social Research, Department of Economics.
    12. Livan, Giacomo & Alfarano, Simone & Milakovic, Mishael & Scalas, Enrico, 2014. "A spectral perspective on excess volatility," FinMaP-Working Papers 12, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    13. Lunardi, José T. & Miccichè, Salvatore & Lillo, Fabrizio & Mantegna, Rosario N. & Gallegati, Mauro, 2014. "Do firms share the same functional form of their growth rate distribution? A statistical test," Journal of Economic Dynamics and Control, Elsevier, vol. 39(C), pages 140-164.
    14. Oh, Ilfan, 2019. "Autonomy of profit rate distribution and its dynamics from firm size measures: A statistical equilibrium approach," BERG Working Paper Series 146, Bamberg University, Bamberg Economic Research Group.
    15. Philipp Mundt & Mishael Milakovic & Simone Alfarano, 2014. "Gibrat's law redux: Think profitability instead of growth," Working Papers 2014/02, Economics Department, Universitat Jaume I, Castellón (Spain).
    16. Scharfenaker, Ellis, 2020. "Implications of quantal response statistical equilibrium," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    17. Juan Melo, 2024. "Decentralized Finance and Local Public Goods: A Bayesian Maximum Entropy Model of School District Spending in the U.S," Papers 2404.17700, arXiv.org.
    18. Ellis Scharfenaker & Duncan Foley, 2017. "Maximum Entropy Estimation of Statistical Equilibrium in Economic Quantal Response Models," Working Papers 1710, New School for Social Research, Department of Economics, revised May 2017.
    19. Scharfenaker, Ellis & dos Santos, Paulo L., 2015. "The distribution and regulation of Tobin’s q," Economics Letters, Elsevier, vol. 137(C), pages 191-194.
    20. Eliazar, Iddo & Cohen, Morrel H., 2014. "On social inequality: Analyzing the rich–poor disparity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 148-158.
    21. Cohen, Morrel H. & Eliazar, Iddo I., 2013. "Econophysical visualization of Adam Smith’s invisible hand," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 813-823.
    22. Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2020. "Survival and the ergodicity of corporate profitability," BERG Working Paper Series 162, Bamberg University, Bamberg Economic Research Group.
    23. Zou, Yijiang, 2019. "An analysis of Chinese firm size distribution and growth rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    24. Anna Maria Fiori, 2020. "On firm size distribution: statistical models, mechanisms, and empirical evidence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(3), pages 447-482, September.
    25. Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2020. "Exploiting ergodicity in forecasts of corporate profitability," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    26. Toda, Alexis Akira, 2012. "The double power law in income distribution: Explanations and evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 84(1), pages 364-381.
    27. Leila Davis & Joao Paulo A. de Souza, 2022. "Churning and profitability in the U.S. corporate sector," Metroeconomica, Wiley Blackwell, vol. 73(3), pages 924-957, July.
    28. Ellis Scharfenaker & Gregor Semieniuk, 2015. "A Statistical Equilibrium Approach to the Distribution of Profit Rates," SCEPA working paper series. 2015-05, Schwartz Center for Economic Policy Analysis (SCEPA), The New School.
    29. David Vidal-Tomás & Alba Ruiz-Buforn & Omar Blanco-Arroyo & Simone Alfarano, 2022. "A Cross-Sectional Analysis of Growth and Profit Rate Distribution: The Spanish Case," Mathematics, MDPI, vol. 10(6), pages 1-20, March.
    30. Halvarsson, Daniel, 2013. "Identifying High-Growth Firms," Ratio Working Papers 215, The Ratio Institute.
    31. Metzig, Cornelia & Gordon, Mirta B., 2014. "A model for scaling in firms’ size and growth rate distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 398(C), pages 264-279.
    32. Ellis Scharfenaker, 2015. "A Quantal Response Model of Firm Competition," Working Papers 1507, New School for Social Research, Department of Economics.
    33. Mundt, Philipp & Förster, Niels & Alfarano, Simone & Milaković, Mishael, 2014. "The real versus the financial economy: A global tale of stability versus volatility," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 8, pages 1-26.
    34. Williams, Michael A. & Baek, Grace & Park, Leslie Y. & Zhao, Wei, 2016. "Global evidence on the distribution of economic profit rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 356-363.
    35. Paulo L. dos Santos & Jangho Yang, 2019. "The persistent and informative distribution of returns on capital," Economics and Business Letters, Oviedo University Press, vol. 8(3), pages 156-165.
    36. Ferrari, Giorgio, 2018. "On a Class of Singular Stochastic Control Problems for Reflected Diffusions," Center for Mathematical Economics Working Papers 592, Center for Mathematical Economics, Bielefeld University.
    37. Gregor Semieniuk & Ellis Scharfenaker, 2014. "A Bayesian Latent Variable Mixture Model for Filtering Firm Profit Rate," SCEPA working paper series. 2014-1, Schwartz Center for Economic Policy Analysis (SCEPA), The New School.
    38. Roberto Veneziani & Luca Zamparelli & Deepankar Basu, 2017. "Quantitative Empirical Research In Marxist Political Economy: A Selective Review," Journal of Economic Surveys, Wiley Blackwell, vol. 31(5), pages 1359-1386, December.
    39. Weber, Jan David & Scharfenaker, Ellis, 2024. "Measures of firm performance and concentration: Stylized facts and a dilemma of data reproduction," Economics Letters, Elsevier, vol. 234(C).
    40. Reiner Franke, 2015. "How Fat-Tailed is US Output Growth?," Metroeconomica, Wiley Blackwell, vol. 66(2), pages 213-242, May.
    41. Eliazar, Iddo, 2014. "From entropy-maximization to equality-maximization: Gauss, Laplace, Pareto, and Subbotin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 479-492.
    42. Arata, Yoshiyuki, 2019. "Firm growth and Laplace distribution: The importance of large jumps," Journal of Economic Dynamics and Control, Elsevier, vol. 103(C), pages 63-82.
    43. Marko Petrovic & Andrea Teglio & Simone Alfarano, 2016. "The role of bank credit allocation: Evidence from the Spanish economy," Working Papers 2016/17, Economics Department, Universitat Jaume I, Castellón (Spain).
    44. Mundt, Philipp & Oh, Ilfan, 2019. "Asymmetric competition, risk, and return distribution," BERG Working Paper Series 145, Bamberg University, Bamberg Economic Research Group.
    45. F. Wagner & M. Milaković & S. Alfarano, 2010. "What distinguishes individual stocks from the index?," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 73(1), pages 23-28, January.
    46. Eliazar, Iddo I. & Cohen, Morrel H., 2013. "On the physical interpretation of statistical data from black-box systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(13), pages 2924-2939.
    47. Jangho Yang, 2023. "Information‐theoretic model of induced technical change: Theory and empirics," Metroeconomica, Wiley Blackwell, vol. 74(1), pages 2-39, February.
    48. Mundt, Philipp & Oh, Ilfan, 2019. "Asymmetric competition, risk, and return distribution," Economics Letters, Elsevier, vol. 179(C), pages 29-32.
    49. Staley, Mark, 2018. "The Knowledge-Diffusion Bottleneck in Economic Growth and Development," MPRA Paper 87255, University Library of Munich, Germany.

  33. Alfarano, Simone & Milaković, Mishael, 2008. "Should Network Structure Matter in Agent-Based Finance?," Economics Working Papers 2008-04, Christian-Albrechts-University of Kiel, Department of Economics.

    Cited by:

    1. Matthew Oldham, 2019. "Understanding How Short-Termism and a Dynamic Investor Network Affects Investor Returns: An Agent-Based Perspective," Complexity, Hindawi, vol. 2019, pages 1-21, July.
    2. 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).
    3. H. Lamba, 2010. "A queueing theory description of fat-tailed price returns in imperfect financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 77(2), pages 297-304, September.
    4. Bowden, Mark P., 2012. "Information contagion within small worlds and changes in kurtosis and volatility in financial prices," Journal of Macroeconomics, Elsevier, vol. 34(2), pages 553-566.
    5. Iori, G. & Porter, J., 2012. "Agent-Based Modelling for Financial Markets," Working Papers 12/08, Department of Economics, City University London.
    6. Simon Cramer & Torsten Trimborn, 2019. "Stylized Facts and Agent-Based Modeling," Papers 1912.02684, arXiv.org.
    7. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Kiel Working Papers 1426, Kiel Institute for the World Economy (IfW Kiel).
    8. 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.

  34. Alfarano, Simone & Lux, Thomas & Wagner, Friedrich, 2005. "Time-variation of higher moments in a financial market with heterogeneous agents: An analytical approach," Economics Working Papers 2005-14, Christian-Albrechts-University of Kiel, Department of Economics.

    Cited by:

    1. A. E. Biondo & A. Pluchino & A. Rapisarda, 2015. "Modelling Financial Markets by Self-Organized Criticality," Papers 1507.04298, arXiv.org, revised Oct 2015.
    2. Lux, Thomas & Alfarano, Simone, 2016. "Financial power laws: Empirical evidence, models, and mechanisms," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 3-18.
    3. Luisanna Cocco & Michele Marchesi, 2016. "Modeling and Simulation of the Economics of Mining in the Bitcoin Market," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-31, October.
    4. Simone Landini & Mauro Gallegati, 2014. "Heterogeneity, interaction and emergence: effects of composition," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 4(3/4), pages 339-361.
    5. Carl Chiarella & Roberto Dieci & Xue-Zhong He, 2008. "Heterogeneity, Market Mechanisms, and Asset Price Dynamics," Research Paper Series 231, Quantitative Finance Research Centre, University of Technology, Sydney.
    6. Ali Naqvi & Miriam Rehm, 2014. "A multi-agent model of a low income economy: simulating the distributional effects of natural disasters," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 9(2), pages 275-309, October.
    7. Kyrtsou, Catherine, 2008. "Re-examining the sources of heteroskedasticity: The paradigm of noisy chaotic models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(27), pages 6785-6789.
    8. Maximilian Beikirch & Simon Cramer & Martin Frank & Philipp Otte & Emma Pabich & Torsten Trimborn, 2020. "Robust Mathematical Formulation And Probabilistic Description Of Agent-Based Computational Economic Market Models," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 23(06), pages 1-41, September.
    9. 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.
    10. Adri'an Carro & Ra'ul Toral & Maxi San Miguel, 2016. "The noisy voter model on complex networks," Papers 1602.06935, arXiv.org, revised Apr 2016.
    11. 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).
    12. Vidal-Tomás, David, 2022. "Which cryptocurrency data sources should scholars use?," International Review of Financial Analysis, Elsevier, vol. 81(C).
    13. Alfarano, Simone & Milakovic, Mishael & Raddant, Matthias, 2011. "A Note on institutional hierarchy and volatility in financial markets," MPRA Paper 30902, University Library of Munich, Germany.
    14. Luisanna Cocco & Giulio Concas & Michele Marchesi, 2017. "Using an artificial financial market for studying a cryptocurrency market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(2), pages 345-365, July.
    15. Xue-Zhong He & Huanhuan Zheng, 2016. "Trading Heterogeneity Under Information Uncertainty," Research Paper Series 373, Quantitative Finance Research Centre, University of Technology, Sydney.
    16. 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.
    17. Jan PALCZEWSKI & Klaus Reiner SCHENK-HOPPE, 2008. "From Discrete to Continuous Time Evolutionary Finance Models," Swiss Finance Institute Research Paper Series 08-30, Swiss Finance Institute.
    18. Di Guilmi, Corrado & He, Xue-Zhong & Li, Kai, 2014. "Herding, trend chasing and market volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 349-373.
    19. Catalano, Michele & Di Guilmi, Corrado, 2019. "Uncertainty, rationality and complexity in a multi-sectoral dynamic model: The dynamic stochastic generalized aggregation approach," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 117-144.
    20. Jovanovic, Franck & Schinckus, Christophe, 2016. "Breaking down the barriers between econophysics and financial economics," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 256-266.
    21. Kirill S. Glavatskiy & Mikhail Prokopenko & Adrian Carro & Paul Ormerod & Michael Harré, 2021. "Explaining herding and volatility in the cyclical price dynamics of urban housing markets using a large-scale agent-based model," SN Business & Economics, Springer, vol. 1(6), pages 1-21, June.
    22. Chen, Zhenxi & Zheng, Huanhuan, 2022. "Herding in the Chinese and US stock markets: Evidence from a micro-founded approach," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 597-604.
    23. Aleksejus Kononovicius & Vygintas Gontis & Valentas Daniunas, 2012. "Agent-based Versus Macroscopic Modeling of Competition and Business Processes in Economics and Finance," Papers 1202.3533, arXiv.org, revised Jun 2012.
    24. Yamamoto, Ryuichi, 2019. "Dynamic Predictor Selection And Order Splitting In A Limit Order Market," Macroeconomic Dynamics, Cambridge University Press, vol. 23(5), pages 1757-1792, July.
    25. David Vidal-Tomás & Simone Alfarano, 2020. "An agent-based early warning indicator for financial market instability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 49-87, January.
    26. Kononovicius, A. & Gontis, V., 2014. "Control of the socio-economic systems using herding interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 80-84.
    27. Irle, Albrecht & Kauschke, Jonas & Lux, Thomas & Milaković, Mishael, 2010. "Switching rates and the asymptotic behavior of herding models," Kiel Working Papers 1595, Kiel Institute for the World Economy (IfW Kiel).
    28. Malliaris, A.G. & Kyrtsou, C., 2009. "Editorial introduction of the special issue: "Energy sector pricing and macroeconomic dynamics"," Energy Economics, Elsevier, vol. 31(6), pages 825-826, November.
    29. Domenico Delli Gatti & Tommaso Ferraresi & Filippo Gusella & Lilit Popoyan & Giorgio Ricchiuti & Andrea Roventini, 2024. "The complex interplay between exchange rate and real markets: an agent-based model exploration," LEM Papers Series 2024/24, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    30. Lux, Thomas, 2006. "Financial power laws: Empirical evidence, models, and mechanism," Economics Working Papers 2006-12, Christian-Albrechts-University of Kiel, Department of Economics.
    31. Moran, José & Fosset, Antoine & Kirman, Alan & Benzaquen, Michael, 2021. "From ants to fishing vessels: a simple model for herding and exploitation of finite resources," Journal of Economic Dynamics and Control, Elsevier, vol. 129(C).
    32. Torsten Trimborn & Philipp Otte & Simon Cramer & Max Beikirch & Emma Pabich & Martin Frank, 2018. "SABCEMM-A Simulator for Agent-Based Computational Economic Market Models," Papers 1801.01811, arXiv.org, revised Oct 2018.
    33. Lux, Thomas, 2017. "Estimation of agent-based models using sequential Monte Carlo methods," Economics Working Papers 2017-07, Christian-Albrechts-University of Kiel, Department of Economics.
    34. Peralta, Antonio F. & Khalil, Nagi & Toral, Raúl, 2020. "Ordering dynamics in the voter model with aging," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 552(C).
    35. 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.
    36. Kononovicius, Aleksejus, 2021. "Supportive interactions in the noisy voter model," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    37. Aleksejus Kononovicius & Vygintas Gontis, 2012. "Three-state herding model of the financial markets," Papers 1210.1838, arXiv.org, revised Jan 2013.
    38. Zhenxi Chen & Thomas Lux, 2018. "Estimation of Sentiment Effects in Financial Markets: A Simulated Method of Moments Approach," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 711-744, October.
    39. Kaltwasser, Pablo Rovira, 2010. "Uncertainty about fundamentals and herding behavior in the FOREX market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(6), pages 1215-1222.
    40. Rytis Kazakevicius & Aleksejus Kononovicius & Bronislovas Kaulakys & Vygintas Gontis, 2021. "Understanding the nature of the long-range memory phenomenon in socioeconomic systems," Papers 2108.02506, arXiv.org, revised Aug 2021.
    41. Weihong Huang & Huanhuan Zheng & Wai-Mun Chia, 2013. "Asymmetric returns, gradual bubbles and sudden crashes," The European Journal of Finance, Taylor & Francis Journals, vol. 19(5), pages 420-437, May.
    42. Ghonghadze, Jaba & Lux, Thomas, 2015. "Bringing an elementary agent-based model to the data: Estimation via GMM and an application to forecasting of asset price volatility," FinMaP-Working Papers 38, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    43. 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.
    44. M. Cristelli & L. Pietronero & A. Zaccaria, 2011. "Critical Overview of Agent-Based Models for Economics," Papers 1101.1847, arXiv.org.
    45. Tang, Yinan & Chen, Ping, 2014. "Time varying moments, regime switch, and crisis warning: The birth–death process with changing transition probability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 404(C), pages 56-64.
    46. Tubbenhauer, Tobias & Fieberg, Christian & Poddig, Thorsten, 2021. "Multi-agent-based VaR forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
    47. Carl Chiarella & Corrado Di Guilmi, 2010. "The Financial Instability Hypothesis: A Stochastic Microfoundation Framework," Research Paper Series 273, Quantitative Finance Research Centre, University of Technology, Sydney.
    48. Giovanni Campisi & Silvia Muzzioli, 2020. "Investor sentiment and trading behavior," Department of Economics 0163, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    49. Alfarano, Simone & Lux, Thomas & Wagner, Friedrich, 2010. "Excess Volatility and Herding in an Artificial Financial Market: Analytical Approach and Estimation," MPRA Paper 24719, University Library of Munich, Germany.
    50. Gontis, V. & Havlin, S. & Kononovicius, A. & Podobnik, B. & Stanley, H.E., 2016. "Stochastic model of financial markets reproducing scaling and memory in volatility return intervals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1091-1102.
    51. Светлов К.В., 2019. "Стадное Поведение На Фондовом Рынке: Анализ И Прогнозирование," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 55(2), pages 81-97, апрель.
    52. 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.
    53. Lux, Thomas, 2009. "Mass psychology in action: identification of social interaction effects in the German stock market," Kiel Working Papers 1514, Kiel Institute for the World Economy (IfW Kiel).
    54. Roy Cerqueti & Giulia Rotundo, 2015. "A review of aggregation techniques for agent-based models: understanding the presence of long-term memory," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(4), pages 1693-1717, July.
    55. Nirei, Makoto & Stachurski, John & Watanabe, Tsutomu, 2020. "Trade clustering and power laws in financial markets," Theoretical Economics, Econometric Society, vol. 15(4), November.
    56. Kukacka, Jiri & Kristoufek, Ladislav, 2020. "Do ‘complex’ financial models really lead to complex dynamics? Agent-based models and multifractality," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    57. Alessio Emanuele Biondo & Alessandro Pluchino & Andrea Rapisarda, 2017. "Informative Contagion Dynamics in a Multilayer Network Model of Financial Markets," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 3(3), pages 343-366, November.
    58. H. Lamba, 2009. "A queueing theory description of fat-tailed price returns in imperfect financial markets," Papers 0908.0949, arXiv.org, revised Aug 2010.
    59. 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.
    60. Carl Chiarella & Corrado Di Guilmi, 2011. "Limit Distribution of Evolving Strategies in Financial Markets," Research Paper Series 294, Quantitative Finance Research Centre, University of Technology, Sydney.
    61. Aleksejus Kononovicius, 2017. "Empirical Analysis and Agent-Based Modeling of the Lithuanian Parliamentary Elections," Complexity, Hindawi, vol. 2017, pages 1-15, November.
    62. Muhammad Arslan & Ahmed Imran Hunjra & Wajid Shakeel Ahmed & Younes Ben Zaied, 2024. "Forecasting multi‐frequency intraday exchange rates using deep learning models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1338-1355, August.
    63. Tae-Seok Jang, 2015. "Identification of Social Interaction Effects in Financial Data," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 207-238, February.
    64. Alessio Emanuele Biondo & Alessandro Pluchino & Andrea Rapisarda, 2016. "Order Book, Financial Markets and Self-Organized Criticality," Papers 1602.08270, arXiv.org.
    65. Domenico Delli Gatti & Corrado Di Guilmi & Mauro Gallegati & Simone Landini, 2012. "Reconstructing Aggregate Dynamics in Heterogeneous Agents Models. A Markovian Approach," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 117-146.
    66. Bleher, Johannes & Dimpfl, Thomas, 2019. "Today I got a million, tomorrow, I don't know: On the predictability of cryptocurrencies by means of Google search volume," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 147-159.
    67. Maximilian Beikirch & Simon Cramer & Martin Frank & Philipp Otte & Emma Pabich & Torsten Trimborn, 2019. "Robust Mathematical Formulation and Probabilistic Description of Agent-Based Computational Economic Market Models," Papers 1904.04951, arXiv.org, revised Mar 2021.
    68. Domenico Delli Gatti & Tommaso Ferraresi & Filippo Gusella & Lilit Popoyan & Giorgio Ricchiuti & Andrea Roventini, 2024. "The interplay between real and exchange rate market: an agent-based model approach," Working Papers - Economics wp2024_10.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    69. Simon Cramer & Torsten Trimborn, 2019. "Stylized Facts and Agent-Based Modeling," Papers 1912.02684, arXiv.org.
    70. Daniele Giachini, 2018. "Rationality and Asset Prices under Belief Heterogeneity," LEM Papers Series 2018/07, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    71. 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.
    72. Lux, Thomas, 2018. "Estimation of agent-based models using sequential Monte Carlo methods," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 391-408.
    73. Makoto Nirei & Tsutomu Watanabe, 2014. "Beauty Contests and Fat Tails in Financial Markets," UTokyo Price Project Working Paper Series 024, University of Tokyo, Graduate School of Economics.
    74. Alfarano, Simone & Milakovic, Mishael, 2010. "Identification of Interaction Effects in Survey Expectations: A Cautionary Note," MPRA Paper 26002, University Library of Munich, Germany.
    75. Friedrich Wagner, 2011. "Market clearing by maximum entropy in agent models of stock markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 6(2), pages 121-138, November.
    76. Aleksejus Kononovicius & Vygintas Gontis, 2014. "Herding interactions as an opportunity to prevent extreme events in financial markets," Papers 1409.8024, arXiv.org, revised May 2015.
    77. Makoto Nirei & John Stachurski & Tsutomu Watanabe, 2018. "Trade Clustering and Power Laws in Financial Markets (Published in Theoretical Economics, 15:1365?1398, 2020)," CARF F-Series CARF-F-450, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    78. Hohnisch, Martin & Westerhoff, Frank, 2008. "Business cycle synchronization in a simple Keynesian macro-model with socially transmitted economic sentiment and international sentiment spill-over," Structural Change and Economic Dynamics, Elsevier, vol. 19(3), pages 249-259, September.
    79. 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.
    80. E. Mnif & A. Jarboui & M.K. Hassan & K. Mouakhar, 2020. "Big Data Tools for Islamic Financial Analysis," Post-Print hal-04457135, HAL.
    81. Mengling Li & Huanhuan Zheng, 2017. "Heterogeneous trading and complex price dynamics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(2), pages 437-442, July.
    82. Chen, Zhenxi, 2016. "Regimes dependent speculative trading: Evidence from the United States housing market," FinMaP-Working Papers 66, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    83. Vygintas Gontis & Shlomo Havlin & Aleksejus Kononovicius & Boris Podobnik & H. Eugene Stanley, 2015. "Stochastic model of financial markets reproducing scaling and memory in volatility return intervals," Papers 1507.05203, arXiv.org, revised Oct 2016.
    84. 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.
    85. Adri'an Carro & Ra'ul Toral & Maxi San Miguel, 2015. "Markets, herding and response to external information," Papers 1506.03708, arXiv.org, revised Jun 2015.
    86. 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.
    87. Adrián Carro & Raúl Toral & Maxi San Miguel, 2015. "Markets, Herding and Response to External Information," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-28, July.
    88. Di Guilmi, C. & Gallegati, M. & Landini, S. & Stiglitz, J.E., 2020. "An analytical solution for network models with heterogeneous and interacting agents," Journal of Economic Behavior & Organization, Elsevier, vol. 171(C), pages 189-220.
    89. Alfarano, Simone & Milaković, Mishael & Raddant, Matthias, 2009. "Network hierarchy in Kirman's ant model: fund investment can create systemic risk," Economics Working Papers 2009-09, Christian-Albrechts-University of Kiel, Department of Economics.
    90. Zhenxi Chen & Jing Ru, 2021. "Herding and capitalization size in the Chinese stock market: a micro-foundation evidence," Empirical Economics, Springer, vol. 60(4), pages 1895-1911, April.
    91. Mikhail Anufriev & Te Bao & Jan Tuinstra, 2015. "Microfoundations for Switching Behavior in Heterogeneous Agent Models: An Experiment," Working Paper Series 31, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    92. Lux, Thomas, 2012. "Estimation of an agent-based model of investor sentiment formation in financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1284-1302.
    93. Ghonghadze, Jaba & Lux, Thomas, 2016. "Bringing an elementary agent-based model to the data: Estimation via GMM and an application to forecasting of asset price volatility," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 1-19.
    94. Di Guilmi, Corrado & Carvalho, Laura, 2017. "The dynamics of leverage in a demand-driven model with heterogeneous firms," Journal of Economic Behavior & Organization, Elsevier, vol. 140(C), pages 70-90.
    95. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Kiel Working Papers 1426, Kiel Institute for the World Economy (IfW Kiel).
    96. Khalil, Nagi & Toral, Raúl, 2019. "The noisy voter model under the influence of contrarians," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 81-92.
    97. Aleksejus Kononovicius & Julius Ruseckas, 2018. "Order book model with herd behavior exhibiting long-range memory," Papers 1809.02772, arXiv.org, revised Apr 2019.
    98. 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.
    99. Torsten Trimborn & Philipp Otte & Simon Cramer & Maximilian Beikirch & Emma Pabich & Martin Frank, 2020. "SABCEMM: A Simulator for Agent-Based Computational Economic Market Models," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 707-744, February.
    100. Vygintas Gontis & Aleksejus Kononovicius & Stefan Reimann, 2012. "The class of nonlinear stochastic models as a background for the bursty behavior in financial markets," Papers 1201.3083, arXiv.org, revised May 2012.
    101. Jia-Ping Huang & Yang Zhang & Juanxi Wang, 2023. "Dynamic effects of social influence on asset prices," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(3), pages 671-699, July.
    102. Rytis Kazakeviv{c}ius & Aleksejus Kononovicius, 2023. "Anomalous diffusion and long-range memory in the scaled voter model," Papers 2301.08088, arXiv.org, revised Feb 2023.
    103. Tang, Yinan & Chen, Ping, 2015. "Transition probability, dynamic regimes, and the critical point of financial crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 11-20.
    104. Adri'an Carro & Ra'ul Toral & Maxi San Miguel, 2013. "Signal amplification in an agent-based herding model," Papers 1302.6477, arXiv.org, revised Sep 2015.
    105. 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.
    106. Simone Alfarano & Thomas Lux & Friedrich Wagner, 2005. "Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model," Computational Economics, Springer;Society for Computational Economics, vol. 26(1), pages 19-49, August.
    107. Alfarano, Simone & Milakovic, Mishael, 2009. "Network structure and N-dependence in agent-based herding models," Journal of Economic Dynamics and Control, Elsevier, vol. 33(1), pages 78-92, January.
    108. Aleksejus Kononovicius & Vygintas Gontis, 2013. "Control of the socio-economic systems using herding interactions," Papers 1309.6105, arXiv.org, revised Feb 2014.

  35. Alfarano, Simone & Lux, Thomas, 2005. "A noise trader model as a generator of apparent financial power laws and long memory," Economics Working Papers 2005-13, Christian-Albrechts-University of Kiel, Department of Economics.

    Cited by:

    1. Lux, Thomas & Alfarano, Simone, 2016. "Financial power laws: Empirical evidence, models, and mechanisms," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 3-18.
    2. Blaurock, Ivonne & Schmitt, Noemi & Westerhoff, Frank, 2017. "Market entry waves and volatility outbursts in stock markets," BERG Working Paper Series 128, Bamberg University, Bamberg Economic Research Group.
    3. Erol Akcay & David Hirshleifer, 2020. "Social Finance: Cultural Evolution, Transmission Bias and Market Dynamics," NBER Working Papers 27745, National Bureau of Economic Research, Inc.
    4. 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).
    5. O. Hermsen, 2010. "Does Basel II destabilize financial markets? An agent-based financial market perspective," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 73(1), pages 29-40, January.
    6. Lux, Thomas, 2009. "Rational forecasts or social opinion dynamics? Identification of interaction effects in a business climate survey," Journal of Economic Behavior & Organization, Elsevier, vol. 72(2), pages 638-655, November.
    7. Hermsen, Oliver & Witte, Björn-Christopher & Westerhoff, Frank, 2009. "Disclosure requirements, the release of new information and market efficiency: new insights from agent-based models," Economics Discussion Papers 2009-51, Kiel Institute for the World Economy (IfW Kiel).
    8. Lux, Thomas, 2008. "Rational forecasts or social opinion dynamics? Identification of interaction effects in a business climate survey," Kiel Working Papers 1424, Kiel Institute for the World Economy (IfW Kiel).
    9. Alfarano, Simone & Milakovic, Mishael & Raddant, Matthias, 2011. "A Note on institutional hierarchy and volatility in financial markets," MPRA Paper 30902, University Library of Munich, Germany.
    10. Webel, Karsten, 2012. "Chaos in German stock returns — New evidence from the 0–1 test," Economics Letters, Elsevier, vol. 115(3), pages 487-489.
    11. Hamid, Alain & Heiden, Moritz, 2015. "Forecasting volatility with empirical similarity and Google Trends," Journal of Economic Behavior & Organization, Elsevier, vol. 117(C), pages 62-81.
    12. Thomas Lux, 2009. "Rational Forecasts or Social Opinion Dynamics? Identification of Interaction Effects in a Business Climate Survey," Post-Print hal-00720175, HAL.
    13. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2020. "The memory of stock return volatility: Asset pricing implications," Journal of Financial Markets, Elsevier, vol. 47(C).
    14. Susanne M. Schennach, 2018. "Long Memory via Networking," Econometrica, Econometric Society, vol. 86(6), pages 2221-2248, November.
    15. Dimpfl, Thomas & Jank, Stephan, 2011. "Can Internet search queries help to predict stock market volatility?," University of Tübingen Working Papers in Business and Economics 18, University of Tuebingen, Faculty of Economics and Social Sciences, School of Business and Economics.
    16. Irle, Albrecht & Kauschke, Jonas & Lux, Thomas & Milaković, Mishael, 2010. "Switching rates and the asymptotic behavior of herding models," Kiel Working Papers 1595, Kiel Institute for the World Economy (IfW Kiel).
    17. 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.
    18. Biondo, Alessio Emanuele & Mazzarino, Laura & Pluchino, Alessandro, 2024. "Trading strategies and Financial Performances: A simulation approach," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    19. Boubaker Heni & Canarella Giorgio & Gupta Rangan & Miller Stephen M., 2017. "Time-varying persistence of inflation: evidence from a wavelet-based approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(4), pages 1-18, September.
    20. Alfarano, Simone & Lux, Thomas & Wagner, Friedrich, 2005. "Time-variation of higher moments in a financial market with heterogeneous agents: An analytical approach," Economics Working Papers 2005-14, Christian-Albrechts-University of Kiel, Department of Economics.
    21. Li, Wen & Yu, Cindy & Carriquiry, Alicia & Kliemann, Wolfgang, 2011. "The asymptotic behavior of the R/S statistic for fractional Brownian motion," Statistics & Probability Letters, Elsevier, vol. 81(1), pages 83-91, January.
    22. Zhenxi Chen & Thomas Lux, 2018. "Estimation of Sentiment Effects in Financial Markets: A Simulated Method of Moments Approach," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 711-744, October.
    23. Jia Li & Peter C. B. Phillips & Shuping Shi & Jun Yu, 2022. "Weak Identification of Long Memory with Implications for Inference," Cowles Foundation Discussion Papers 2334, Cowles Foundation for Research in Economics, Yale University.
    24. Sato, Aki-Hiro, 2012. "Patterns of regional travel behavior: An analysis of Japanese hotel reservation data," International Review of Financial Analysis, Elsevier, vol. 23(C), pages 55-65.
    25. Ghonghadze, Jaba & Lux, Thomas, 2015. "Bringing an elementary agent-based model to the data: Estimation via GMM and an application to forecasting of asset price volatility," FinMaP-Working Papers 38, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    26. Gabriele La Spada & Fabrizio Lillo, 2011. "The effect of round-off error on long memory processes," Papers 1107.4476, arXiv.org, revised Mar 2013.
    27. Sattarhoff, Cristina & Gronwald, Marc, 2022. "Measuring informational efficiency of the European carbon market — A quantitative evaluation of higher order dependence," International Review of Financial Analysis, Elsevier, vol. 84(C).
    28. Lux, Thomas & Kaizoji, Taisei, 2007. "Forecasting volatility and volume in the Tokyo Stock Market: Long memory, fractality and regime switching," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1808-1843, June.
    29. Hernández, Juan Antonio & Benito, Rosa Marı´a & Losada, Juan Carlos, 2012. "An adaptive stochastic model for financial markets," Chaos, Solitons & Fractals, Elsevier, vol. 45(6), pages 899-908.
    30. V. Alfi & M. Cristelli & L. Pietronero & A. Zaccaria, 2008. "Mechanisms of Self-Organization and Finite Size Effects in a Minimal Agent Based Model," Papers 0811.4256, arXiv.org.
    31. Ghonghadze, Jaba & Lux, Thomas, 2009. "Modeling the dynamics of EU economic sentiment indicators: an interaction-based approach," Kiel Working Papers 1487, Kiel Institute for the World Economy (IfW Kiel).
    32. Hollstein, Fabian & Prokopczuk, Marcel & Wese Simen, Chardin, 2020. "Beta uncertainty," Journal of Banking & Finance, Elsevier, vol. 116(C).
    33. Thomas Lux & Jaba Ghonghadze, 2011. "Modeling the Dynamics of EU Economic Sentiment Indicators: An Interaction-Based Approach," Post-Print hal-00711445, HAL.
    34. 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.
    35. Roberto Veneziani & Luca Zamparelli & Reiner Franke & Frank Westerhoff, 2017. "Taking Stock: A Rigorous Modelling Of Animal Spirits In Macroeconomics," Journal of Economic Surveys, Wiley Blackwell, vol. 31(5), pages 1152-1182, December.
    36. Georges, Christophre, 2008. "Staggered updating in an artificial financial market," Journal of Economic Dynamics and Control, Elsevier, vol. 32(9), pages 2809-2825, September.
    37. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
    38. Tae-Seok Jang, 2015. "Identification of Social Interaction Effects in Financial Data," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 207-238, February.
    39. 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.
    40. Marwil J. Dávila-Fernández & Serena Sordi & Alessia Cafferata, 2024. "How do you feel about going green? Modelling environmental sentiments in a growing open economy," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 19(4), pages 649-687, October.
    41. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.
    42. Ghonghadze, Jaba & Lux, Thomas, 2016. "Bringing an elementary agent-based model to the data: Estimation via GMM and an application to forecasting of asset price volatility," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 1-19.
    43. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Kiel Working Papers 1426, Kiel Institute for the World Economy (IfW Kiel).
    44. Makoto Nirei & Theodoros Stamatiou & Vladyslav Sushko, 2012. "Stochastic Herding in Financial Markets Evidence from Institutional Investor Equity Portfolios," BIS Working Papers 371, Bank for International Settlements.
    45. 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.

  36. Alfarano, Simone & Lux, Thomas, 2003. "A minimal noise trader model with realistic time series properties," Economics Working Papers 2003-15, Christian-Albrechts-University of Kiel, Department of Economics.

    Cited by:

    1. Gilles Dufrenot & Dominique Guegan & Anne Peguin-Feissolle, 2008. "Changing-regime volatility: A fractionally integrated SETAR model," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00185369, HAL.
    2. Lux, Thomas, 2006. "Financial power laws: Empirical evidence, models, and mechanism," Economics Working Papers 2006-12, Christian-Albrechts-University of Kiel, Department of Economics.
    3. Moran, José & Fosset, Antoine & Kirman, Alan & Benzaquen, Michael, 2021. "From ants to fishing vessels: a simple model for herding and exploitation of finite resources," Journal of Economic Dynamics and Control, Elsevier, vol. 129(C).
    4. Heni Boubaker & Nadia Sghaier, 2014. "Wavelet based Estimation of Time- Varying Long Memory Model with Nonlinear Fractional Integration Parameter," Working Papers 2014-284, Department of Research, Ipag Business School.
    5. Vishwesha Guttal & Srinivas Raghavendra & Nikunj Goel & Quentin Hoarau, 2016. "Lack of Critical Slowing Down Suggests that Financial Meltdowns Are Not Critical Transitions, yet Rising Variability Could Signal Systemic Risk," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-20, January.
    6. Christopher M Wray & Steven R Bishop, 2016. "A Financial Market Model Incorporating Herd Behaviour," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-28, March.
    7. David Morton de Lachapelle & Damien Challet, 2009. "Turnover, account value and diversification of real traders: evidence of collective portfolio optimizing behavior," Papers 0912.4723, arXiv.org, revised Jun 2010.
    8. 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.
    9. Simone Alfarano & Thomas Lux & Friedrich Wagner, 2005. "Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model," Computational Economics, Springer;Society for Computational Economics, vol. 26(1), pages 19-49, August.

  37. Simone Alfarano & Thomas Lux, 2002. "A minimal noise trader model with realistic time series," Computing in Economics and Finance 2002 317, Society for Computational Economics.

    Cited by:

    1. Gilles Dufrenot & Dominique Guegan & Anne Peguin-Feissolle, 2008. "Changing-regime volatility: A fractionally integrated SETAR model," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00185369, HAL.
    2. Heni Boubaker & Nadia Sghaier, 2014. "Wavelet based Estimation of Time- Varying Long Memory Model with Nonlinear Fractional Integration Parameter," Working Papers 2014-284, Department of Research, Ipag Business School.
    3. Alfarano, Simone & Lux, Thomas & Wagner, Friedrich, 2010. "Excess Volatility and Herding in an Artificial Financial Market: Analytical Approach and Estimation," MPRA Paper 24719, University Library of Munich, Germany.
    4. David Morton de Lachapelle & Damien Challet, 2009. "Turnover, account value and diversification of real traders: evidence of collective portfolio optimizing behavior," Papers 0912.4723, arXiv.org, revised Jun 2010.
    5. 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.
    6. Simone Alfarano & Thomas Lux & Friedrich Wagner, 2005. "Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model," Computational Economics, Springer;Society for Computational Economics, vol. 26(1), pages 19-49, August.

Articles

  1. Philipp Mundt & Simone Alfarano & Mishael Milaković, 2022. "Survival and the Ergodicity of Corporate Profitability," Management Science, INFORMS, vol. 68(5), pages 3726-3734, May.
    See citations under working paper version above.
  2. 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.
    See citations under working paper version above.
  3. Ruiz-Buforn, Alba & Camacho-Cuena, Eva & Morone, Andrea & Alfarano, Simone, 2021. "Overweighting of public information in financial markets: A lesson from the lab," Journal of Banking & Finance, Elsevier, vol. 133(C).
    See citations under working paper version above.
  4. Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2020. "Exploiting ergodicity in forecasts of corporate profitability," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    See citations under working paper version above.
  5. David Vidal-Tomás & Simone Alfarano, 2020. "An agent-based early warning indicator for financial market instability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 49-87, January.
    See citations under working paper version above.
  6. Annarita Colasante & Simone Alfarano & Eva Camacho-Cuena & Mauro Gallegati, 2020. "Long-run expectations in a learning-to-forecast experiment: a simulation approach," Journal of Evolutionary Economics, Springer, vol. 30(1), pages 75-116, January.
    See citations under working paper version above.
  7. Annarita Colasante & Simone Alfarano & Eva Camacho-Cuena, 2020. "Heuristic Switching Model and Exploration-Exploitation Algorithm to Describe Long-Run Expectations in LtFEs: a Comparison," Computational Economics, Springer;Society for Computational Economics, vol. 56(3), pages 623-658, October.
    See citations under working paper version above.
  8. Simone Alfarano & Eva Camacho & Gabriele Tedeschi, 2019. "Alternative approaches for the reformulation of economics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(1), pages 1-6, March.

    Cited by:

    1. Gabriele Tedeschi & Fabio Caccioli & Maria Cristina Recchioni, 2020. "Taming financial systemic risk: models, instruments and early warning indicators," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 1-7, January.
    2. Reena Marwah & Sanika Sulochani Ramanayake, 2021. "Pandemic-Led Disruptions in Asia: Tracing the Early Economic Impacts on Sri Lanka and Thailand," South Asian Survey, , vol. 28(1), pages 172-198, March.
    3. David Vidal-Tomás & Rocco Caferra & Gabriele Tedeschi, 2022. "The day after tomorrow: financial repercussions of COVID-19 on systemic risk," Review of Evolutionary Political Economy, Springer, vol. 3(1), pages 169-192, April.

  9. Annarita Colasante & Simone Alfarano & Eva Camacho-Cuena, 2019. "The term structure of cross-sectional dispersion of expectations in a Learning-to-Forecast Experiment," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(3), pages 491-520, September.
    See citations under working paper version above.
  10. Annarita Colasante & Simone Alfarano & Eva Camacho & Mauro Gallegati, 2018. "Long-run expectations in a learning-to-forecast experiment," Applied Economics Letters, Taylor & Francis Journals, vol. 25(10), pages 681-687, June.
    See citations under working paper version above.
  11. Blanco-Arroyo, Omar & Ruiz-Buforn, Alba & Vidal-Tomás, David & Alfarano, Simone, 2018. "On the determination of the granular size of the economy," Economics Letters, Elsevier, vol. 173(C), pages 35-38.
    See citations under working paper version above.
  12. Lux, Thomas & Alfarano, Simone, 2016. "Financial power laws: Empirical evidence, models, and mechanisms," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 3-18.

    Cited by:

    1. Blaurock, Ivonne & Schmitt, Noemi & Westerhoff, Frank, 2017. "Market entry waves and volatility outbursts in stock markets," BERG Working Paper Series 128, Bamberg University, Bamberg Economic Research Group.
    2. Erol Akcay & David Hirshleifer, 2020. "Social Finance: Cultural Evolution, Transmission Bias and Market Dynamics," NBER Working Papers 27745, National Bureau of Economic Research, Inc.
    3. Sabiou Inoua & Vernon Smith, 2023. "A Classical Model of Speculative Asset Price Dynamics," Papers 2307.00410, arXiv.org.
    4. Changtai Li & Weihong Huang & Wei-Siang Wang & Wai-Mun Chia, 2023. "Price Change and Trading Volume: Behavioral Heterogeneity in Stock Market," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 677-713, February.
    5. Roberto Dieci & Xue-Zhong He, 2018. "Heterogeneous Agent Models in Finance," Research Paper Series 389, Quantitative Finance Research Centre, University of Technology, Sydney.
    6. Grobys, Klaus, 2024. "On co-dependent power-law behavior across cryptocurrencies," Finance Research Letters, Elsevier, vol. 63(C).
    7. Eliazar, Iddo, 2018. "Universal Poisson-process limits for general random walks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1160-1174.
    8. Xiao, Di & Wang, Jun, 2021. "Attitude interaction for financial price behaviours by contact system with small-world network topology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    9. David Vidal-Tomás & Simone Alfarano, 2020. "An agent-based early warning indicator for financial market instability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 49-87, January.
    10. Gallegati, Mauro & Kirman, Alan, 2019. "20 years of WEHIA: A journey in search of a safer road," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 5-14.
    11. Lahmiri, Salim & Bekiros, Stelios, 2017. "Disturbances and complexity in volatility time series," Chaos, Solitons & Fractals, Elsevier, vol. 105(C), pages 38-42.
    12. Biondo, Alessio Emanuele & Mazzarino, Laura & Pluchino, Alessandro, 2024. "Trading strategies and Financial Performances: A simulation approach," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    13. Wu, Xu & Zhang, Linlin & Li, Jia & Yan, Ruzhen, 2021. "Fractal statistical measure and portfolio model optimization under power-law distribution," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    14. Sabiou M. Inoua & Vernon L. Smith, 2022. "Perishable goods versus re-tradable assets: A theoretical reappraisal of a fundamental dichotomy," Chapters, in: Sascha Füllbrunn & Ernan Haruvy (ed.), Handbook of Experimental Finance, chapter 15, pages 162-171, Edward Elgar Publishing.
    15. Grobys, Klaus, 2023. "A multifractal model of asset (in)variances," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    16. Tilfani, Oussama & Kristoufek, Ladislav & Ferreira, Paulo & El Boukfaoui, My Youssef, 2022. "Heterogeneity in economic relationships: Scale dependence through the multivariate fractal regression," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    17. Tiziana Assenza & Jakob Grazzini & Domenico Massaro, 2019. "Introduction to the special issue," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(3), pages 431-436, September.
    18. Klaus Grobys, 2024. "Science or scientism? On the momentum illusion," Annals of Finance, Springer, vol. 20(4), pages 479-519, December.
    19. Di Xiao & Jun Wang & Hongli Niu, 2016. "Volatility Analysis of Financial Agent-Based Market Dynamics from Stochastic Contact System," Computational Economics, Springer;Society for Computational Economics, vol. 48(4), pages 607-625, December.
    20. Georges, Christophre & Pereira, Javier, 2021. "Market stability with machine learning agents," Journal of Economic Dynamics and Control, Elsevier, vol. 122(C).
    21. Giovanni Campisi & Silvia Muzzioli, 2020. "Fundamentalists heterogeneity and the role of the sentiment indicator," Department of Economics 0167, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    22. Giovanni Campisi & Silvia Muzzioli, 2020. "Investor sentiment and trading behavior," Department of Economics 0163, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    23. Blanco-Arroyo, Omar & Ruiz-Buforn, Alba & Vidal-Tomás, David & Alfarano, Simone, 2019. "Empresas granulares y desagregación regional: un análisis del caso español [Granular firms and regional disaggregation: an analysis of the Spanish case]," MPRA Paper 93913, University Library of Munich, Germany.
    24. Duarte Queirós, Sílvio M. & Anteneodo, Celia, 2016. "Complexity in quantitative finance and economics," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 1-2.
    25. Grobys, Klaus, 2023. "Correlation versus co-fractality: Evidence from foreign-exchange-rate variances," International Review of Financial Analysis, Elsevier, vol. 86(C).
    26. Sabiou Inoua, 2023. "News-driven Expectations and Volatility Clustering," Papers 2309.04876, arXiv.org.
    27. Nirei, Makoto & Stachurski, John & Watanabe, Tsutomu, 2020. "Trade clustering and power laws in financial markets," Theoretical Economics, Econometric Society, vol. 15(4), November.
    28. Sabiou M. Inoua, 2020. "News-Driven Expectations and Volatility Clustering," JRFM, MDPI, vol. 13(1), pages 1-14, January.
    29. Zheng, Min & Liu, Ruipeng & Li, Youwei, 2018. "Long memory in financial markets: A heterogeneous agent model perspective," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 38-51.
    30. Minh Tran & Thanh Duong & Duc Pham-Hi & Marc Bui, 2020. "Detecting the Proportion of Traders in the Stock Market: An Agent-Based Approach," Mathematics, MDPI, vol. 8(2), pages 1-14, February.
    31. Zhao, Zhijun & Zhang, Xiaoqi, 2022. "A continuous heterogeneous-agent model for the co-evolution of asset price and wealth distribution in financial market," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    32. Jia, Linlu & Ke, Jinchuan & Wang, Jun, 2019. "Volatility aggregation intensity energy futures series on stochastic finite-range exclusion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 370-383.
    33. Oldham, Matthew, 2020. "Quantifying the concerns of Dimon and Buffett with data and computation," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    34. Wang, Yiduan & Zheng, Shenzhou & Zhang, Wei & Wang, Guochao & Wang, Jun, 2018. "Fuzzy entropy complexity and multifractal behavior of statistical physics financial dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 486-498.
    35. Niu, Hongli & Wang, Jun & Lu, Yunfan, 2016. "Fluctuation behaviors of financial return volatility duration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 30-40.
    36. Fernández-Martínez, M. & Sánchez-Granero, M.A. & Casado Belmonte, M.P. & Trinidad Segovia, J.E., 2020. "A note on power-law cross-correlated processes," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    37. Grobys, Klaus & Dufitinema, Josephine & Sapkota, Niranjan & Kolari, James W., 2022. "What’s the expected loss when Bitcoin is under cyberattack? A fractal process analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    38. Grobys, Klaus, 2023. "A Fractal and Comparative View of the Memory of Bitcoin and S&P 500 Returns," Research in International Business and Finance, Elsevier, vol. 66(C).
    39. Ruiz-Buforn, Alba & Alfarano, Simone & Camacho-Cuena, Eva & Morone, Andrea, 2018. "Crowding out effect and traders' overreliance on public information in financial markets: a lesson from the lab," MPRA Paper 88866, University Library of Munich, Germany.
    40. Makoto Nirei & John Stachurski & Tsutomu Watanabe, 2018. "Trade Clustering and Power Laws in Financial Markets (Published in Theoretical Economics, 15:1365?1398, 2020)," CARF F-Series CARF-F-450, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    41. B. Zhang & J. Wang & W. Zhang & G. C. Wang, 2020. "Nonlinear Scaling Behavior of Visible Volatility Duration for Financial Statistical Physics Dynamics," Computational Economics, Springer;Society for Computational Economics, vol. 56(2), pages 373-389, August.
    42. Wang, Yiduan & Zheng, Shenzhou & Zhang, Wei & Wang, Jun & Wang, Guochao, 2018. "Modeling and complexity of stochastic interacting Lévy type financial price dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 498-511.
    43. Zhang, Bo & Wang, Guochao & Wang, Yiduan & Zhang, Wei & Wang, Jun, 2019. "Multiscale statistical behaviors for Ising financial dynamics with continuum percolation jump," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1012-1025.
    44. Grobys, Klaus, 2021. "What do we know about the second moment of financial markets?," International Review of Financial Analysis, Elsevier, vol. 78(C).
    45. Safari, Muhammad Aslam Mohd & Masseran, Nurulkamal & Ibrahim, Kamarulzaman & AL-Dhurafi, Nasr Ahmed, 2020. "The power-law distribution for the income of poor households," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    46. Westerhoff Frank H., 2008. "The Use of Agent-Based Financial Market Models to Test the Effectiveness of Regulatory Policies," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(2-3), pages 195-227, April.
    47. Guochao Wang & Shenzhou Zheng & Jun Wang, 2019. "Statistical and nonlinear analyses of return volatility dynamics on energy futures," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 30(11), pages 1-26, November.
    48. Wang, Guochao & Zheng, Shenzhou & Wang, Jun, 2019. "Complex and composite entropy fluctuation behaviors of statistical physics interacting financial model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 97-113.
    49. Grobys, Klaus & Junttila, Juha & Kolari, James W. & Sapkota, Niranjan, 2021. "On the stability of stablecoins," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 207-223.
    50. Wang, Guochao & Zheng, Shenzhou & Wang, Jun, 2020. "Fluctuation and volatility dynamics of stochastic interacting energy futures price model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    51. Alexander Smirnov, 2016. "A Simple Model of Credit Expansion," Papers 1609.05055, arXiv.org.
    52. Cao, Guangxi & Jiang, Min & He, LingYun, 2018. "Comparative analysis of grey detrended fluctuation analysis methods based on empirical research on China’s interest rate market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 156-169.

  13. Philipp Mundt & Simone Alfarano & Mishael Milakovic, 2016. "Gibrat’s Law Redux: think profitability instead of growth," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 25(4), pages 549-571.
    See citations under working paper version above.
  14. Giacomo Livan & Simone Alfarano & Mishael Milaković & Enrico Scalas, 2015. "A spectral perspective on excess volatility," Applied Economics Letters, Taylor & Francis Journals, vol. 22(9), pages 745-750, June.
    See citations under working paper version above.
  15. Mundt, Philipp & Förster, Niels & Alfarano, Simone & Milaković, Mishael, 2014. "The real versus the financial economy: A global tale of stability versus volatility," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 8, pages 1-26.
    See citations under working paper version above.
  16. S. Alfarano & M. Milakovic & M. Raddant, 2013. "A note on institutional hierarchy and volatility in financial markets," The European Journal of Finance, Taylor & Francis Journals, vol. 19(6), pages 449-465, July.
    See citations under working paper version above.
  17. Einar Erlingsson & Simone Alfarano & Marco Raberto & Hlynur Stefánsson, 2013. "On the distributional properties of size, profit and growth of Icelandic firms," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 57-74, April.
    See citations under working paper version above.
  18. Alfarano, Simone & Milaković, Mishael & Irle, Albrecht & Kauschke, Jonas, 2012. "A statistical equilibrium model of competitive firms," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 136-149.
    See citations under working paper version above.
  19. Alfarano Simone & Milakovic Mishael, 2012. "Identification of Interaction Effects in Survey Expectations: A Cautionary Note," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(4), pages 1-23, October.
    See citations under working paper version above.
  20. F. Wagner & M. Milaković & S. Alfarano, 2010. "What distinguishes individual stocks from the index?," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 73(1), pages 23-28, January.

    Cited by:

    1. Raddant, Matthias & Wagner, Friedrich, 2016. "Multivariate GARCH for a large number of stocks," Kiel Working Papers 2049, Kiel Institute for the World Economy (IfW Kiel).
    2. M. Raddant & F. Wagner, 2022. "Multivariate GARCH with dynamic beta," The European Journal of Finance, Taylor & Francis Journals, vol. 28(13-15), pages 1324-1343, October.
    3. Friedrich Wagner, 2011. "Market clearing by maximum entropy in agent models of stock markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 6(2), pages 121-138, November.

  21. Wagner, Friedrich & Milaković, Mishael & Alfarano, Simone, 2010. "Firm profitability and the network of organizational capabilities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4769-4775.

    Cited by:

    1. Erlingsson, Einar Jón & Alfarano, Simone & Raberto, Marco & Stefánsson, Hlynur, 2012. "On the distributional properties of size, pro fit and growth of Icelandic firms," MPRA Paper 35857, University Library of Munich, Germany.
    2. Williams, Michael A. & Baek, Grace & Park, Leslie Y. & Zhao, Wei, 2016. "Global evidence on the distribution of economic profit rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 356-363.
    3. Irle, Albrecht & Milaković, Mishael & Alfarano, Simone & Kauschke, Jonas, 2008. "A Statistical Equilibrium Model of Competitive Firms," Economics Working Papers 2008-10, Christian-Albrechts-University of Kiel, Department of Economics.

  22. Mishael Milaković & Simone Alfarano & Thomas Lux, 2010. "The small core of the German corporate board network," Computational and Mathematical Organization Theory, Springer, vol. 16(2), pages 201-215, June.
    See citations under working paper version above.
  23. Alfarano, Simone & Milakovic, Mishael, 2009. "Network structure and N-dependence in agent-based herding models," Journal of Economic Dynamics and Control, Elsevier, vol. 33(1), pages 78-92, January.

    Cited by:

    1. Lux, Thomas & Alfarano, Simone, 2016. "Financial power laws: Empirical evidence, models, and mechanisms," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 3-18.
    2. Panchenko, Valentyn & Gerasymchuk, Sergiy & Pavlov, Oleg V., 2013. "Asset price dynamics with heterogeneous beliefs and local network interactions," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2623-2642.
    3. Adri'an Carro & Ra'ul Toral & Maxi San Miguel, 2016. "The noisy voter model on complex networks," Papers 1602.06935, arXiv.org, revised Apr 2016.
    4. 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.
    5. Schütz, Gunter M. & de Almeida Prado, Fernando Pigeard & Harris, Rosemary J. & Belitsky, Vladimir, 2009. "Short-time behaviour of demand and price viewed through an exactly solvable model for heterogeneous interacting market agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(19), pages 4126-4144.
    6. Gunter M. Schutz & Fernando Pigeard de Almeida Prado & Rosemary J. Harris & Vladimir Belitsky, 2007. "Short-time behaviour of demand and price viewed through an exactly solvable model for heterogeneous interacting market agents," Papers 0801.0003, arXiv.org, revised Jun 2009.
    7. Jørgen Vitting Andersen & Ioannis Vrontos & Petros Dellaportas & Serge Galam, 2014. "Communication impacting financial markets," Post-Print hal-01215750, HAL.
    8. Mishael Milaković & Simone Alfarano & Thomas Lux, 2010. "The small core of the German corporate board network," Computational and Mathematical Organization Theory, Springer, vol. 16(2), pages 201-215, June.
    9. 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).
    10. Alfarano, Simone & Milakovic, Mishael & Raddant, Matthias, 2011. "A Note on institutional hierarchy and volatility in financial markets," MPRA Paper 30902, University Library of Munich, Germany.
    11. Wang, Chengjin & Gao, Yudong & Li, Honggang, 2021. "Information interaction, behavioral synchronization and asset market volatility," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    12. David Vidal-Tomás & Simone Alfarano, 2020. "An agent-based early warning indicator for financial market instability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 49-87, January.
    13. Chen, Shu-heng & Chang, Chia-ling, 2012. "Interactions in the New Keynesian DSGE models: The Boltzmann-Gibbs machine and social networks approach," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-32.
    14. Kononovicius, A. & Gontis, V., 2014. "Control of the socio-economic systems using herding interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 80-84.
    15. Irle, Albrecht & Kauschke, Jonas & Lux, Thomas & Milaković, Mishael, 2010. "Switching rates and the asymptotic behavior of herding models," Kiel Working Papers 1595, Kiel Institute for the World Economy (IfW Kiel).
    16. Huang, Weihong & Zheng, Huanhuan & Chia, Wai-Mun, 2010. "Financial crises and interacting heterogeneous agents," Journal of Economic Dynamics and Control, Elsevier, vol. 34(6), pages 1105-1122, June.
    17. Peralta, Antonio F. & Khalil, Nagi & Toral, Raúl, 2020. "Ordering dynamics in the voter model with aging," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 552(C).
    18. 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.
    19. Kononovicius, Aleksejus, 2021. "Supportive interactions in the noisy voter model," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    20. Rytis Kazakevicius & Aleksejus Kononovicius & Bronislovas Kaulakys & Vygintas Gontis, 2021. "Understanding the nature of the long-range memory phenomenon in socioeconomic systems," Papers 2108.02506, arXiv.org, revised Aug 2021.
    21. Chang Sheng-Kai, 2014. "Herd behavior, bubbles and social interactions in financial markets," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(1), pages 89-101, February.
    22. Zakaria Babutsidze & Robin Cowan, 2014. "Showing or telling? Local interaction and organization of behavior," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 9(2), pages 151-181, October.
    23. 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.
    24. Steinbacher, Mitja & Raddant, Matthias & Karimi, Fariba & Camacho-Cuena, Eva & Alfarano, Simone & Iori, Giulia & Lux, Thomas, 2021. "Advances in the Agent-Based Modeling of Economic and Social Behavior," MPRA Paper 107317, University Library of Munich, Germany.
    25. Zakaria Babutsidze, 2012. "Comments on the paper "Of Ants and Voters: Maximum entropy prediction of agent-based models with recruitment" by S. Barde," SciencePo Working papers Main halshs-01926892, HAL.
    26. Aleksejus Kononovicius & Vygintas Gontis, 2019. "Approximation of the first passage time distribution for the birth-death processes," Papers 1902.00924, arXiv.org.
    27. 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.
    28. Aguilar-Janita, Miguel & Blanco-Alonso, Andres & Khalil, Nagi, 2024. "Polarization-induced stress in the noisy voter model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 647(C).
    29. Kai Jäger, 2017. "Studies on Issues in Political Economy since the Global Financial Crisis," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 71.
    30. Matthias Raddant & Mishael Milaković & Laura Birg, 2017. "Persistence in corporate networks," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(2), pages 249-276, July.
    31. H. Lamba, 2009. "A queueing theory description of fat-tailed price returns in imperfect financial markets," Papers 0908.0949, arXiv.org, revised Aug 2010.
    32. Aleksejus Kononovicius, 2017. "Empirical Analysis and Agent-Based Modeling of the Lithuanian Parliamentary Elections," Complexity, Hindawi, vol. 2017, pages 1-15, November.
    33. Bowden, Mark P., 2012. "Information contagion within small worlds and changes in kurtosis and volatility in financial prices," Journal of Macroeconomics, Elsevier, vol. 34(2), pages 553-566.
    34. Domenico Delli Gatti & Corrado Di Guilmi & Mauro Gallegati & Simone Landini, 2012. "Reconstructing Aggregate Dynamics in Heterogeneous Agents Models. A Markovian Approach," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 117-146.
    35. Simon Cramer & Torsten Trimborn, 2019. "Stylized Facts and Agent-Based Modeling," Papers 1912.02684, arXiv.org.
    36. Vygintas Gontis & Aleksejus Kononovicius, 2019. "Bessel-like birth-death process," Papers 1904.13064, arXiv.org, revised Oct 2019.
    37. Abhijit Sengupta & Danica Vukadinović Greetham, 2010. "Dynamics of brand competition: Effects of unobserved social networks," Post-Print hal-00743832, HAL.
    38. Mikhail Anufriev & Davide Radi & Fabio Tramontana, 2018. "Some reflections on past and future of nonlinear dynamics in economics and finance," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 41(2), pages 91-118, November.
    39. Alfarano, Simone & Milakovic, Mishael, 2010. "Identification of Interaction Effects in Survey Expectations: A Cautionary Note," MPRA Paper 26002, University Library of Munich, Germany.
    40. Asjad Naqvi & Franziska Gaupp & Stefan Hochrainer-Stigler, 2020. "The risk and consequences of multiple breadbasket failures: an integrated copula and multilayer agent-based modeling approach," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(3), pages 727-754, September.
    41. Aleksejus Kononovicius & Vygintas Gontis, 2014. "Herding interactions as an opportunity to prevent extreme events in financial markets," Papers 1409.8024, arXiv.org, revised May 2015.
    42. Kai Jäger, 2013. "Sources of Franco-German corporate support for the euro: The effects of business network centrality and political connections," European Union Politics, , vol. 14(1), pages 115-139, March.
    43. E. Mnif & A. Jarboui & M.K. Hassan & K. Mouakhar, 2020. "Big Data Tools for Islamic Financial Analysis," Post-Print hal-04457135, HAL.
    44. 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).
    45. Vygintas Gontis & Aleksejus Kononovicius, 2017. "Spurious memory in non-equilibrium stochastic models of imitative behavior," Papers 1707.09801, arXiv.org.
    46. Adri'an Carro & Ra'ul Toral & Maxi San Miguel, 2015. "Markets, herding and response to external information," Papers 1506.03708, arXiv.org, revised Jun 2015.
    47. Adrián Carro & Raúl Toral & Maxi San Miguel, 2015. "Markets, Herding and Response to External Information," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-28, July.
    48. Gontis, V. & Kononovicius, A., 2020. "Bessel-like birth–death process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    49. Alfarano, Simone & Milaković, Mishael & Raddant, Matthias, 2009. "Network hierarchy in Kirman's ant model: fund investment can create systemic risk," Economics Working Papers 2009-09, Christian-Albrechts-University of Kiel, Department of Economics.
    50. 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.
    51. Huang, Chuangxia & Cai, Yaqian & Yang, Xiaoguang & Deng, Yanchen & Yang, Xin, 2023. "Laplacian-energy-like measure: Does it improve the Cross-Sectional Absolute Deviation herding model?," Economic Modelling, Elsevier, vol. 127(C).
    52. Aleksejus Kononovicius & Julius Ruseckas, 2018. "Order book model with herd behavior exhibiting long-range memory," Papers 1809.02772, arXiv.org, revised Apr 2019.
    53. Xiong, Hang & Payne, Diane & Kinsella, Stephen, 2016. "Peer effects in the diffusion of innovations: Theory and simulation," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 63(C), pages 1-13.
    54. Sylvain Barde, 2012. "Of ants and voters: maximum entropy prediction and agent based models with recruitment," SciencePo Working papers Main hal-01071853, HAL.
    55. Jia-Ping Huang & Yang Zhang & Juanxi Wang, 2023. "Dynamic effects of social influence on asset prices," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(3), pages 671-699, July.
    56. Adri'an Carro & Ra'ul Toral & Maxi San Miguel, 2013. "Signal amplification in an agent-based herding model," Papers 1302.6477, arXiv.org, revised Sep 2015.
    57. Milaković, Mishael & Raddant, Matthias & Birg, Laura, 2009. "Persistence of a network core in the time evolution of interlocking directorates," Economics Working Papers 2009-10, Christian-Albrechts-University of Kiel, Department of Economics.
    58. Aleksejus Kononovicius & Vygintas Gontis, 2013. "Control of the socio-economic systems using herding interactions," Papers 1309.6105, arXiv.org, revised Feb 2014.

  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.
    See citations under working paper version above.
  25. Alfarano, Simone & Milakovic, Mishael, 2008. "Does classical competition explain the statistical features of firm growth?," Economics Letters, Elsevier, vol. 101(3), pages 272-274, December.
    See citations under working paper version above.
  26. S. Alfarano & T. Lux & F. Wagner, 2007. "Empirical validation of stochastic models of interacting agents," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 55(2), pages 183-187, January.

    Cited by:

    1. Pasquale Cirillo & Mauro Gallegati, 2012. "The Empirical Validation of an Agent-based Model," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 38(4), pages 525-547.
    2. 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.
    3. Recchioni, Maria Cristina & Tedeschi, Gabriele & Gallegati, Mauro, 2015. "A calibration procedure for analyzing stock price dynamics in an agent-based framework," Journal of Economic Dynamics and Control, Elsevier, vol. 60(C), pages 1-25.
    4. Francesco Lamperti, 2015. "An Information Theoretic Criterion for Empirical Validation of Time Series Models," LEM Papers Series 2015/02, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    5. Argentiero, Amedeo & Bovi, Maurizio & Cerqueti, Roy, 2016. "Bayesian estimation and entropy for economic dynamic stochastic models: An exploration of overconsumption," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 143-157.
    6. Alexandru Stan, 2015. "A Price Crash Alerting Strategy for Agent-based Artificial Financial Markets," MIC 2015: Managing Sustainable Growth; Proceedings of the Joint International Conference, Portorož, Slovenia, 28–30 May 2015,, University of Primorska, Faculty of Management Koper.
    7. Jakob Grazzini & Matteo Richiardi & Mike Tsionas, 2015. "Bayesian Estimation of Agent-Based Models," Economics Papers 2015-W12, Economics Group, Nuffield College, University of Oxford.
    8. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.
    9. Colasante, Annarita, 2017. "Selection of the distributional rule as an alternative tool to foster cooperation in a Public Good Game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 482-492.
    10. Mattia Guerini & Alessio Moneta, 2016. "A Method for Agent-Based Models Validation," Working Papers Series 42, Institute for New Economic Thinking.
    11. J. Doyne Farmer & John Geanakoplos, 2008. "The virtues and vices of equilibrium and the future of financial economics," Papers 0803.2996, arXiv.org.
    12. Tae-Seok Jang, 2015. "Identification of Social Interaction Effects in Financial Data," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 207-238, February.
    13. Donovan Platt, 2019. "A Comparison of Economic Agent-Based Model Calibration Methods," Papers 1902.05938, arXiv.org.
    14. Platt, Donovan, 2020. "A comparison of economic agent-based model calibration methods," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    15. Colasante, Annarita, 2016. "Evolution of Cooperation in Public Good Game," MPRA Paper 72577, University Library of Munich, Germany.
    16. 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.
    17. Lamperti, Francesco, 2018. "An information theoretic criterion for empirical validation of simulation models," Econometrics and Statistics, Elsevier, vol. 5(C), pages 83-106.
    18. Donovan Platt & Tim Gebbie, 2016. "The Problem of Calibrating an Agent-Based Model of High-Frequency Trading," Papers 1606.01495, arXiv.org, revised Mar 2017.

  27. 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.
    See citations under working paper version above.
  28. Alfarano, Simone & Lux, Thomas & Wagner, Friedrich, 2006. "Estimation of a simple agent-based model of financial markets: An application to Australian stock and foreign exchange data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(1), pages 38-42.

    Cited by:

    1. Gabriele Tedeschi & Fabio Caccioli & Maria Cristina Recchioni, 2020. "Taming financial systemic risk: models, instruments and early warning indicators," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 1-7, January.
    2. Francesco Lamperti & Andrea Roventini & Amir Sani, 2017. "Agent-Based Model Calibration using Machine Learning Surrogates," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01499344, HAL.
    3. Grazzini, Jakob & Richiardi, Matteo, 2013. "Consistent Estimation of Agent-Based Models by Simulated Minimum Distance," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201335, University of Turin.
    4. 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.
    5. Klein, Achim & Urbig, Diemo, 2008. "Who Drives the Market? Estimating a Heterogeneous Agent-based Financial Market Model Using a Neural Network Approach," MPRA Paper 116175, University Library of Munich, Germany, revised 30 Apr 2011.
    6. Recchioni, Maria Cristina & Tedeschi, Gabriele & Gallegati, Mauro, 2015. "A calibration procedure for analyzing stock price dynamics in an agent-based framework," Journal of Economic Dynamics and Control, Elsevier, vol. 60(C), pages 1-25.
    7. Saskia ter Ellen & Willem F. C. Verschoor, 2018. "Heterogeneous Beliefs and Asset Price Dynamics: A Survey of Recent Evidence," Dynamic Modeling and Econometrics in Economics and Finance, in: Fredj Jawadi (ed.), Uncertainty, Expectations and Asset Price Dynamics, pages 53-79, Springer.
    8. 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.
    9. Damien Challet, 2016. "Regrets, learning and wisdom," Post-Print hal-01312973, HAL.
    10. Francesco Lamperti, 2015. "An Information Theoretic Criterion for Empirical Validation of Time Series Models," LEM Papers Series 2015/02, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    11. Jacob Grazzini & Matteo Richiardi & Lisa Sella, 2012. "Indirect estimation of agent-based models.An application to a simple diffusion model," LABORatorio R. Revelli Working Papers Series 118, LABORatorio R. Revelli, Centre for Employment Studies.
    12. Aki-Hiro Sato & Takaki Hayashi & Janusz Hołyst, 2012. "Comprehensive analysis of market conditions in the foreign exchange market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 7(2), pages 167-179, October.
    13. 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.
    14. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2019. "Validation of Agent-Based Models in Economics and Finance," SciencePo Working papers Main halshs-02375423, HAL.
    15. Grazzini, Jakob & Richiardi, Matteo, 2015. "Estimation of ergodic agent-based models by simulated minimum distance," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 148-165.
    16. Francesco Lamperti, 2016. "Empirical Validation of Simulated Models through the GSL-div: an Illustrative Application," LEM Papers Series 2016/18, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    17. Francesco Lamperti, 2018. "Empirical validation of simulated models through the GSL-div: an illustrative application," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(1), pages 143-171, April.
    18. Jakob Grazzini & Matteo Richiardi & Mike Tsionas, 2015. "Bayesian Estimation of Agent-Based Models," Economics Papers 2015-W12, Economics Group, Nuffield College, University of Oxford.
    19. 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.
    20. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.
    21. Mattia Guerini & Alessio Moneta, 2016. "A Method for Agent-Based Models Validation," Working Papers Series 42, Institute for New Economic Thinking.
    22. Donovan Platt, 2019. "A Comparison of Economic Agent-Based Model Calibration Methods," Papers 1902.05938, arXiv.org.
    23. Platt, Donovan, 2020. "A comparison of economic agent-based model calibration methods," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    24. 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.
    25. Aki-Hiro Sato & Takaki Hayashi & Janusz A. Ho{l}yst, 2012. "Comprehensive Analysis of Market Conditions in the Foreign Exchange Market: Fluctuation Scaling and Variance-Covariance Matrix," Papers 1204.0426, arXiv.org.
    26. Lamperti, Francesco, 2018. "An information theoretic criterion for empirical validation of simulation models," Econometrics and Statistics, Elsevier, vol. 5(C), pages 83-106.
    27. Sato, Aki-Hiro & Nishimura, Maiko & Hołyst, Janusz A., 2010. "Fluctuation scaling of quotation activities in the foreign exchange market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(14), pages 2793-2804.
    28. Donovan Platt & Tim Gebbie, 2016. "The Problem of Calibrating an Agent-Based Model of High-Frequency Trading," Papers 1606.01495, arXiv.org, revised Mar 2017.
    29. Lee, Kangil & Han, Taek-Whan, 2016. "How vulnerable is the emissions market to transaction costs?: An ABMS Approach," Energy Policy, Elsevier, vol. 90(C), pages 273-286.

  29. Simone Alfarano & Iván Barreda-Tarrazona & Eva Camacho-Cuena, 2006. "On the role of heterogeneous and imperfect information in a laboratory financial market," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 14(4), pages 417-433, December.

    Cited by:

    1. Merl, Robert & Stöckl, Thomas & Palan, Stefan, 2023. "Insider trading regulation and shorting constraints. Evaluating the joint effects of two market interventions," Journal of Banking & Finance, Elsevier, vol. 154(C).
    2. Nuzzo, Simone & Morone, Andrea, 2017. "Asset markets in the lab: A literature review," Journal of Behavioral and Experimental Finance, Elsevier, vol. 13(C), pages 42-50.
    3. Andrea Morone & Giovanni Ferri, 2008. "The Effect of Rating Agencies on Herd Behaviour," SERIES 0022, Dipartimento di Economia e Finanza - Università degli Studi di Bari "Aldo Moro", revised Nov 2008.
    4. Adriana Gabriela Breaban & Juan Carlos Matallín-Sáez & Iván Barreda-Tarrazona & Mª Rosario Balaguer-Franch, 2012. "The demand for structured products: an experimental approach," Working Papers 2012/15, Economics Department, Universitat Jaume I, Castellón (Spain).
    5. Simone Alfarano & Andrea Morone & Eva Camacho, 2011. "The role of public and private information in a laboratory financial market," Working Papers. Serie AD 2011-06, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    6. Andrea Morone & Simone Nuzzo, 2016. "Market Efficiency, Trading Institutions and Information Mirages: Evidence from an Experimental Asset Market," EERI Research Paper Series EERI RP 2016/17, Economics and Econometrics Research Institute (EERI), Brussels.
    7. Eldad Yechiam & Amitay Kauffmann & Nathaniel J S Ashby & Gal Zahavi, 2017. "On the relation between economic bubbles and effort gaps between sellers and buyers: An experimental study," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-15, December.
    8. Aleksandra Rutkowska & Agata Kliber, 2021. "Say anything you want about me if you spell my name right: the effect of Internet searches on financial market," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(2), pages 633-664, June.
    9. Iván Barreda-Tarrazona & Juan Matallín-Sáez & Mª Balaguer-Franch, 2011. "Measuring Investors’ Socially Responsible Preferences in Mutual Funds," Journal of Business Ethics, Springer, vol. 103(2), pages 305-330, October.
    10. Philipp Hornung & Ulrike Leopold-Wildburger & Roland Mestel & Stefan Palan, 2015. "Insider behavior under different market structures: experimental evidence on trading patterns, manipulation, and profitability," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 23(2), pages 357-373, June.
    11. Barreda Tarrazona, Iván J. & Grimalda, Gianluca & Morone, Andrea & Nuzzo, Simone & Teglio, Andrea, 2017. "Centralizing information improves market efficiency more than increasing information: Results from experimental asset markets," Kiel Working Papers 2072, Kiel Institute for the World Economy (IfW Kiel).
    12. Adriana Breaban & Juan Carlos Matallín-Sáez & Iván Barreda-Tarrazona & Mª Rosario Balaguer-Franch, 2014. "Special Section: Experiments on Learning, Methods, and Voting," Pacific Economic Review, Wiley Blackwell, vol. 19(3), pages 332-354, August.
    13. Owen Powell & Natalia Shestakova, 2017. "Experimental asset markets: behavior and bubbles," Chapters, in: Morris Altman (ed.), Handbook of Behavioural Economics and Smart Decision-Making, chapter 21, pages 375-391, Edward Elgar Publishing.
    14. Merl, Robert, 2022. "Literature review of experimental asset markets with insiders," Journal of Behavioral and Experimental Finance, Elsevier, vol. 33(C).

  30. Simone Alfarano & Thomas Lux & Friedrich Wagner, 2005. "Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model," Computational Economics, Springer;Society for Computational Economics, vol. 26(1), pages 19-49, August.

    Cited by:

    1. S. Alfarano & T. Lux & F. Wagner, 2007. "Empirical validation of stochastic models of interacting agents," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 55(2), pages 183-187, January.
    2. Gabriele Tedeschi & Fabio Caccioli & Maria Cristina Recchioni, 2020. "Taming financial systemic risk: models, instruments and early warning indicators," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 1-7, January.
    3. Lux, Thomas & Alfarano, Simone, 2016. "Financial power laws: Empirical evidence, models, and mechanisms," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 3-18.
    4. Sylvain Barde & Ofce Observatoire Français Des Conjonctures Économiques, 2016. "Direct comparison of agent-based models of herding in financial markets," Post-Print hal-03604749, HAL.
    5. Blaurock, Ivonne & Schmitt, Noemi & Westerhoff, Frank, 2017. "Market entry waves and volatility outbursts in stock markets," BERG Working Paper Series 128, Bamberg University, Bamberg Economic Research Group.
    6. de Grauwe, Paul & Ji, Yuemei, 2018. "Behavioural economics is useful also in macroeconomics : the role of animal spirits," LSE Research Online Documents on Economics 87286, London School of Economics and Political Science, LSE Library.
    7. Sander van der Hoog, 2017. "Deep Learning in (and of) Agent-Based Models: A Prospectus," Papers 1706.06302, arXiv.org.
    8. Francesco Lamperti & Andrea Roventini & Amir Sani, 2017. "Agent-Based Model Calibration using Machine Learning Surrogates," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01499344, HAL.
    9. Thorsten Lehnert & Bart Frijns & Remco Zwinkels, 2009. "Behavioral Heterogeneity in the Option Market," LSF Research Working Paper Series 09-07, Luxembourg School of Finance, University of Luxembourg.
    10. Matthijs Lof, 2015. "Rational Speculators, Contrarians, and Excess Volatility," Management Science, INFORMS, vol. 61(8), pages 1889-1901, August.
    11. Carl Chiarella & Roberto Dieci & Xue-Zhong He, 2008. "Heterogeneity, Market Mechanisms, and Asset Price Dynamics," Research Paper Series 231, Quantitative Finance Research Centre, University of Technology, Sydney.
    12. O. Hermsen, 2010. "Does Basel II destabilize financial markets? An agent-based financial market perspective," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 73(1), pages 29-40, January.
    13. Witte, Björn-Christopher, 2011. "Removing systematic patterns in returns in a financial market model by artificially intelligent traders," BERG Working Paper Series 82, Bamberg University, Bamberg Economic Research Group.
    14. Eminente, Clara & Artime, Oriol & De Domenico, Manlio, 2022. "Interplay between exogenous triggers and endogenous behavioral changes in contagion processes on social networks," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    15. Carl Chiarella & Roberto Dieci & Xue-Zhong He, 2011. "The dynamic behaviour of asset prices in disequilibrium: a survey," International Journal of Behavioural Accounting and Finance, Inderscience Enterprises Ltd, vol. 2(2), pages 101-139.
    16. Roberto Dieci & Xue-Zhong He, 2018. "Heterogeneous Agent Models in Finance," Research Paper Series 389, Quantitative Finance Research Centre, University of Technology, Sydney.
    17. Hommes, Cars & Kiseleva, Tatiana & Kuznetsov, Yuri & Verbic, Miroslav, 2012. "Is More Memory In Evolutionary Selection (De)Stabilizing?," Macroeconomic Dynamics, Cambridge University Press, vol. 16(3), pages 335-357, June.
    18. 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).
    19. Nan Lu, 2018. "La modélisation de l’indice CAC 40 avec un modèle basé agent," Erudite Ph.D Dissertations, Erudite, number ph18-02 edited by François Legendre.
    20. Alfarano, Simone & Milakovic, Mishael & Raddant, Matthias, 2011. "A Note on institutional hierarchy and volatility in financial markets," MPRA Paper 30902, University Library of Munich, Germany.
    21. Siyan Chen & Saul Desiderio, 2022. "Calibration of Agent-Based Models by Means of Meta-Modeling and Nonparametric Regression," Computational Economics, Springer;Society for Computational Economics, vol. 60(4), pages 1457-1478, December.
    22. Grazzini, Jakob & Richiardi, Matteo, 2013. "Consistent Estimation of Agent-Based Models by Simulated Minimum Distance," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201335, University of Turin.
    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. 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.
    25. Tiziana Assenza & William A. Brock & Cars H. Hommes, 2017. "Animal Spirits, Heterogeneous Expectations, And The Amplification And Duration Of Crises," Economic Inquiry, Western Economic Association International, vol. 55(1), pages 542-564, January.
    26. Singh, Bharati, 2021. "A Bibliometric Analysis of Behavioral Finance and Behavioral Accounting," American Business Review, Pompea College of Business, University of New Haven, vol. 24(2), pages 198-230, November.
    27. Klein, Achim & Urbig, Diemo, 2008. "Who Drives the Market? Estimating a Heterogeneous Agent-based Financial Market Model Using a Neural Network Approach," MPRA Paper 116175, University Library of Munich, Germany, revised 30 Apr 2011.
    28. Giorgio Fagiolo & Andrea Roventini, 2017. "Macroeconomic Policy in DSGE and Agent-Based Models Redux: New Developments and Challenges Ahead," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 20(1), pages 1-1.
    29. 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.
    30. Di Guilmi, Corrado & He, Xue-Zhong & Li, Kai, 2014. "Herding, trend chasing and market volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 349-373.
    31. Recchioni, Maria Cristina & Tedeschi, Gabriele & Gallegati, Mauro, 2015. "A calibration procedure for analyzing stock price dynamics in an agent-based framework," Journal of Economic Dynamics and Control, Elsevier, vol. 60(C), pages 1-25.
    32. Liu, Yi-Fang & Zhang, Wei & Xu, Chao & Vitting Andersen, Jørgen & Xu, Hai-Chuan, 2014. "Impact of information cost and switching of trading strategies in an artificial stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 204-215.
    33. Kirill S. Glavatskiy & Mikhail Prokopenko & Adrian Carro & Paul Ormerod & Michael Harré, 2021. "Explaining herding and volatility in the cyclical price dynamics of urban housing markets using a large-scale agent-based model," SN Business & Economics, Springer, vol. 1(6), pages 1-21, June.
    34. Annalisa Fabretti, 2013. "On the problem of calibrating an agent based model for financial markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(2), pages 277-293, October.
    35. Po-Keng Cheng & Young Shin Kim, 2017. "Speculative bubbles and crashes： Fundamentalists and positive‐feedback trading," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1381370-138, January.
    36. Leonardo Bargigli & Luca Riccetti & Alberto Russo & Mauro Gallegati, 2016. "Network Calibration and Metamodeling of a Financial Accelerator Agent Based Model," Working Papers - Economics wp2016_01.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    37. Aleksejus Kononovicius & Vygintas Gontis & Valentas Daniunas, 2012. "Agent-based Versus Macroscopic Modeling of Competition and Business Processes in Economics and Finance," Papers 1202.3533, arXiv.org, revised Jun 2012.
    38. Yi-Fang Liu & Wei Zhang & Chao Xu & Jørgen Vitting Andersen & Hai-Chuan Xu, 2014. "Impact of information cost and switching of trading strategies in an artificial stock market," Post-Print halshs-00983051, HAL.
    39. David Vidal-Tomás & Simone Alfarano, 2020. "An agent-based early warning indicator for financial market instability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 49-87, January.
    40. Kononovicius, A. & Gontis, V., 2014. "Control of the socio-economic systems using herding interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 80-84.
    41. Irle, Albrecht & Kauschke, Jonas & Lux, Thomas & Milaković, Mishael, 2010. "Switching rates and the asymptotic behavior of herding models," Kiel Working Papers 1595, Kiel Institute for the World Economy (IfW Kiel).
    42. Carl Chiarella & Roberto Dieci & Xue-Zhong He, 2010. "Time-Varying Beta: A Boundedly Rational Equilibrium Approach," Research Paper Series 275, Quantitative Finance Research Centre, University of Technology, Sydney.
    43. Vygintas Gontis & Aleksejus Kononovicius, 2013. "Fluctuation analysis of the three agent groups herding model," Papers 1305.5958, arXiv.org.
    44. Domenico Delli Gatti & Tommaso Ferraresi & Filippo Gusella & Lilit Popoyan & Giorgio Ricchiuti & Andrea Roventini, 2024. "The complex interplay between exchange rate and real markets: an agent-based model exploration," LEM Papers Series 2024/24, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    45. Carl Chiarella & Roberto Dieci & Xue-Zhong He, 2011. "Do heterogeneous beliefs diversify market risk?," The European Journal of Finance, Taylor & Francis Journals, vol. 17(3), pages 241-258.
    46. Gallegati, Mauro & Kirman, Alan, 2019. "20 years of WEHIA: A journey in search of a safer road," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 5-14.
    47. Boswijk, H.P. & Hommes C.H. & Manzan, S., 2005. "Behavioral Heterogeneity in Stock Prices," CeNDEF Working Papers 05-12, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    48. Moran, José & Fosset, Antoine & Kirman, Alan & Benzaquen, Michael, 2021. "From ants to fishing vessels: a simple model for herding and exploitation of finite resources," Journal of Economic Dynamics and Control, Elsevier, vol. 129(C).
    49. Tomasz Makarewicz, 2017. "Contrarian Behavior, Information Networks and Heterogeneous Expectations in an Asset Pricing Model," Computational Economics, Springer;Society for Computational Economics, vol. 50(2), pages 231-279, August.
    50. Torsten Trimborn & Philipp Otte & Simon Cramer & Max Beikirch & Emma Pabich & Martin Frank, 2018. "SABCEMM-A Simulator for Agent-Based Computational Economic Market Models," Papers 1801.01811, arXiv.org, revised Oct 2018.
    51. Peralta, Antonio F. & Khalil, Nagi & Toral, Raúl, 2020. "Ordering dynamics in the voter model with aging," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 552(C).
    52. He, Xue-Zhong & Li, Kai & Wang, Chuncheng, 2016. "Volatility clustering: A nonlinear theoretical approach," Journal of Economic Behavior & Organization, Elsevier, vol. 130(C), pages 274-297.
    53. Francesco Lamperti, 2015. "An Information Theoretic Criterion for Empirical Validation of Time Series Models," LEM Papers Series 2015/02, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    54. Michael Wegener & Frank Westerhoff, 2012. "Evolutionary competition between prediction rules and the emergence of business cycles within Metzler’s inventory model," Journal of Evolutionary Economics, Springer, vol. 22(2), pages 251-273, April.
    55. Giorgio Fagiolo & Andrea Roventini, 2012. "Macroeconomic Policy in DSGE and Agent-Based Models," Working Papers 07/2012, University of Verona, Department of Economics.
    56. 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.
    57. Biondo, Alessio Emanuele & Mazzarino, Laura & Pluchino, Alessandro, 2024. "Trading strategies and Financial Performances: A simulation approach," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    58. Westerhoff, Frank, 2009. "A simple agent-based financial market model: Direct interactions and comparisons of trading profits," BERG Working Paper Series 61, Bamberg University, Bamberg Economic Research Group.
    59. Jacob Grazzini & Matteo Richiardi & Lisa Sella, 2012. "Indirect estimation of agent-based models.An application to a simple diffusion model," LABORatorio R. Revelli Working Papers Series 118, LABORatorio R. Revelli, Centre for Employment Studies.
    60. Alfarano, Simone & Lux, Thomas & Wagner, Friedrich, 2005. "Time-variation of higher moments in a financial market with heterogeneous agents: An analytical approach," Economics Working Papers 2005-14, Christian-Albrechts-University of Kiel, Department of Economics.
    61. Eduard Krkoska & Klaus Reiner Schenk-Hoppé, 2019. "Herding in Smart-Beta Investment Products," JRFM, MDPI, vol. 12(1), pages 1-14, March.
    62. Kononovicius, Aleksejus, 2021. "Supportive interactions in the noisy voter model," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    63. Aleksejus Kononovicius & Vygintas Gontis, 2012. "Three-state herding model of the financial markets," Papers 1210.1838, arXiv.org, revised Jan 2013.
    64. Zhenxi Chen & Thomas Lux, 2018. "Estimation of Sentiment Effects in Financial Markets: A Simulated Method of Moments Approach," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 711-744, October.
    65. Aleksejus Kononovicius & Vygintas Gontis, 2011. "Agent based reasoning for the non-linear stochastic models of long-range memory," Papers 1106.2685, arXiv.org, revised Aug 2011.
    66. Frank Westerhoff & Martin Hohnisch, 2007. "A note on interactions-driven business cycles," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 2(1), pages 85-91, June.
    67. Demary, Markus, 2009. "Transaction taxes and traders with heterogeneous investment horizons in an agent-based financial market model," Economics Discussion Papers 2009-47, Kiel Institute for the World Economy (IfW Kiel).
    68. Rytis Kazakevicius & Aleksejus Kononovicius & Bronislovas Kaulakys & Vygintas Gontis, 2021. "Understanding the nature of the long-range memory phenomenon in socioeconomic systems," Papers 2108.02506, arXiv.org, revised Aug 2021.
    69. Lines Marji & Westerhoff Frank, 2012. "Effects of Inflation Expectations on Macroeconomic Dynamics: Extrapolative Versus Regressive Expectations," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(4), pages 1-30, October.
    70. Grosche, Stephanie & Heckelei, Thomas, 2014. "Price dynamics and financialization effects in corn futures markets with heterogeneous traders," Discussion Papers 172077, University of Bonn, Institute for Food and Resource Economics.
    71. Jakob Grazzini, 2011. "Consistent Estimation of Agent Based Models," LABORatorio R. Revelli Working Papers Series 110, LABORatorio R. Revelli, Centre for Employment Studies.
    72. Alfarano, Simone & Lux, Thomas & Wagner, Friedrich, 2006. "Estimation of a simple agent-based model of financial markets: An application to Australian stock and foreign exchange data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(1), pages 38-42.
    73. Ghonghadze, Jaba & Lux, Thomas, 2015. "Bringing an elementary agent-based model to the data: Estimation via GMM and an application to forecasting of asset price volatility," FinMaP-Working Papers 38, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    74. Dieci, Roberto & Westerhoff, Frank, 2011. "On the inherent instability of international financial markets: Natural nonlinear interactions between stock and foreign exchange markets," BERG Working Paper Series 79, Bamberg University, Bamberg Economic Research Group.
    75. Bàrbara Llacay & Gilbert Peffer, 2018. "Using realistic trading strategies in an agent-based stock market model," Computational and Mathematical Organization Theory, Springer, vol. 24(3), pages 308-350, September.
    76. Clio Ciaschini & Kateryna Tkach & Francesca Mariani & Maria Cristina Recchioni, 2019. "Speculative bubbles in agricultural commodity prices: detection and forecasting via market indicators," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 73(2), pages 63-73, April-Jun.
    77. Cars Hommes & Florian Wagener, 2008. "Complex Evolutionary Systems in Behavioral Finance," Tinbergen Institute Discussion Papers 08-054/1, Tinbergen Institute.
    78. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2019. "Validation of Agent-Based Models in Economics and Finance," SciencePo Working papers Main halshs-02375423, HAL.
    79. Sylvain Barde, 2015. "Direct calibration and comparison of agent-based herding models of financial markets," Studies in Economics 1507, School of Economics, University of Kent.
    80. Tiziana Assenza & Jakob Grazzini & Domenico Massaro, 2019. "Introduction to the special issue," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(3), pages 431-436, September.
    81. Peter Winker & Manfred Gilli & Vahidin Jeleskovic, 2007. "An Objective Function for Simulation Based Inference on Exchange Rate Data," Swiss Finance Institute Research Paper Series 07-01, Swiss Finance Institute.
    82. Vygintas Gontis & Aleksejus Kononovicius, 2014. "Consentaneous Agent-Based and Stochastic Model of the Financial Markets," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-12, July.
    83. Grazzini, Jakob & Richiardi, Matteo, 2015. "Estimation of ergodic agent-based models by simulated minimum distance," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 148-165.
    84. Tubbenhauer, Tobias & Fieberg, Christian & Poddig, Thorsten, 2021. "Multi-agent-based VaR forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
    85. Francesco Lamperti, 2016. "Empirical Validation of Simulated Models through the GSL-div: an Illustrative Application," LEM Papers Series 2016/18, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    86. Radu T. Pruna & Maria Polukarov & Nicholas R. Jennings, 2020. "Loss aversion in an agent-based asset pricing model," Quantitative Finance, Taylor & Francis Journals, vol. 20(2), pages 275-290, February.
    87. Francesco Lamperti, 2018. "Empirical validation of simulated models through the GSL-div: an illustrative application," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(1), pages 143-171, April.
    88. Xue-Zhong He, 2012. "Recent Developments on Heterogeneous Beliefs and Adaptive Behaviour of Financial Markets," Research Paper Series 316, Quantitative Finance Research Centre, University of Technology, Sydney.
    89. Jakob Grazzini & Matteo Richiardi & Mike Tsionas, 2015. "Bayesian Estimation of Agent-Based Models," Economics Papers 2015-W12, Economics Group, Nuffield College, University of Oxford.
    90. He, Xue-Zhong & Li, Kai, 2012. "Heterogeneous beliefs and adaptive behaviour in a continuous-time asset price model," Journal of Economic Dynamics and Control, Elsevier, vol. 36(7), pages 973-987.
    91. Tedeschi, Gabriele & Recchioni, Maria Cristina & Berardi, Simone, 2019. "An approach to identifying micro behavior: How banks’ strategies influence financial cycles," Journal of Economic Behavior & Organization, Elsevier, vol. 162(C), pages 329-346.
    92. Wieland, Volker & Binder, Michael & Lieberknecht, Philipp & Quintana, Jorge, 2017. "Model Uncertainty in Macroeconomics: On the Implications of Financial Frictions," CEPR Discussion Papers 12013, C.E.P.R. Discussion Papers.
    93. Giorgio Fagiolo & Andrea Roventini, 2016. "Macroeconomic Policy in DGSE and Agent-Based Models Redux," Working Papers hal-03459348, HAL.
    94. Raquel Almeida Ramos & Federico Bassi & Dany Lang, 2020. "Bet against the trend and cash in profits," Working Papers halshs-02956879, HAL.
    95. Todd Feldman & Shuming Liu, 2018. "A New Predictive Measure Using Agent-Based Behavioral Finance," Computational Economics, Springer;Society for Computational Economics, vol. 51(4), pages 941-959, April.
    96. Lof, Matthijs, 2013. "Essays on Expectations and the Econometrics of Asset Pricing," MPRA Paper 59064, University Library of Munich, Germany.
    97. Lucas Fievet & Didier Sornette, 2018. "Calibrating emergent phenomena in stock markets with agent based models," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-17, March.
    98. Andrew G. Haldane & Arthur E. Turrell, 2019. "Drawing on different disciplines: macroeconomic agent-based models," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 39-66, March.
    99. Franke, Reiner & Westerhoff, Frank, 2012. "Structural stochastic volatility in asset pricing dynamics: Estimation and model contest," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1193-1211.
    100. Kononovicius, A. & Gontis, V., 2012. "Agent based reasoning for the non-linear stochastic models of long-range memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1309-1314.
    101. Xu, Shaojun, 2023. "Behavioral asset pricing under expected feedback mode," International Review of Financial Analysis, Elsevier, vol. 86(C).
    102. Alfarano, Simone & Lux, Thomas & Wagner, Friedrich, 2010. "Excess Volatility and Herding in an Artificial Financial Market: Analytical Approach and Estimation," MPRA Paper 24719, University Library of Munich, Germany.
    103. Raddant, Matthias & Wagner, Friedrich, 2013. "Phase transition in the S&P stock market," Kiel Working Papers 1846, Kiel Institute for the World Economy (IfW Kiel).
    104. Federico Bassi & Dany Lang & Raquel Almeida Ramos, 2023. "Bet against the trend and cash in profits: An agent‑based model of endogenous fluctuations of exchange rates," Post-Print hal-04428234, HAL.
    105. V. Alfi & M. Cristelli & L. Pietronero & A. Zaccaria, 2008. "Minimal Agent Based Model for Financial Markets I: Origin and Self-Organization of Stylized Facts," Papers 0808.3562, arXiv.org.
    106. Gontis, V. & Havlin, S. & Kononovicius, A. & Podobnik, B. & Stanley, H.E., 2016. "Stochastic model of financial markets reproducing scaling and memory in volatility return intervals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1091-1102.
    107. Carl Chiarella & Roberto Dieci & Xue-Zhong He, 2009. "A Framework for CAPM with Heterogenous Beliefs," Research Paper Series 254, Quantitative Finance Research Centre, University of Technology, Sydney.
    108. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.
    109. Venelina Nikolova & Juan E. Trinidad Segovia & Manuel Fernández-Martínez & Miguel Angel Sánchez-Granero, 2020. "A Novel Methodology to Calculate the Probability of Volatility Clusters in Financial Series: An Application to Cryptocurrency Markets," Mathematics, MDPI, vol. 8(8), pages 1-15, July.
    110. Frank Westerhoff & Martin Hohnisch, 2010. "Consumer sentiment and countercyclical fiscal policies," International Review of Applied Economics, Taylor & Francis Journals, vol. 24(5), pages 609-618.
    111. Kukacka, Jiri & Kristoufek, Ladislav, 2020. "Do ‘complex’ financial models really lead to complex dynamics? Agent-based models and multifractality," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    112. Hommes, Cars & in ’t Veld, Daan, 2017. "Booms, busts and behavioural heterogeneity in stock prices," Journal of Economic Dynamics and Control, Elsevier, vol. 80(C), pages 101-124.
    113. Todd Feldman & Daniel Friedman, 2010. "Human and Artificial Agents in a Crash-Prone Financial Market," Computational Economics, Springer;Society for Computational Economics, vol. 36(3), pages 201-229, October.
    114. Didier SORNETTE, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based Models," Swiss Finance Institute Research Paper Series 14-25, Swiss Finance Institute.
    115. 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.
    116. Mattia Guerini & Alessio Moneta, 2016. "A Method for Agent-Based Models Validation," Working Papers Series 42, Institute for New Economic Thinking.
    117. Demary Markus, 2008. "Who Does a Currency Transaction Tax Harm More: Short-Term Speculators or Long-Term Investors?," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(2-3), pages 228-250, April.
    118. 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).
    119. Tiziana Assenza & William Brock & Cars Hommes, 2013. "Animal Spirits, Heterogeneous Expectations and the Emergence of Booms and Busts," DISCE - Working Papers del Dipartimento di Economia e Finanza def007, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    120. Yi-Fang Liu & Wei Zhang & Chao Xu & Jørgen Vitting Andersen & Hai-Chuan Xu, 2014. "Impact of information cost and switching of trading strategies in an artificial stock market," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01215947, HAL.
    121. 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).
    122. Zheng, Min & Liu, Ruipeng & Li, Youwei, 2018. "Long memory in financial markets: A heterogeneous agent model perspective," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 38-51.
    123. Guy Maugis, Pierre-André, 2017. "Paradigm shifts," Economics Discussion Papers 2017-92, Kiel Institute for the World Economy (IfW Kiel).
    124. Franke, Reiner, 2010. "On the specification of noise in two agent-based asset pricing models," Journal of Economic Dynamics and Control, Elsevier, vol. 34(6), pages 1140-1152, June.
    125. Aleksejus Kononovicius, 2017. "Empirical Analysis and Agent-Based Modeling of the Lithuanian Parliamentary Elections," Complexity, Hindawi, vol. 2017, pages 1-15, November.
    126. Xue-Zhong He & Youwei Li, 2015. "The Adaptiveness in Stock Markets: Testing the Stylized Facts in the Dax 30," Research Paper Series 364, Quantitative Finance Research Centre, University of Technology, Sydney.
    127. Simone Berardi & Gabriele Tedeschi, 2016. "How banks’ strategies influence financial cycles: An approach to identifying micro behavior," Working Papers 2016/24, Economics Department, Universitat Jaume I, Castellón (Spain).
    128. Ji, Jingru & Wang, Donghua & Xu, Dinghai, 2019. "Modelling the spreading process of extreme risks via a simple agent-based model: Evidence from the China stock market," Economic Modelling, Elsevier, vol. 80(C), pages 383-391.
    129. Zhao, Zhijun & Zhang, Xiaoqi, 2022. "A continuous heterogeneous-agent model for the co-evolution of asset price and wealth distribution in financial market," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    130. Zhang, Yu-Xia & Liao, Hao & Medo, Matus & Shang, Ming-Sheng & Yeung, Chi Ho, 2016. "Study of market model describing the contrary behaviors of informed and uninformed agents: Being minority and being majority," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 486-496.
    131. Lines, Marji & Westerhoff, Frank, 2010. "Inflation expectations and macroeconomic dynamics: The case of rational versus extrapolative expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 34(2), pages 246-257, February.
    132. Carl Chiarella & Xue-Zhong He & Weihong Huang & Huanhuan Zheng, 2011. "Estimating Behavioural Heterogeneity Under Regime Switching," Research Paper Series 290, Quantitative Finance Research Centre, University of Technology, Sydney.
    133. Yi-Fang Liu & Wei Zhang & Chao Xu & J{o}rgen Vitting Andersen & Hai-Chuan Xu, 2013. "Impact of information cost and switching of trading strategies in an artificial stock market," Papers 1311.4274, arXiv.org, revised Jul 2014.
    134. 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.
    135. Giovanni Dosi & Andrea Roventini, 2019. "More is different ... and complex! the case for agent-based macroeconomics," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 1-37, March.
    136. Aleksejus Kononovicius & Valentas Daniunas, 2013. "Agent-based and macroscopic modeling of the complex socio-economic systems," Papers 1303.3693, arXiv.org, revised Apr 2013.
    137. Blake LeBaron, 2021. "Microconsistency in Simple Empirical Agent-Based Financial Models," Computational Economics, Springer;Society for Computational Economics, vol. 58(1), pages 83-101, June.
    138. Yi-Fang Liu & Wei Zhang & Chao Xu & Jørgen Vitting Andersen & Hai-Chuan Xu, 2014. "Impact of information cost and switching of trading strategies in an artificial stock market," Post-Print halshs-01215947, HAL.
    139. Tae-Seok Jang, 2015. "Identification of Social Interaction Effects in Financial Data," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 207-238, February.
    140. Qingfu Liu & Yiuman Tse & Kaixin Zheng, 2021. "The impact of trading behavioral biases on market liquidity under different volatility levels: Evidence from the Chinese commodity futures market," The Financial Review, Eastern Finance Association, vol. 56(4), pages 671-692, November.
    141. Jiri Kukacka & Jozef Barunik, 2012. "Behavioural breaks in the heterogeneous agent model: the impact of herding, overconfidence, and market sentiment," Papers 1205.3763, arXiv.org, revised May 2013.
    142. Domenico Delli Gatti & Tommaso Ferraresi & Filippo Gusella & Lilit Popoyan & Giorgio Ricchiuti & Andrea Roventini, 2024. "The interplay between real and exchange rate market: an agent-based model approach," Working Papers - Economics wp2024_10.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    143. Simon Cramer & Torsten Trimborn, 2019. "Stylized Facts and Agent-Based Modeling," Papers 1912.02684, arXiv.org.
    144. Vygintas Gontis & Aleksejus Kononovicius, 2019. "Bessel-like birth-death process," Papers 1904.13064, arXiv.org, revised Oct 2019.
    145. Daye Li & Rongrong Li & Qiankun Sun, 2017. "How the heterogeneity in investment horizons affects market trends," Applied Economics, Taylor & Francis Journals, vol. 49(15), pages 1473-1482, March.
    146. David Allen & Stephen Satchell & Colin Lizieri, 2024. "Quantifying the non-Gaussian gain," Journal of Asset Management, Palgrave Macmillan, vol. 25(1), pages 1-18, February.
    147. Alfarano, Simone & Milakovic, Mishael, 2010. "Identification of Interaction Effects in Survey Expectations: A Cautionary Note," MPRA Paper 26002, University Library of Munich, Germany.
    148. Donovan Platt, 2019. "A Comparison of Economic Agent-Based Model Calibration Methods," Papers 1902.05938, arXiv.org.
    149. Friedrich Wagner, 2011. "Market clearing by maximum entropy in agent models of stock markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 6(2), pages 121-138, November.
    150. Frank M. A. Klingert & Matthias Meyer, 2018. "Comparing Prediction Market Mechanisms: An Experiment-Based and Micro Validated Multi-Agent Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 21(1), pages 1-7.
    151. 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.
    152. Aleksejus Kononovicius & Vygintas Gontis, 2014. "Herding interactions as an opportunity to prevent extreme events in financial markets," Papers 1409.8024, arXiv.org, revised May 2015.
    153. Ha Che-Ngoc & Nga Do-Thi & Thao Nguyen-Trang, 2023. "Profitability of Ichimoku-Based Trading Rule in Vietnam Stock Market in the Context of the COVID-19 Outbreak," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1781-1799, December.
    154. Fathi Abid & Bilel Kaffel, 2018. "The extent of virgin olive-oil prices’ distribution revealing the behavior of market speculators," Review of Quantitative Finance and Accounting, Springer, vol. 50(2), pages 561-590, February.
    155. Platt, Donovan, 2020. "A comparison of economic agent-based model calibration methods," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    156. Hohnisch, Martin & Westerhoff, Frank, 2008. "Business cycle synchronization in a simple Keynesian macro-model with socially transmitted economic sentiment and international sentiment spill-over," Structural Change and Economic Dynamics, Elsevier, vol. 19(3), pages 249-259, September.
    157. Franke, Reiner, 2008. "Artificial Long Memory Effects in Two Agend-Based Asset Pricing Models," Economics Working Papers 2008-15, Christian-Albrechts-University of Kiel, Department of Economics.
    158. He, Xue-Zhong & Li, Youwei & Zheng, Min, 2019. "Heterogeneous agent models in financial markets: A nonlinear dynamics approach," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 135-149.
    159. Yi-Fang Liu & Wei Zhang & Chao Xu & Jørgen Vitting Andersen & Hai-Chuan Xu, 2014. "Impact of information cost and switching of trading strategies in an artificial stock market," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00983051, HAL.
    160. 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.
    161. Vipin P. Veetil & Lawrence H. White, 2017. "Towards a New Austrian Macroeconomics," The Review of Austrian Economics, Springer;Society for the Development of Austrian Economics, vol. 30(1), pages 19-38, March.
    162. Baur, Dirk G. & Glover, Kristoffer J., 2014. "Heterogeneous expectations in the gold market: Specification and estimation," Journal of Economic Dynamics and Control, Elsevier, vol. 40(C), pages 116-133.
    163. Ron Bird & Lorenzo Casavecchia & Paul Woolley, 2008. "Insights into the Market Impact of Different Investment Styles," Working Paper Series 1, The Paul Woolley Centre for Capital Market Dysfunctionality, University of Technology, Sydney.
    164. Maria Elvira Mancino & Maria Cristina Recchioni, 2015. "Fourier Spot Volatility Estimator: Asymptotic Normality and Efficiency with Liquid and Illiquid High-Frequency Data," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-33, September.
    165. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
    166. Vygintas Gontis & Aleksejus Kononovicius, 2017. "Spurious memory in non-equilibrium stochastic models of imitative behavior," Papers 1707.09801, arXiv.org.
    167. Vygintas Gontis & Shlomo Havlin & Aleksejus Kononovicius & Boris Podobnik & H. Eugene Stanley, 2015. "Stochastic model of financial markets reproducing scaling and memory in volatility return intervals," Papers 1507.05203, arXiv.org, revised Oct 2016.
    168. Krause, Sebastian M. & Bornholdt, Stefan, 2013. "Spin models as microfoundation of macroscopic market models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(18), pages 4048-4054.
    169. Adri'an Carro & Ra'ul Toral & Maxi San Miguel, 2015. "Markets, herding and response to external information," Papers 1506.03708, arXiv.org, revised Jun 2015.
    170. Adrián Carro & Raúl Toral & Maxi San Miguel, 2015. "Markets, Herding and Response to External Information," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-28, July.
    171. Gontis, V. & Kononovicius, A., 2020. "Bessel-like birth–death process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    172. Lamperti, Francesco, 2018. "An information theoretic criterion for empirical validation of simulation models," Econometrics and Statistics, Elsevier, vol. 5(C), pages 83-106.
    173. Alfarano, Simone & Milaković, Mishael & Raddant, Matthias, 2009. "Network hierarchy in Kirman's ant model: fund investment can create systemic risk," Economics Working Papers 2009-09, Christian-Albrechts-University of Kiel, Department of Economics.
    174. Coqueret, Guillaume, 2017. "Empirical properties of a heterogeneous agent model in large dimensions," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 180-201.
    175. Cafferata, Alessia & Tramontana, Fabio, 2022. "Disposition Effect and its outcome on endogenous price fluctuations," MPRA Paper 113904, University Library of Munich, Germany.
    176. Donovan Platt & Tim Gebbie, 2016. "The Problem of Calibrating an Agent-Based Model of High-Frequency Trading," Papers 1606.01495, arXiv.org, revised Mar 2017.
    177. Ghonghadze, Jaba & Lux, Thomas, 2016. "Bringing an elementary agent-based model to the data: Estimation via GMM and an application to forecasting of asset price volatility," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 1-19.
    178. Markus Demary, 2011. "Transaction taxes, greed and risk aversion in an agent-based financial market model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 6(1), pages 1-28, May.
    179. Tai Vo-Van & Ha Che-Ngoc & Nghiep Le-Dai & Thao Nguyen-Trang, 2022. "A New Strategy for Short-Term Stock Investment Using Bayesian Approach," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 887-911, February.
    180. Guy Maugis, Pierre-André, 2019. "Paradigm shifts," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 13, pages 1-9.
    181. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Kiel Working Papers 1426, Kiel Institute for the World Economy (IfW Kiel).
    182. Hisakado, Masato & Mori, Shintaro, 2015. "Information cascade, Kirman’s ant colony model, and kinetic Ising model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 417(C), pages 63-75.
    183. Aleksejus Kononovicius & Julius Ruseckas, 2018. "Order book model with herd behavior exhibiting long-range memory," Papers 1809.02772, arXiv.org, revised Apr 2019.
    184. Yi-Fang Liu & Wei Zhang & Chao Xu & Jørgen Vitting Andersen & Hai-Chuan Xu, 2014. "Impact of information cost and switching of trading strategies in an artificial stock market," Documents de travail du Centre d'Economie de la Sorbonne 14031, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    185. Westerhoff Frank H., 2008. "The Use of Agent-Based Financial Market Models to Test the Effectiveness of Regulatory Policies," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(2-3), pages 195-227, April.
    186. Xiong, Hang & Payne, Diane & Kinsella, Stephen, 2016. "Peer effects in the diffusion of innovations: Theory and simulation," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 63(C), pages 1-13.
    187. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2007. "Agent-based Models of Financial Markets," Papers physics/0701140, arXiv.org.
    188. Torsten Trimborn & Philipp Otte & Simon Cramer & Maximilian Beikirch & Emma Pabich & Martin Frank, 2020. "SABCEMM: A Simulator for Agent-Based Computational Economic Market Models," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 707-744, February.
    189. Simone Landini & Mauro Gallegati & Joseph Stiglitz, 2015. "Economies with heterogeneous interacting learning agents," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(1), pages 91-118, April.
    190. V. Alfi & L. Pietronero & A. Zaccaria, 2008. "Minimal Agent Based Model For The Origin And Self-Organization Of Stylized Facts In Financial Markets," Papers 0807.1888, arXiv.org.
    191. Benjamin Patrick Evans & Mikhail Prokopenko, 2022. "Bounded strategic reasoning explains crisis emergence in multi-agent market games," Papers 2206.05568, arXiv.org.
    192. Vygintas Gontis & Aleksejus Kononovicius & Stefan Reimann, 2012. "The class of nonlinear stochastic models as a background for the bursty behavior in financial markets," Papers 1201.3083, arXiv.org, revised May 2012.
    193. Adri'an Carro & Ra'ul Toral & Maxi San Miguel, 2013. "Signal amplification in an agent-based herding model," Papers 1302.6477, arXiv.org, revised Sep 2015.
    194. Makoto Nirei & Theodoros Stamatiou & Vladyslav Sushko, 2012. "Stochastic Herding in Financial Markets Evidence from Institutional Investor Equity Portfolios," BIS Working Papers 371, Bank for International Settlements.
    195. 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.
    196. Leonid Serkov & Sergey Krasnykh, 2023. "Peculiarity of Behavior of Economic Agents under Cognitive Constraints in a Semi-Open New Keynesian Model," Mathematics, MDPI, vol. 12(1), pages 1-22, December.
    197. Alfarano, Simone & Milakovic, Mishael, 2009. "Network structure and N-dependence in agent-based herding models," Journal of Economic Dynamics and Control, Elsevier, vol. 33(1), pages 78-92, January.
    198. Aleksejus Kononovicius & Vygintas Gontis, 2013. "Control of the socio-economic systems using herding interactions," Papers 1309.6105, arXiv.org, revised Feb 2014.

Chapters

  1. Simone Alfarano & Thomas Lux, 2007. "A Minimal Noise Trader Model with Realistic Time Series Properties," Springer Books, in: Gilles Teyssière & Alan P. Kirman (ed.), Long Memory in Economics, pages 345-361, Springer.
    See citations under working paper version above.Sorry, no citations of chapters recorded.

Books

  1. Andrea Teglio & Simone Alfarano & Eva Camacho-Cuena & Miguel Ginés-Vilar (ed.), 2013. "Managing Market Complexity," Lecture Notes in Economics and Mathematical Systems, Springer, edition 127, number 978-3-642-31301-1, October.

    Cited by:

    1. Thomas Fischer, 2017. "Can Redistribution by Means of a Progressive Labor Income-Taxation Transfer System Increase Financial Stability?," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 20(2), pages 1-3.
    2. Anufriev, M. & Hommes, C.H. & Makarewicz, T.A., 2015. "Simple Forecasting Heuristics that Make us Smart: Evidence from Different Market Experiments," CeNDEF Working Papers 15-07, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.