Portmanteau Test for ARCH-Type Models by Using High-Frequency Data

被引：0
|
作者：
Chen, Yanshan [1 ,3 ]
Zhang, Xingfa [1 ]
Deng, Chunliang [2 ]
Liu, Yujiao [1 ]
机构：
[1] Guangzhou Univ, Sch Econ & Stat, Guangzhou 510006, Peoples R China
[2] Jiaying Univ, Sch Math, Meizhou 514015, Peoples R China
[3] Guangzhou Univ, Guangdong Higher Educ Mega Ctr, Univ City Campus,230 Waihuan Xi Rd, Guangzhou 510006, Peoples R China
来源：
AXIOMS | 2024年 / 13卷 / 03期
关键词：
portmanteau test; high-frequency data; ARCH; QMLE; statistic; CONDITIONAL HETEROSCEDASTICITY; GARCH;
D O I：
10.3390/axioms13030141
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
The portmanteau test is an effective tool for testing the goodness of fit of models. Motivated by the fact that high-frequency data can improve the estimation accuracy of models, a modified portmanteau test using high-frequency data is proposed for ARCH-type models in this paper. Simulation results show that the empirical size and power of the modified test statistics of the model using high-frequency data are better than those of the daily model. Three stock indices (CSI 300, SSE 50, CSI 500) are taken as an example to illustrate the practical application of the test.
引用
收藏
页数：20
相关论文
共 50 条
  • [11] UNIT ROOT TEST WITH HIGH-FREQUENCY DATA
    Laurent, Sebastien
    Shi, Shuping
    [J]. ECONOMETRIC THEORY, 2022, 38 (01) : 113 - 171
  • [12] Composite quantile regression for GARCH models using high-frequency data
    Wang, Meng
    Chen, Zhao
    Wang, Christina Dan
    [J]. ECONOMETRICS AND STATISTICS, 2018, 7 : 115 - 133
  • [13] Bayesian comparison of bivariate ARCH-type models for the main exchange rates in Poland
    Osiewalski, J
    Pipien, M
    [J]. JOURNAL OF ECONOMETRICS, 2004, 123 (02) : 371 - 391
  • [14] Dynamical models of high-frequency data analysis
    Lim, Gyuchang
    Kim, Soo Yoo
    Kang, Ji-Hyun
    Kim, Kyungsik
    [J]. COMPUTER PHYSICS COMMUNICATIONS, 2007, 177 (1-2) : 187 - 187
  • [15] DENSITY FORECASTS OF CRUDE-OIL PRICES USING OPTION-IMPLIED AND ARCH-TYPE MODELS
    Hog, Esben
    Tsiaras, Leonidas
    [J]. JOURNAL OF FUTURES MARKETS, 2011, 31 (08) : 727 - 754
  • [16] Forecasting high-frequency financial data with the ARFIMA-ARCH model
    Hauser, MA
    Kunst, RM
    [J]. JOURNAL OF FORECASTING, 2001, 20 (07) : 501 - 518
  • [17] ARCH-GARCH approaches to modeling high-frequency financial data
    Podobnik, B
    Ivanov, PC
    Grosse, I
    Matia, K
    Stanley, HE
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2004, 344 (1-2) : 216 - 220
  • [18] A rank test for the number of factors with high-frequency data
    Kong, Xin-Bing
    Liu, Zhi
    Zhou, Wang
    [J]. JOURNAL OF ECONOMETRICS, 2019, 211 (02) : 439 - 460
  • [19] Estimating latent variables and jump diffusion models using high-frequency data
    Jiang, George J.
    Oomen, Roel C. A.
    [J]. JOURNAL OF FINANCIAL ECONOMETRICS, 2007, 5 (01) : 1 - 30
  • [20] Forecasting Using High-Frequency Data: A Comparison of Asymmetric Financial Duration Models
    Zhang, Qi
    Cai, Charlie X.
    Keasey, Kevin
    [J]. JOURNAL OF FORECASTING, 2009, 28 (05) : 371 - 386
12345