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A generalized Schwartz model for energy spot prices — Estimation using a particle MCMC method

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A generalized Schwartz model for energy spot prices — Estimation using a particle MCMC method. / Brix, Anne Floor; Lunde, Asger; Wei, Wei.

I: Energy Economics, Bind 72, 2018, s. 560-582.

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

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@article{d94ac306db3b4e97ac920753dd5092f5,
title = "A generalized Schwartz model for energy spot prices — Estimation using a particle MCMC method",
abstract = "We investigate a large set of energy models that account for the stylized properties in energy prices, especially stochastic volatility and spikes. The models under consideration belong to the class of factor models while our full model features a two-factor price process and a two-component stochastic volatility process. The first factor in the price process captures the normal variations; the second accounts for spikes. The two-component volatility allows for a flexible autocorrelation structure. Instead of using various filtering techniques for splitting the factors, as often found in the literature, we estimate the model in one step using the particle MCMC method. We fit the models to both the spot market and the forward market for UK natural gas. We find that the inclusion of stochastic volatility is crucial for the statistical fit of spot prices whereas the spikes are important for explaining forward prices.",
keywords = "ELECTRICITY, Energy prices, Forward prices, INFERENCE, JUMP DIFFUSION, MARKET PRICE, Multi-factor model, RISK, SIMULATION, Spikes, Stochastic volatility",
author = "Brix, {Anne Floor} and Asger Lunde and Wei Wei",
year = "2018",
doi = "10.1016/j.eneco.2018.03.037",
language = "English",
volume = "72",
pages = "560--582",
journal = "Energy Economics",
issn = "0140-9883",
publisher = "Elsevier BV",

}

RIS

TY - JOUR

T1 - A generalized Schwartz model for energy spot prices — Estimation using a particle MCMC method

AU - Brix, Anne Floor

AU - Lunde, Asger

AU - Wei, Wei

PY - 2018

Y1 - 2018

N2 - We investigate a large set of energy models that account for the stylized properties in energy prices, especially stochastic volatility and spikes. The models under consideration belong to the class of factor models while our full model features a two-factor price process and a two-component stochastic volatility process. The first factor in the price process captures the normal variations; the second accounts for spikes. The two-component volatility allows for a flexible autocorrelation structure. Instead of using various filtering techniques for splitting the factors, as often found in the literature, we estimate the model in one step using the particle MCMC method. We fit the models to both the spot market and the forward market for UK natural gas. We find that the inclusion of stochastic volatility is crucial for the statistical fit of spot prices whereas the spikes are important for explaining forward prices.

AB - We investigate a large set of energy models that account for the stylized properties in energy prices, especially stochastic volatility and spikes. The models under consideration belong to the class of factor models while our full model features a two-factor price process and a two-component stochastic volatility process. The first factor in the price process captures the normal variations; the second accounts for spikes. The two-component volatility allows for a flexible autocorrelation structure. Instead of using various filtering techniques for splitting the factors, as often found in the literature, we estimate the model in one step using the particle MCMC method. We fit the models to both the spot market and the forward market for UK natural gas. We find that the inclusion of stochastic volatility is crucial for the statistical fit of spot prices whereas the spikes are important for explaining forward prices.

KW - ELECTRICITY

KW - Energy prices

KW - Forward prices

KW - INFERENCE

KW - JUMP DIFFUSION

KW - MARKET PRICE

KW - Multi-factor model

KW - RISK

KW - SIMULATION

KW - Spikes

KW - Stochastic volatility

UR - http://www.scopus.com/inward/record.url?scp=85047067277&partnerID=8YFLogxK

U2 - 10.1016/j.eneco.2018.03.037

DO - 10.1016/j.eneco.2018.03.037

M3 - Journal article

AN - SCOPUS:85047067277

VL - 72

SP - 560

EP - 582

JO - Energy Economics

JF - Energy Economics

SN - 0140-9883

ER -