基于高频数据的LGARCH (1,1)模型的Hausman检验

Hausman tests for LGARCH model

  • 摘要: 本文将基于GARCH模型的Hausman检验推广到一类线性GARCH (LGARCH)模型上,给出了LGARCH (1,1)模型的Hausman检验的具体形式,并进一步将日内高频数据信息引入这些检验中.模拟结果表明,LGARCH (1,1)模型的Hausman检验效果良好.基于上证50指数的实证研究表明,通过引入日内高频数据,可以使得Hausman检验提供更多误差项相关的信息.

     

    Abstract: In this paper, the Hausman tests are applied to linear GARCH-type error models, with the focus on the LGARCH(1, 1) model for simplicity. The specific form of Hausman tests are given for the LGARCH(1, 1) model, and the high frequency data information is further introduced into these tests. The simulation results show that the Hausman tests perform well for the LGARCH(1, 1) model under the daily frequency. Empirical studies based on the SSE 50 Index show that the introduction of intraday high frequency data for Hausman tests can provide more information about the distribution of the error term.

     

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