Journal of Guangxi Normal University(Natural Science Edition) ›› 2021, Vol. 39 ›› Issue (4): 68-78.doi: 10.16088/j.issn.1001-6600.2020091601

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Daily GARCH Model Estimation Using High Frequency Data

LI Lili1, ZHANG Xingfa1,2*, LI Yuan1,2, DENG Chunliang1   

  1. 1. School of Economics and Statistics, Guangzhou University, Guangzhou Guangdong 510006, China;
    2. Lingnan Research Institute of Statistical Science, Guangzhou University, Guangzhou Guangdong 510006, China
  • Revised:2020-10-10 Online:2021-07-25 Published:2021-07-23

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Abstract: This paper studies the daily GARCH model estimation by introducing the intraday high frequency data. Existing results assume that the constant term in GARCH equation is given, which restricts the extensive applications of the method. In this paper, based on the framework of GARCH(1, 1) model, two estimators for all model parameters, together with the according asymptotic properties, are discussed. A criterion is given to choose the optimal volatility proxy. Simulation studies show that the estimators have smaller asymptotic standard deviation and the empirical study gives a specific application.

Key words: GARCH model, intraday high frequency data, quasi maximum likelihood estimation

CLC Number: 

  • O212.1
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