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Econometric analysis of microscopic simulation models

Author

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  • Youwei Li
  • Bas Donkers
  • Bertrand Melenberg
Abstract
Microscopic simulation models are often evaluated based on visual inspection of the results. This paper presents formal econometric techniques to compare microscopic simulation (MS) models with real-life data. A related result is a methodology to compare different MS models with each other. For this purpose, possible parameters of interest, such as mean returns, or autocorrelation patterns, are classified and characterized. For each class of characteristics, the appropriate techniques are presented. We illustrate the methodology by comparing the MS model developed by He and Li [J. Econ. Dynam. Control, 2007, 31, 3396-3426, Quant. Finance, 2008, 8, 59-79] with actual data.

Suggested Citation

  • Youwei Li & Bas Donkers & Bertrand Melenberg, 2010. "Econometric analysis of microscopic simulation models," Quantitative Finance, Taylor & Francis Journals, vol. 10(10), pages 1187-1201.
  • Handle: RePEc:taf:quantf:v:10:y:2010:i:10:p:1187-1201
    DOI: 10.1080/14697680903460176
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    Citations

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    Cited by:

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    2. Pataracchia, B., 2013. "Ambiguity aversion and heterogeneity in financial markets : An empirical and theoretical perspective," Other publications TiSEM bc849a3c-87a4-4718-b049-f, Tilburg University, School of Economics and Management.
    3. 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.
    4. 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.
    5. Xu, Shaojun, 2023. "Behavioral asset pricing under expected feedback mode," International Review of Financial Analysis, Elsevier, vol. 86(C).
    6. 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.
    7. 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.
    8. 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.
    9. Fu, Jie & Zhang, Xiaoqi & Zhou, Wenyuan & Lyu, Yang, 2024. "A continuous heterogeneous agent model for multi-asset pricing and portfolio construction under market matching friction," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 267-283.
    10. Jeffrey (Jun) Chen & Yun Guan & Ivy Tang, 2020. "Optimal Contracting of Pension Incentive: Evidence of Currency Risk Management in Multinational Companies," JRFM, MDPI, vol. 13(2), pages 1-29, February.
    11. Zheng, Min & Wang, Hefei & Wang, Chengzhang & Wang, Shouyang, 2017. "Speculative behavior in a housing market: Boom and bust," Economic Modelling, Elsevier, vol. 61(C), pages 50-64.

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    More about this item

    Keywords

    Econometric analysis; Financial markets; Market fraction model; Microscopic simulation models;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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