Evaluating Multivariate GARCH Models in the Nordic Electricity Markets
نویسندگان
چکیده
منابع مشابه
Semiparametric Multivariate Garch Models
Estimation of multivariate GARCH models is usually carried out by quasi maximum likelihood (QMLE), for which recently consistency and asymptotic normality have been proven under quite general conditions. However, there are to date no results on the efficiency loss of QMLE if the true innovation distribution is not multinormal. We investigate this issue by suggesting a nonparametric estimation o...
متن کاملBidding in sequential electricity markets: The Nordic case
For electricity market participants trading in sequential markets with differences in price levels and risk exposure, coordinated bidding is highly relevant. We consider a Nordic power producer who engages in the day-ahead spot market and the near real-time balancing market. In both markets, clearing prices and dispatched volumes are unknown at the time of bidding. However, in the balancing mar...
متن کاملOn Long-Term Transmission Rights in the Nordic Electricity Markets
In vein with the new energy market rules drafted in the EU this paper presents and discusses two contract types for hedging the risks connected to long-term transmission rights, the financial transmission right (FTR) and the electricity price area differentials (EPAD) that are used in the Nordic electricity markets. The possibility to replicate the FTR contracts with a combination of EPAD contr...
متن کاملRobust M-estimation of multivariate GARCH models
In empirical work on multivariate financial time series, it is common to postulate a Multivariate GARCH model. We show that the popular Gaussian quasi-maximum likelihood estimator of MGARCH models is very sensitive to outliers in the data. We propose to use robust M-estimators and provide asymptotic theory for M-estimators of MGARCH models. The Monte Carlo study and empirical application docume...
متن کاملMultivariate GARCH Models with Correlation Clustering
This paper proposes a new clustered correlation multivariate GARCH model (CCMGARCH) that allows conditional correlations to form clusters. This model can generalize the time-varying correlation structure in Tse and Tsui (2002) by determining a natural grouping of the correlations among the series. To estimate the proposed model, we adopt Markov Chain Monte Carlo methods. Two efficient sampling ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Communications in Statistics - Simulation and Computation
سال: 2006
ISSN: 0361-0918,1532-4141
DOI: 10.1080/03610910500416033