THE NORMAL INVERSE GAUSSIAN DISTRIBUTION AND SPOT PRICE MODELLING IN ENERGY MARKETS

By Fred Espen Benth, J. Saltyte-Benth. 2004

108 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/3765dfac2bace09481ecc0e50db8a566f4910d8d

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Citations in the corpus

Stochastic Modeling of Wind Derivatives in Energy Markets (2018, methodology): “, Benth et al. (2008); or Tankov and Cont (2004). Therefore, an NIG process cannot be correlated with a Brownian motion, as this is a continuous process.”
Stochastic Modelling of Temperature Variations with a View Towards Weather Derivatives (2005, methodology): “Following the analysis in Benth and Saltyte-Benth (2003), we specify a sub-family of probability measures using the so-called Esscher transform.”
TIME‐CHANGED ORNSTEIN–UHLENBECK PROCESSES AND THEIR APPLICATIONS IN COMMODITY DERIVATIVE MODELS (2012, background): “The maturity effect implies that long term futures are less volatile than short term futures, and is well documented in the empirical literature (see Bessembinder et al. (1995), Kalev and Duong (2008) and references therein).”
THE STOCHASTIC VOLATILITY MODEL OF BARNDORFF‐NIELSEN AND SHEPHARD IN COMMODITY MARKETS (2010, methodology): “We refer to the works of Benth and Šaltytė-Benth (2004) for using the Schwartz model with NIG-distributed innovations for gas and oil, or Börger et al. (2009) for cross-commodity modeling using exponential NIG-distributed Lévy processes.”
Modelling energy spot prices by volatility modulated Levy-driven Volterra processes (2013, methodology): “In practice, however, one restricts to a parametric class of equivalent probability measures, and the standard choice seems to be given by the Esscher transform, see Benth, Šaltytė Benth and Koekebakker [29], Shiryaev [63].”
The volatility of temperature and pricing of weather derivatives (2007, methodology): “The same conclusions were reached for the Norwegian temperature data analysed by Benth and Šaltyt_ e Benth (2005), and there we suggested modelling 0 500 1000 1500 2000 −0.”
Valuing Volatility and Variance Swaps for a Non‐Gaussian Ornstein–Uhlenbeck Stochastic Volatility Model (2007, methodology): “We construct martingale measures Q using the Esscher transform, following the analysis in Benth and Saltyte-Benth (2004).”