Regnard, Nazim and Zakoian, Jean-Michel (2010): A conditionally heteroskedastic model with time-varying coefficients for daily gas spot prices.
Preview |
PDF
MPRA_paper_22642.pdf Download (288kB) | Preview |
Abstract
A novel GARCH(1,1) model, with coefficients function of the realizations of an exogenous process, is considered for the volatility of daily gas prices. A distinctive feature of the model is that it produces non-stationary solutions. The probability properties, and the convergence and asymptotic normality of the Quasi-Maximum Likelihood Estimator (QMLE) have been derived by Regnard and Zakoian (2009). The prediction properties of the model are considered. We derive a strongly consistent estimator of the asymptotic variance of the QMLE. An application to daily gas spot prices from the Zeebruge market is presented. Apart from conditional heteroskedasticity, an empirical finding is the existence of distinct volatility regimes depending on the temperature level.
Item Type: | MPRA Paper |
---|---|
Original Title: | A conditionally heteroskedastic model with time-varying coefficients for daily gas spot prices |
Language: | English |
Keywords: | GARCH; Gas prices; Nonstationary models; Periodic models; Quasi-maximum likelihood estimation; Time-varying coefficients |
Subjects: | C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes |
Item ID: | 22642 |
Depositing User: | Pr. Jean-Michel Zakoian |
Date Deposited: | 11 May 2010 19:05 |
Last Modified: | 26 Sep 2019 15:45 |
References: | Aknouche, A., Bibi, B., 2009. Quasi-Maximum Likelihood Estimation of Periodic GARCH and Periodic ARMA-GARCH Processes. Journal of Time Series Analysis 30, 19--46. Asche, F., Osmundsen, P., Sandsmark, M., 2006. The UK market for natural gas, oil and electricity: Are the prices decoupled? Energy Journal, 27, 27--40. Azrak, R., Mélard, G., 2006. Asymptotic properties of quasi-maximum likelihood estimators for ARMA models with time-dependent coefficients. Statistical Inference for Stochastic Processes 3, 279-330. Bachmeier, L.J., Griffin, J.M., 2006. Testing for market integration : crude oil, coal, and natural gas. The Energy Journal 27, 55--71. Berkes, I., Horv\'ath, L., Kokoszka, P., 2003. GARCH processes: structure and estimation. Bernoulli 9, 201--227. Bibi, A., Francq C., 2003. Consistent and asymptotically normal estimators for time-dependent linear models. Annals of the Institute of Statistical Mathematics, 55, 41--68. Bollerslev, T., 1986. Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics 31, 307--327. Bollerslev, T., Ghysels, E., 1996. Periodic autoregressive conditional heteroskedasticity. Journal of Business and Economic Statistics} 14, 139--151. Engle, R.F., 1982. Autoregressive conditional heteroskedasticity with estimates of the variance of the United Kingdom inflation. Econometrica 50, 987--1007. Francq, C., Gautier, A., 2004a. Large sample properties of parameter least squares estimates for time-varying ARMA models. Journal of Time Series Analysis 25, 765-783. Francq, C., Gautier, A., 2004b. Estimation of time-varying ARMA models with Markovian changes in regime. Statistics and Probability Letters 70, 243-251. Francq, C., Zakoïan, J-M. 2004 Maximum likelihood estimation of pure GARCH and ARMA-GARCH processes. Bernoulli 10, 605-637. Francq, C. and Zakoïan, J-M. 2009. Bartlett's formula for a general class of non linear processes. Journal of Time Series Analysis, 30, 449--465. Hamilton, J.D., 1989. A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica 57, 357--384. Johansen, S., 1988. Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control 12, 231--254. Johansen, S., 1995. Likelihood-based inferencein cointegrated vector autoregressive models. Oxford University Press, Oxford. Koopman, S.J., Ooms, M., Carnero, M.A., 2007. Periodic Seasonal Reg-ARFIMA-GARCH Models for Daily Electricity Spot Prices. Journal of the American Statistical Association 102, 16-27. Kwiatowski, D., Phillips, P.C.B., Schmidt, P., and Shin, Y., 1992. Testing the null hypothesis of stationarity against the alternative of of a unit root: how sure are we that economic time series have a unit root? Journal of Econometrics, 54, 159--178. Panagiotidis, T., Rutledge, E., 2007. Oil and gas markets in the UK: Evidence from a cointegrating approach. Energy Economics 29, 329--347 Regnard, N., Zakoian, J-M. 2009. Structure and estimation of a class of nonstationary yet nonexplosive GARCH models. Discussion paper, Laboratoire FIME. Available at http://www.fime-lab.org/fr/index.php?section=publications. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/22642 |