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  • Search: person:"Skare, Øivind"
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Year of publication
Subject
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Ornstein-Uhlenbeck processes 4 exchange rates 4 Stochastic process 2 Stochastischer Prozess 2 Volatility 2 Volatilität 2 factor models 2 financial econometrics 2 indirect inference 2 multivariate stochastic volatility 2 quasi-likelihood 2 state space models 2 state space representation 2 stochastic volatility 2 1989-2010 1 Asymptotic variance 1 Estimation theory 1 Exchange rate 1 Exchange rate data 1 Financial market 1 Finanzmarkt 1 Indirect inference 1 Multi-criteria analysis 1 Multikriterielle Entscheidungsanalyse 1 Norway 1 Norwegen 1 Ornstein-Uhlenbeck process 1 Quasi-likelihood estimation 1 Schätztheorie 1 Simulation study 1 Statistical distribution 1 Statistische Verteilung 1 Stochastic volatility model 1 Time series analysis 1 USA 1 United States 1 Wechselkurs 1 Zeitreihenanalyse 1
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Online availability
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Free 6 Undetermined 3
Type of publication
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Book / Working Paper 6 Article 4
Type of publication (narrower categories)
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Working Paper 4 Arbeitspapier 2 Graue Literatur 2 Non-commercial literature 2
Language
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English 6 Undetermined 4
Author
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Skare, Øivind 9 Raknerud, Arvid 7 Benth, Fred Espen 1 Bølviken, Erik 1 Frigessi, Arnoldo 1 Holden, Lars 1 Host, Gudmund 1 Skare, Oivind 1 Varin, Cristiano 1
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Institution
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Statistisk Sentralbyrå, Government of Norway 2
Published in...
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Computational Statistics & Data Analysis 2 Discussion Papers 2 Discussion Papers / Statistisk Sentralbyrå, Government of Norway 2 Discussion papers / Statistics Norway, Research Department 2 Scandinavian Journal of Statistics 1 Statistics & Probability Letters 1
Source
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RePEc 6 ECONIS (ZBW) 2 EconStor 2
Showing 1 - 10 of 10
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Multivariate stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck processes: A quasi-likelihood approach
Raknerud, Arvid; Skare, Øivind - 2010
This paper extends the ordinary quasi-likelihood estimator for stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck (OU) processes to vector processes. Despite the fact that multivariate modeling of asset returns is essential for portfolio optimization and risk management --...
Persistent link: https://www.econbiz.de/10011968384
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Multivariate stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck processes: A quasi-likelihood approach
Raknerud, Arvid; Skare, Øivind - Statistisk Sentralbyrå, Government of Norway - 2010
This paper extends the ordinary quasi-likelihood estimator for stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck (OU) processes to vector processes. Despite the fact that multivariate modeling of asset returns is essential for portfolio optimization and risk management --...
Persistent link: https://www.econbiz.de/10008488941
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Multivariate stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck processes : a quasi-likelihood approach
Raknerud, Arvid; Skare, Øivind - 2010
Persistent link: https://www.econbiz.de/10003950031
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Indirect inference methods for stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck processes
Raknerud, Arvid; Skare, Øivind - 2009
This paper aims to develop new methods for statistical inference in a class of stochastic volatility models for financial data based on non-Gaussian Ornstein-Uhlenbeck (OU) processes. Our approach uses indirect inference methods: First, a quasi-likelihood for the actual data is estimated. This...
Persistent link: https://www.econbiz.de/10011968371
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Indirect inference methods for stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck processes
Raknerud, Arvid; Skare, Øivind - Statistisk Sentralbyrå, Government of Norway - 2009
This paper aims to develop new methods for statistical inference in a class of stochastic volatility models for financial data based on non-Gaussian Ornstein-Uhlenbeck (OU) processes. Our approach uses indirect inference methods: First, a quasi-likelihood for the actual data is estimated. This...
Persistent link: https://www.econbiz.de/10008556607
Saved in:
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Indirect inference methods for stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck processes
Raknerud, Arvid; Skare, Øivind - 2009
Persistent link: https://www.econbiz.de/10003912053
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Indirect inference methods for stochastic volatility models based on non-Gaussian Ornstein–Uhlenbeck processes
Raknerud, Arvid; Skare, Øivind - In: Computational Statistics & Data Analysis 56 (2012) 11, pp. 3260-3275
An indirect inference method is implemented for a class of stochastic volatility models for financial data based on non-Gaussian Ornstein–Uhlenbeck (OU) processes. First, a quasi-likelihood estimator is derived from an approximative Gaussian state space representation of the OU model. Next,...
Persistent link: https://www.econbiz.de/10011056439
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Pairwise likelihood inference in spatial generalized linear mixed models
Varin, Cristiano; Host, Gudmund; Skare, Oivind - In: Computational Statistics & Data Analysis 49 (2005) 4, pp. 1173-1191
Persistent link: https://www.econbiz.de/10005118342
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Improved Sampling-Importance Resampling and Reduced Bias Importance Sampling
Skare, Øivind; Bølviken, Erik; Holden, Lars - In: Scandinavian Journal of Statistics 30 (2003) 4, pp. 719-737
The sampling-importance resampling (SIR) algorithm aims at drawing a random sample from a target distribution π. First, a sample is drawn from a proposal distribution "q", and then from this a smaller sample is drawn with sample probabilities proportional to the importance ratios π/"q". We...
Persistent link: https://www.econbiz.de/10005195846
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Smoothed Langevin proposals in Metropolis-Hastings algorithms
Skare, Øivind; Benth, Fred Espen; Frigessi, Arnoldo - In: Statistics & Probability Letters 49 (2000) 4, pp. 345-354
The Metropolis Adjusted Langevin Algorithm (MALA) samples from complex multivariate densities [pi]. The proposal density is based on a discretized version of a Langevin diffusion, and is well defined only for continuously differentiable densities [pi]. We propose a modified MALA algorithm when...
Persistent link: https://www.econbiz.de/10005223642
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