Risk premium in the UK natural gas forward market

Haff, Ingrid Hobæk; Lindqvist, Ola; Løland, Anders

doi:10.1016/j.eneco.2007.12.002

Cited by 17 publications

(6 citation statements)

References 21 publications

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“…In addition, these results indicate that 1 and 2 months futures contracts during Phase 1 are biased predictors, while for 3 months futures (Phase 1) as well as 2 and 3 months (Phase 2) contracts the restrictions on the slope coefficient ( ) is rejected such that no long-run biasedness relationship can be identified. Overall, this finding is in line with Hobaeck-Haff et al (2008) who identified a time-varying risk premium in the UK natural gas forward markets. and are the normalized cointegrating parameters from the Vector Error Correction model (standard errors are reported in parenthesis).…”

Section: Empirical Results On the Unbiasedness Of Futures Pricessupporting

confidence: 80%

“…Second, futures prices are biased predictors in the long-and short-run and, thus, the joint hypothesis of unbiasedness and risk neutrality has to be rejected. This finding is in line with several seminal studies ; ; Wei & Zhu (2006); Cartea & Williams (2008);Hobaeck-Haff et al (2008). Third, we highlight that past information is relevant to forecast future prices, and, thus, the information incorporated in futures contracts can be used to speculate on future spot price levels.…”

Section: Empirical Results On the Unbiasedness Of Futures Pricessupporting

confidence: 71%

“…More specifically, results argue (at least in most cases) in favor of the existence of a risk premium. This is consistent with results, for example, from and Hobaeck-Haff et al (2008). Moreover, we illustrated that past information is relevant to forecast future prices and, thus, should be incorporated to increase the predictive performance of the model.…”

Section: Discussionsupporting

confidence: 76%

“…For natural gas forward contracts at HH, Wei & Zhu (2006) find that forward contracts are biased predictors of future spot prices and conclude that there exists a time-varying risk premium. For Europe Hobaeck-Haff et al (2008) find that prices of forward contracts ranging from one to five months and spot prices are cointegrated and that forward prices are biased predictors of the future spot price. Furthermore, they find a significant positive risk premium inherent in UK natural gas forward markets at the National Balancing Point (NBP).…”

Section: Introductionmentioning

confidence: 99%

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Predictive Performance and Bias: Evidence from Natural Gas Markets

Kremser¹,

Rammerstorfer²

2017

JMS

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This paper sheds light on the differences and similarities in natural gas trading at the National Balancing Point in the UK and the Henry Hub located in the US. For this, we analyze traders' expectations and implement a mechanical forecasting model that allows traders to predict future spot prices. Based on this, we compute the deviations between expected and realized spot prices and analyze possible reasons and dependencies with other market variables. Overall, the mechanical predictor performs well, but a small forecast error remains which can not be characterized by the explanatory variables included.

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Section: Empirical Results On the Unbiasedness Of Futures Pricessupporting

confidence: 80%

Section: Empirical Results On the Unbiasedness Of Futures Pricessupporting

confidence: 71%

Section: Discussionsupporting

confidence: 76%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Predictive Performance and Bias: Evidence from Natural Gas Markets

Kremser¹,

Rammerstorfer²

2017

JMS

View full text Add to dashboard Cite

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“…However, there are many various factors affecting the price dynamics of the natural gas. Existing literatures, including Cartea and Williams (2008), Haff et al (2008), Bunn and Chen (2013), and Lin and Duan (2007), document that the price of natural gas is affected by the seasonal variation. Like the general commodity, the price of natural gas extracted is subject to the forces of demand and supply which tend to push the transaction price back to its long term average, giving it mean reversion characteristics (Schwartz 1997;Pindyck 2001;Tang 2012).…”

Section: Introductionmentioning

confidence: 99%

The affine styled-facts price dynamics for the natural gas: evidence from daily returns and option prices

Hsu

Chen

Lin

et al. 2016

Rev Quant Finan Acc

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This study analyzes affine styled-facts price dynamics of Henry Hub natural gas price by incorporating the price features of jump risk, and seasonality within stochastic volatility framework. Affine styled-facts dynamics has the advantage of being able to incorporate mean reversion (MR), stochastic volatility (SV), seasonality trends (S), and jump diffusion (J) in a standardized inclusive framework. Our main finding is that models that incorporate jumps significantly improve overall out-of-sample option pricing performance. The combined MRSVJS model provides the best fit of both daily gas price returns and the related cross section of option prices. Incorporating seasonal effects tend to provide more stable pricing ability, especially for the long-term option contracts.

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A robust model of the convenience yield in the natural gas market

Volmer

2010

Journal of Futures Markets

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This study advances the research on the convenience yield of natural gas. Econometric models confirm that air temperature is an important explanatory variable in addition to storage levels. Furthermore, an extended linear model shows that one has to account for a changing cost of physical storage in the spirit of Brennan (1958). Besides this, an alternative regime-switching model for the convenience yield helps to put in perspective a prominent finding by Fama, and French (1987). That is, given binding capacity constraints for gas storage, the variance of the futures' basis will increase rather than decrease with the storage levels. Finally and most importantly, robustness tests demonstrate that the extended linear model produces the most viable forecasts and that these forecasts can help to amend the performance of reduced-form models for the gas spot price.transparency increase are now on the agenda. One fact underpinning the rising interest in standardized contracts is the recent start of gas trading at two main energy exchanges in this region. In July 2007, the German EEX (European Energy Exchange) launched its gas trading platform and less than a year later, in May 2008, the Scandinavian Nord Pool followed suit. Further support can be found by looking at the traded volumes of gas contracts on the emerging continental marketplaces: APX Group (Amsterdam Power Exchange), the most liquid gas trading place on the mainland, reported a volume increase of 74% in gas contracts for delivery at the Dutch gas hub TTF and a 16-fold increase in volumes for the Belgian hub Zeebrugge. 1 Along with the importance of exchange-traded gas grows the necessity to find accurate pricing models for the different contracts, and this regularly requires a future spot price. One notable difference between commodities and stocks or bonds is that the current spot price is not directly observable in the market. During the last few decades, a number of general commodity pricing models have been developed and tested. However, the application to natural gas pricing was predominantly tested using reduced-form models such as the well-known two-factor models in Gibson and Schwartz (1990), Schwartz (1997), and Schwartz and Smith (2000). As opposed to equilibrium models, these models build on an exogenously specified stochastic process rather than demand and supply conditions founded in microeconomic theory. They are easily tractable and also capture typical phenomena of the forward curve (e.g. the Samuelson effect 2 ), but they do not offer fundamental economic explanations for the predicted prices.The lack of insight into the real price drivers is a downside of pure reduced-form models because the risk of misspecification is high and the outof-sample performance can be poor. With respect to the Schwartz and Smith model, Carlson, Khokher, and Titman (2007) show that given frictional production adjustments in the oil and gas market, the model will systematically overestimate the prices for oil and gas options. Similarly, Ribeiro and Hodges (200...

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Risk premium in the UK natural gas forward market

Cited by 17 publications

References 21 publications

Predictive Performance and Bias: Evidence from Natural Gas Markets

Predictive Performance and Bias: Evidence from Natural Gas Markets

The affine styled-facts price dynamics for the natural gas: evidence from daily returns and option prices

A robust model of the convenience yield in the natural gas market

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