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Modelling the spreading process of extreme risks via a simple agent-based model: Evidence from the China stock market

Author

Listed:
  • Dinghai Xu

    (Department of Economics, University of Waterloo)

  • Jingru Ji

    (Department of Finance, East China University of Science and Technology)

  • Donghua Wang

    (Department of Finance, East China University of Science and Technology)

Abstract
This paper focuses on investigating financial returns' extreme risks, which are defined as the negative log-returns over a certain threshold. A simple agent-based model is constructed to explain the behavior of the market traders when extreme risks occur. We consider both the volatility clustering and the heavy tail characteristics when constructing the model. Empirical study uses the China securities index 300 daily level data and applies the method of simulated moments to estimate the model parameters. The stationarity and ergodicity tests provide evidence that the proposed model is good for estimation and prediction. The goodness-of-fit measures show that our proposed model fits the empirical data well. Our estimated model performs well in out-of-sample Value-at-Risk prediction, which contributes to the risk management.

Suggested Citation

  • Dinghai Xu & Jingru Ji & Donghua Wang, 2018. "Modelling the spreading process of extreme risks via a simple agent-based model: Evidence from the China stock market," Working Papers 1806, University of Waterloo, Department of Economics, revised 09 Jan 2018.
    • Handle: RePEc:wat:wpaper:1806
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    References listed on IDEAS

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    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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