A k- factor GIGARCH process : estimation and application to electricity market spot prices
Some crucial time series of market data, such as electricity spot prices, exhibit long memory, in the sense of slowly-decaying correlations combined with heteroscedasticity. To e able to model such a behaviour, we consider the k-factor GIGARCH process and we propose two methods to address the related parameter estimation problem. For each method, we develop the asymptotic theory for this estimation.
|Date of creation:||Jul 2004|
|Date of revision:|
|Publication status:||Published in Probabilistic methods applied to power systems, Jul 2004, United States. pp.1 - 7, 2004|
|Note:||View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00188533|
|Contact details of provider:|| Web page: https://hal.archives-ouvertes.fr/|
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- Yin-Wong Cheung & Francis X. Diebold, 1993.
"On maximum-likelihood estimation of the differencing parameter of fractionally integrated noise with unknown mean,"
93-5, Federal Reserve Bank of Philadelphia.
- Cheung, Yin-Wong & Diebold, Francis X., 1994. "On maximum likelihood estimation of the differencing parameter of fractionally-integrated noise with unknown mean," Journal of Econometrics, Elsevier, vol. 62(2), pages 301-316, June.
- Yin-Wong Cheung & Francis X. Diebold, 1990. "On maximum-likelihood estimation of the differencing parameter of fractionally integrated noise with unknown mean," Discussion Paper / Institute for Empirical Macroeconomics 34, Federal Reserve Bank of Minneapolis.
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