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Modelling Different Volatility Components in High-Frequency Financial Returns

  • Yuanhua Feng

    ()

    (Department of Mathematics and Statistics, University of Konstanz)

This paper considers simultaneous modelling of seasonality, slowly changing un- conditional variance and conditional heteroskedasticity in high-frequency financial returns. A new approach, called a seasonal SEMIGARCH model, is proposed to perform this by introducing multiplicative seasonal and trend components into the GARCH model. A data-driven semiparametric algorithm is developed for estimating the model. Asymptotic properties of the proposed estimators are investigated brie y. An approximate significance test of seasonality and the use of Monte Carlo confidence bounds for the trend are proposed. Practical performance of the proposal is investigated in detail using some German stock price returns. The approach proposed here provides a useful semiparametric extension of the GARCH model.

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File URL: http://cofe.uni-konstanz.de/Papers/dp02_18.pdf
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Paper provided by Center of Finance and Econometrics, University of Konstanz in its series CoFE Discussion Paper with number 02-18.

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Length: 26 pages
Date of creation: Nov 2002
Date of revision:
Handle: RePEc:knz:cofedp:0218
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  1. Yuanhua Feng, 2002. "Simultaneously Modelling Conditional Heteroskedasticity and Scale Change," CoFE Discussion Paper 02-12, Center of Finance and Econometrics, University of Konstanz.
  2. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  3. Ling, Shiqing & McAleer, Michael, 2002. "NECESSARY AND SUFFICIENT MOMENT CONDITIONS FOR THE GARCH(r,s) AND ASYMMETRIC POWER GARCH(r,s) MODELS," Econometric Theory, Cambridge University Press, vol. 18(03), pages 722-729, June.
  4. Jan Beran & Yuanhua Feng, 1999. "Local Polynomial Estimation with a FARIMA-GARCH Error Process," CoFE Discussion Paper 99-08, Center of Finance and Econometrics, University of Konstanz.
  5. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
  6. He, Changli & Ter svirta, Timo, 1999. "FOURTH MOMENT STRUCTURE OF THE GARCH(p,q) PROCESS," Econometric Theory, Cambridge University Press, vol. 15(06), pages 824-846, December.
  7. Mercurio, Danilo & Spokoiny, Vladimir G., 2002. "Statistical inference for time-inhomogeneous volatility models," SFB 373 Discussion Papers 2002,61, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  8. Jan Beran, 1999. "SEMIFAR Models - A Semiparametric Framework for Modelling Trends, Long Range Dependence and Nonstationarity," CoFE Discussion Paper 99-16, Center of Finance and Econometrics, University of Konstanz.
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