On the threshold hyperbolic GARCH models

Wilson Kwan, Wai Keung Li, Guodong Li

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


In the financial market, the volatility of financial assets plays a key role in the problem of measuring market risk in many investment decisions. Insights into economic forces that may contribute to or amplify volatility are thus important. The financial market is characterized by regime switching between phases of low volatility and phases of high volatility. Nonlinearity and long memory are two salient features of volatility. To jointly capture the features of long memory and nonlinearity, a new threshold time series model with hyperbolic generalized autoregressive conditional heteroscedasticity is considered in this article. A goodness of fit test is derived to check the adequacy of the fitted model. Simulation and empirical results provide further support to the proposed model. AMS 2000 subject classifications: Primary 91B84; secondary 62M10.

Original languageEnglish
Pages (from-to)159-166
Number of pages8
JournalStatistics and its Interface
Issue number2
Publication statusPublished - 2011


  • Hyperbolic garch model
  • Long memory
  • Threshold model
  • Volatility


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