IDEAS home Printed from https://ideas.repec.org/r/eee/jeborg/v81y2012i1p82-96.html
   My bibliography  Save this item

Herding effects in order driven markets: The rise and fall of gurus

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Galariotis, Emilios C. & Rong, Wu & Spyrou, Spyros I., 2015. "Herding on fundamental information: A comparative study," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 589-598.
  2. Jiewang Chu & Jiaxuan Li, 2022. "The Composition and Operation Mechanism of Digital Entrepreneurial Ecosystem: A Study of Hangzhou Yunqi Town as an Example," Sustainability, MDPI, vol. 14(24), pages 1-19, December.
  3. Alessio Emanuele Biondo, 2020. "Information versus imitation in a real-time agent-based model of financial markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(3), pages 613-631, July.
  4. Alessio Emanuele Biondo, 2018. "Order book microstructure and policies for financial stability," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 35(1), pages 196-218, March.
  5. Pascal Seppecher & Isabelle Salle, 2015. "Deleveraging crises and deep recessions: a behavioural approach," Applied Economics, Taylor & Francis Journals, vol. 47(34-35), pages 3771-3790, July.
  6. Alessio Emanuele Biondo, 2019. "Order book modeling and financial stability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(3), pages 469-489, September.
  7. Vivien Lespagnol & Juliette Rouchier, 2014. "Trading volume and market efficiency: an Agent Based Model with heterogenous knowledge about fundamentals," AMSE Working Papers 1419, Aix-Marseille School of Economics, France, revised May 2014.
  8. 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).
  9. 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.
  10. 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.
  11. Егорова Людмила Геннадьевна, 2014. "Эффективность Торговых Стратегий Мелких Трейдеров," Проблемы управления, CyberLeninka;Общество с ограниченной ответственностью "СенСиДат-Контрол", issue 5, pages 34-41.
  12. Brzezicka Justyna & Wisniewski Radosław, 2014. "Price Bubble In The Real Estate Market - Behavioral Aspects," Real Estate Management and Valuation, Sciendo, vol. 22(1), pages 1-14, March.
  13. Alessio Emanuele Biondo & Alessandro Pluchino & Andrea Rapisarda & Dirk Helbing, 2013. "Are Random Trading Strategies More Successful than Technical Ones?," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-13, July.
  14. Vivien Lespagnol & Juliette Rouchier, 2015. "What Is the Impact of Heterogeneous Knowledge About Fundamentals on Market Liquidity and Efficiency: An ABM Approach," Lecture Notes in Economics and Mathematical Systems, in: Frédéric Amblard & Francisco J. Miguel & Adrien Blanchet & Benoit Gaudou (ed.), Advances in Artificial Economics, edition 127, pages 105-117, Springer.
  15. Humayun Kabir, M. & Shakur, Shamim, 2018. "Regime-dependent herding behavior in Asian and Latin American stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 47(C), pages 60-78.
  16. 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.
  17. Liudmila G. Egorova, 2014. "The Effectiveness Of Different Trading Strategies For Price-Takers," HSE Working papers WP BRP 29/FE/2014, National Research University Higher School of Economics.
  18. Gabriele Tedeschi & Stefania Vitali & Mauro Gallegati, 2014. "The dynamic of innovation networks: a switching model on technological change," Journal of Evolutionary Economics, Springer, vol. 24(4), pages 817-834, September.
  19. Bao, Te & Corgnet, Brice & Hanaki, Nobuyuki & Riyanto, Yohanes E. & Zhu, Jiahua, 2023. "Predicting the unpredictable: New experimental evidence on forecasting random walks," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
  20. Goldbaum, David, 2021. "The origins of influence," Economic Modelling, Elsevier, vol. 97(C), pages 380-396.
  21. 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.
  22. Patrick Chang, 2020. "Fourier instantaneous estimators and the Epps effect," Papers 2007.03453, arXiv.org, revised Sep 2020.
  23. Vivien Lespagnol & Juliette Rouchier, 2018. "Trading Volume and Price Distortion: An Agent-Based Model with Heterogenous Knowledge of Fundamentals," Computational Economics, Springer;Society for Computational Economics, vol. 51(4), pages 991-1020, April.
  24. Jan Polach & Jiri Kukacka, 2019. "Prospect Theory in the Heterogeneous Agent Model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(1), pages 147-174, March.
  25. 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.
  26. 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.
  27. 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.
  28. 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.
  29. A. E. Biondo & A. Pluchino & A. Rapisarda & D. Helbing, 2013. "Are random trading strategies more successful than technical ones?," Papers 1303.4351, arXiv.org, revised Jul 2013.
  30. Misha Perepelitsa & Ilya Timofeyev, 2022. "Self-sustained price bubbles driven by digital currency innovations and adaptive market behavior," SN Business & Economics, Springer, vol. 2(3), pages 1-15, March.
  31. 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.
  32. Riccetti, Luca & Russo, Alberto & Gallegati, Mauro, 2016. "Stock market dynamics, leveraged network-based financial accelerator and monetary policy," International Review of Economics & Finance, Elsevier, vol. 43(C), pages 509-524.
  33. Iori, G. & Porter, J., 2012. "Agent-Based Modelling for Financial Markets," Working Papers 12/08, Department of Economics, City University London.
  34. Wang, Guocheng & Wang, Yanyi, 2018. "Herding, social network and volatility," Economic Modelling, Elsevier, vol. 68(C), pages 74-81.
  35. 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.
  36. Lenzu, Simone & Tedeschi, Gabriele, 2012. "Systemic risk on different interbank network topologies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(18), pages 4331-4341.
  37. Bargigli, Leonardo & Tedeschi, Gabriele, 2014. "Interaction in agent-based economics: A survey on the network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 399(C), pages 1-15.
  38. 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).
  39. Ibrahim Filiz & Thomas Nahmer & Markus Spiwoks & Kilian Bizer, 2018. "Portfolio diversification: the influence of herding, status-quo bias, and the gambler’s fallacy," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 32(2), pages 167-205, May.
  40. 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.
  41. Grilli, Ruggero & Tedeschi, Gabriele & Gallegati, Mauro, 2020. "Business fluctuations in a behavioral switching model: Gridlock effects and credit crunch phenomena in financial networks," Journal of Economic Dynamics and Control, Elsevier, vol. 114(C).
  42. 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.
  43. Blaurock, Ivonne & Schmitt, Noemi & Westerhoff, Frank, 2018. "Market entry waves and volatility outbursts in stock markets," Journal of Economic Behavior & Organization, Elsevier, vol. 153(C), pages 19-37.
  44. Fabio Della Rossa & Lorenzo Giannini & Pietro DeLellis, 2020. "Herding or wisdom of the crowd? Controlling efficiency in a partially rational financial market," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-16, September.
  45. Mark Setterfield & Bill Gibson, 2013. "Real and financial crises: A multi-agent approach," Working Papers 1309, Trinity College, Department of Economics, revised Jul 2014.
  46. Lu, Jingen & Chen, Xiaohong & Liu, Xiaoxing, 2018. "Stock market information flow: Explanations from market status and information-related behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 837-848.
  47. Galariotis, Emilios C. & Krokida, Styliani-Iris & Spyrou, Spyros I., 2016. "Bond market investor herding: Evidence from the European financial crisis," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 367-375.
  48. Li, Zhuolei & Diao, Xundi & Wu, Chongfeng, 2022. "The influence of mobile trading on return dispersion and herding behavior," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).
  49. 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.
  50. Muskan Sachdeva & Ritu Lehal & Sanjay Gupta & Aashish Garg, 2021. "What make investors herd while investing in the Indian stock market? A hybrid approach," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 15(1), pages 19-37, September.
  51. Tubbenhauer, Tobias & Fieberg, Christian & Poddig, Thorsten, 2021. "Multi-agent-based VaR forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
  52. Hazem Krichene & Mhamed-Ali El-Aroui, 2018. "Artificial stock markets with different maturity levels: simulation of information asymmetry and herd behavior using agent-based and network models," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(3), pages 511-535, October.
  53. Vivien Lespagnol & Juliette Rouchier, 2018. "Trading Volume and Price Distortion: An Agent-Based Model with Heterogenous Knowledge of Fundamentals," Post-Print hal-02084910, HAL.
  54. Delli Gatti,Domenico & Fagiolo,Giorgio & Gallegati,Mauro & Richiardi,Matteo & Russo,Alberto (ed.), 2018. "Agent-Based Models in Economics," Cambridge Books, Cambridge University Press, number 9781108400046.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.