Double Threshold GARCHモデルとその株価変化率への応用 : ベイズ統計学を用いたパラメータ推定とモデル選択  [in Japanese] Double Threshold GARCH model and its Application to Individual Stock Price : Bayesian Estimation and Model Selection  [in Japanese]

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Author(s)

Abstract

We apply Double Threshold GARCH (DT-GARCH) models to weekly change rate of Japanese individual stock price(Mitsui Fudosan). For comparison, we apply threshold autoregressive (TAR) model and autoregressive (AR) model, too. After Bayesian estimation, we select DT-GARCH model as most appropriate model by DIC. The estimate of its threshold is of -4.17(%). Then the auto regressive model with GARCH process will change the parameters, if the change rate exceeds the threshold.

Journal

  • Bulletin of the Yamagata University. Social science

    Bulletin of the Yamagata University. Social science 42(2), 17-30, 2012-02

    Yamagata University

Codes

  • NII Article ID (NAID)
    110008902006
  • NII NACSIS-CAT ID (NCID)
    AN00243021
  • Text Lang
    JPN
  • Article Type
    departmental bulletin paper
  • Journal Type
    大学紀要
  • ISSN
    0513-4684
  • NDL Article ID
    023581127
  • NDL Call No.
    Z22-430
  • Data Source
    NDL  NII-ELS  IR 
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