Asymmetric impacts of fundamentals on the natural gas futures volatility: An augmented GARCH approach

Ergen, Ibrahim; Rizvanoghlu, Islam

doi:10.1016/j.eneco.2016.02.022

Cited by 42 publications

(13 citation statements)

References 30 publications

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“…The empirical distribution of lprice has also heavy tails reflecting rare observations scattered farther from the mean. For these reasons we do not consider normal distribution as done, for example, in [6][7][8][9]. Our decision is consistent with [10], which highlights that there is ample evidence that data do not follow normal distribution.…”

Section: Introductionmentioning

confidence: 75%

The Impact of Regulatory Reforms on Demand Weighted Average Prices

Tashpulatov

2021

Mathematics

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Average prices are popularly used in the literature on price modeling. Calculating daily or weekly prices as an average over hourly or half-hourly trading periods assumes the same weight ignoring demand or traded volumes during those periods. Analyzing demand weighted average prices is important if producers may affect prices by decreasing them during low-demand periods and increasing them during high-demand periods within a day. The prediction of this price manipulation might have motivated the regulatory authority to introduce price caps not only on annual average prices but also on annual demand weighted average prices in the England and Wales wholesale electricity market. The dynamics of demand weighted average prices of electricity has been analyzed little in the literature. We show that skew generalized error distribution (SGED) is the appropriate assumption for model residuals. The estimated volatility model is used for evaluating the impact of regulatory reforms on demand weighted average prices during the complete history of the England and Wales wholesale electricity market.

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Section: Introductionmentioning

confidence: 75%

The Impact of Regulatory Reforms on Demand Weighted Average Prices

Tashpulatov

2021

Mathematics

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“…Indeed, when assuming SGED, we find that the value of the log-likelihood function was the highest compared to GED and normal distribution (Table 5). However, normal distribution is still used frequently (e.g., [21,22]) even when there is ample evidence that data or model residuals do not follow normal distribution [23].…”

Section: Discussionmentioning

confidence: 99%

Modeling and Estimating Volatility of Day-Ahead Electricity Prices

Tashpulatov

2021

Mathematics

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We model day-ahead electricity prices of the UK power market using skew generalized error distribution. This distribution allows us to take into account the features of asymmetry, heavy tails, and a peak higher than in normal or Student’s t distributions. The adequacy of the estimated volatility model is verified using various tests and criteria. A correctly specified volatility model can be used for analyzing the impact of reforms or other events. We find that, after the start of the COVID-19 pandemic, price level and volatility increased.

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“…Ergen and Rizvanoghlu [21] augmented the standard GARCH models with the natural gas market fundamentals in order to isolate the sources of high volatility in natural gas futures prices. Lin, Jiang, Xiao & Zhou [22] proposed a novel hybrid forecast model to forecast crude oil price by considering the long memory, asymmetric, heavy-tail distribution, nonlinear and non-stationary characteristics of crude oil price.…”

Section: Liu and Shimentioning

confidence: 99%

Benefit of GARCH Multivariate Models: Application to the Energy Market

Amrani

Zeghdoudi

2021

AJPAS

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This article presents the advantages of multivariate GARCH models. Multivariate GARCH models are identified as the best and flexible models in econometrics. Also, the interest of these models is to be able to examine and analyze the various relations which the various series maintain between them. In order to be able to estimate several financial series to analyze their correlations and transfers of volatility. We present an application on the relationship between the existing volatility in the oil market and the energy market, which we found that the assembly performance of the BEKK-GARCH form is better than that of other models.

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Asymmetric impacts of fundamentals on the natural gas futures volatility: An augmented GARCH approach

Cited by 42 publications

References 30 publications

The Impact of Regulatory Reforms on Demand Weighted Average Prices

The Impact of Regulatory Reforms on Demand Weighted Average Prices

Modeling and Estimating Volatility of Day-Ahead Electricity Prices

Benefit of GARCH Multivariate Models: Application to the Energy Market

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