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An agent-based modeling approach for analyzing the influence of market participants’ strategic behavior on green certificate trading

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  • Hui, Wang
  • Xin-gang, Zhao
  • Ling-zhi, Ren
  • Fan, Lu

Abstract

China has announced that the mandatory green certificate trading would be implemented in 2021. The mandatory green certificate trading not only fosters the liquidity of the green certificate market but also induces the possibility of market participants taking strategic behavior to gain more market returns. Generally, the self-interested strategic behavior was not conducive to improving market efficiency, thereby impeding the implementation of mandatory green certificate trading. To evaluate the influence of market participants’ strategic behavior on the green certificate trading, we embed the strategic behavior model into the artificial green certificate market to simulate the market participants’ strategic behavior in green certificate trading. The results indicate: (1) in green certificate market, the strength of the herd effect determines the average compliance costs level; (2) the value-trading strategy is the optimal strategy for renewable obligation subjects to reduce the compliance costs of mandatory green certificate trading; (3) market participants’ strategic behavior mainly affect the stability of green certificate price, and the greater the price fluctuation, the slower convergence speed to the equilibrium price.

Suggested Citation

  • Hui, Wang & Xin-gang, Zhao & Ling-zhi, Ren & Fan, Lu, 2021. "An agent-based modeling approach for analyzing the influence of market participants’ strategic behavior on green certificate trading," Energy, Elsevier, vol. 218(C).
  • Handle: RePEc:eee:energy:v:218:y:2021:i:c:s0360544220325706
    DOI: 10.1016/j.energy.2020.119463
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    as
    1. Shi, Yingying & Zeng, Yongchao & Engo, Jean & Han, Botang & Li, Yang & Muehleisen, Ralph T., 2020. "Leveraging inter-firm influence in the diffusion of energy efficiency technologies: An agent-based model," Applied Energy, Elsevier, vol. 263(C).
    2. Eirik S. Amundsen & Gjermund Nese, 2016. "Market Power in Interactive Environmental and Energy Markets: The Case of Green Certificates," CESifo Working Paper Series 5922, CESifo.
    3. 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.
    4. Eirik Amundsen & Fridrik Baldursson & Jørgen Mortensen, 2006. "Price Volatility and Banking in Green Certificate Markets," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 35(4), pages 259-287, December.
    5. Marco Cipriani & Antonio Guarino, 2005. "Herd Behavior in a Laboratory Financial Market," American Economic Review, American Economic Association, vol. 95(5), pages 1427-1443, December.
    6. Arvind Shrivats & Sebastian Jaimungal, 2020. "Optimal Generation and Trading in Solar Renewable Energy Certificate (SREC) Markets," Applied Mathematical Finance, Taylor & Francis Journals, vol. 27(1-2), pages 99-131, July.
    7. LeBaron, Blake, 2006. "Agent-based Computational Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 24, pages 1187-1233, Elsevier.
    8. Tesfatsion, Leigh, 2006. "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 16, pages 831-880, Elsevier.
    9. Jessica James, 2003. "Simple trend-following strategies in currency trading," Quantitative Finance, Taylor & Francis Journals, vol. 3(4), pages 75-77.
    10. Ciarreta, Aitor & Espinosa, Maria Paz & Pizarro-Irizar, Cristina, 2017. "Optimal regulation of renewable energy: A comparison of Feed-in Tariffs and Tradable Green Certificates in the Spanish electricity system," Energy Economics, Elsevier, vol. 67(C), pages 387-399.
    11. Arvind Shrivats & Dena Firoozi & Sebastian Jaimungal, 2020. "A Mean-Field Game Approach to Equilibrium Pricing in Solar Renewable Energy Certificate Markets," Papers 2003.04938, arXiv.org, revised Aug 2021.
    12. Bhattacharya, Suparna & Giannakas, Konstantinos & Schoengold, Karina, 2017. "Market and welfare effects of renewable portfolio standards in United States electricity markets," Energy Economics, Elsevier, vol. 64(C), pages 384-401.
    13. Lee, Eun Jung & Eom, Kyong Shik & Park, Kyung Suh, 2013. "Microstructure-based manipulation: Strategic behavior and performance of spoofing traders," Journal of Financial Markets, Elsevier, vol. 16(2), pages 227-252.
    14. Arvind Shrivats & Sebastian Jaimungal, 2019. "Optimal Behaviour in Solar Renewable Energy Certificate (SREC) Markets," Papers 1904.06337, arXiv.org, revised Apr 2020.
    15. Stavrakas, Vassilis & Papadelis, Sotiris & Flamos, Alexandros, 2019. "An agent-based model to simulate technology adoption quantifying behavioural uncertainty of consumers," Applied Energy, Elsevier, vol. 255(C).
    16. Amundsen, Eirik Schrøder & Nese, Gjermund, 2016. "Market power in interactive environmental and energy markets: The case of green certificates," Working Papers in Economics 04/16, University of Bergen, Department of Economics.
    17. J. Doyne Farmer & Duncan Foley, 2009. "The economy needs agent-based modelling," Nature, Nature, vol. 460(7256), pages 685-686, August.
    18. Rostek, Marzena & Weretka, Marek, 2015. "Information and strategic behavior," Journal of Economic Theory, Elsevier, vol. 158(PB), pages 536-557.
    19. Jensen, S. G. & Skytte, K., 2002. "Interactions between the power and green certificate markets," Energy Policy, Elsevier, vol. 30(5), pages 425-435, April.
    20. Sachs, Julia & Meng, Yiming & Giarola, Sara & Hawkes, Adam, 2019. "An agent-based model for energy investment decisions in the residential sector," Energy, Elsevier, vol. 172(C), pages 752-768.
    21. Eirik S. Amundsen and Lars Bergman, 2012. "Green Certificates and Market Power on the Nordic Power Market," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    22. Merrick, John Jr & Naik, Narayan Y. & Yadav, Pradeep K., 2005. "Strategic trading behavior and price distortion in a manipulated market: anatomy of a squeeze," Journal of Financial Economics, Elsevier, vol. 77(1), pages 171-218, July.
    23. Hogan, Steve & Jarrow, Robert & Teo, Melvyn & Warachka, Mitch, 2004. "Testing market efficiency using statistical arbitrage with applications to momentum and value strategies," Journal of Financial Economics, Elsevier, vol. 73(3), pages 525-565, September.
    24. Helgesen, Per Ivar & Tomasgard, Asgeir, 2018. "An equilibrium market power model for power markets and tradable green certificates, including Kirchhoff's Laws and Nash-Cournot competition," Energy Economics, Elsevier, vol. 70(C), pages 270-288.
    25. Rzeszutek, Marcin & Godin, Antoine & Szyszka, Adam & Augier, Stanislas, 2020. "Managerial overconfidence in initial public offering decisions and its impact on macrodynamics and financial stability: Analysis using an agent-based model," Journal of Economic Dynamics and Control, Elsevier, vol. 118(C).
    26. Vo, Xuan Vinh & Phan, Dang Bao Anh, 2017. "Further evidence on the herd behavior in Vietnam stock market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 13(C), pages 33-41.
    27. Kannai, Yakar & Rosenmüller, Joachim, 2010. "Strategic behavior in financial markets," Journal of Mathematical Economics, Elsevier, vol. 46(2), pages 148-162, March.
    28. Espey, Simone, 2001. "Renewables portfolio standard: a means for trade with electricity from renewable energy sources?," Energy Policy, Elsevier, vol. 29(7), pages 557-566, June.
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