On the risk premium in Nordic electricity futures prices

Lucia, Julio J.; Torró, Hipòlit

doi:10.1016/j.iref.2011.02.005

Cited by 50 publications

(70 citation statements)

References 11 publications

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“…Following Haugom and Ullrich (2012), we look at the realized risk premium, ie, the difference between the futures price and the spot price at delivery. This allows us to compare our results with previous studies (see, for example, Botterud et al 2010;Gjolberg and Brattested 2011;Haugom and Ullrich 2012;Lucia and Torró 2011;Weron and Zator 2013). We add to previous research by investigating whether there is evidence of a systematic risk premium in the futures prices, and whether the prices are unbiased predictors of spot price.…”

Section: Introductionmentioning

confidence: 74%

“…In addition, they find no support for the Bessembinder and Lemmon (B&L) model in the data. Several papers arrive at the same conclusion for the B&L model in the Nordic market (see, for example, Botterud et al 2010;Lucia and Torró 2011;Redl et al 2009). Botterud et al (2002) were among the first to provide empirical evidence of a risk premium in the Nordic market.…”

Section: Earlier Findings On the Relationship Between Spot And Futurementioning

confidence: 81%

“…Previous studies analyze the basis (see, for example, Gjolberg and Johnsen 2001;Lucia and Torró 2011;Redl and Bunn 2013). As seen from (3.1), the basis gives information on the expected risk premium in addition to the expected change in the spot price.…”

Section: Ex Ante and Ex Post Risk Premiumsmentioning

confidence: 99%

“…Consequently, such studies may not be comparable. When the realized risk premium is used, as in Lucia and Torró (2011), Gjolberg and Brattested (2011), Haugom and Ullrich (2012) and Weron and Zator (2013), it is assumed that the difference between the expected spot price and realized spot price acts as noise. The realized premium will then equal the sum of the expected risk premium and a noise term:…”

Section: Ex Ante and Ex Post Risk Premiumsmentioning

confidence: 99%

See 3 more Smart Citations

The forecasting power of medium-term futures contracts

Haugom¹,

Hoff²,

Mortensen³

et al. 2014

JEM

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Section: Introductionmentioning

confidence: 74%

Section: Earlier Findings On the Relationship Between Spot And Futurementioning

confidence: 81%

Section: Ex Ante and Ex Post Risk Premiumsmentioning

confidence: 99%

Section: Ex Ante and Ex Post Risk Premiumsmentioning

confidence: 99%

See 2 more Smart Citations

The forecasting power of medium-term futures contracts

Haugom¹,

Hoff²,

Mortensen³

et al. 2014

JEM

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“…The existence of risk premia in the electricity futures prices has been well established empirically in the literature; see, e.g. [20] and [21]. When it comes to a jump risk premium for electricity spot price models, two ideas exist in the literature.…”

Section: Introductionmentioning

confidence: 99%

Electricity futures price models: Calibration and forecasting

Islyaev

Date

2015

European Journal of Operational Research

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A new one factor model with a random volatility parameter is presented in this paper for pricing of electricity futures contracts. It is shown that the model is more tractable than multi-factor jump diffusion models and yields an approximate closed-form pricing formula for the electricity futures prices. On real market data, it is shown that the performance of the new model compares favorably with two existing models in the literature, viz. a two factor jump diffusion model and its jump free version, i.e., a two factor linear Gaussian model, in terms of ability to predict one day ahead futures prices. Further, a multi-stage procedure is suggested and implemented for calibration of the two factor jump diffusion model, which alleviates the difficulty in calibration due to a large number of parameters and pricing formulae which involve numerical evaluation of integrals. We demonstrate the utility of our new model, as well as the utility of the calibration procedure for the existing two factor jump diffusion model, by model calibration and price forecasting experiments on three different futures price data sets from Nord pool electricity data. For the jump diffusion model, we also investigate empirically whether it performs better in terms of futures price prediction than a corresponding, jump-free linear Gaussian model. Finally, we investigate whether an explicit calibration of jump risk premium in the jump diffusion model adds value to the quality of futures price prediction. Our experiments do not yield any evidence that modelling jumps leads to a better price prediction in electricity markets.

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Convenience Yields and Risk Premiums in the EU‐ETS—Evidence from the Kyoto Commitment Period

Trück

Weron

2016

Journal of Futures Markets

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We examine convenience yields and risk premiums in the EU‐wide CO2 emissions trading scheme (EU‐ETS) during the first Kyoto commitment period (2008–2012). We find that the market has changed from initial backwardation to contango with significantly negative convenience yields in futures contracts. We further examine the impact of interest rate levels in the Eurozone, the increasing level of surplus allowances and banking, as well as returns, variance, or skewness in the EU‐ETS spot market. Our findings suggest that the drop in risk‐free rates during and after the financial crisis has impacted on the deviation from the cost‐of‐carry relationship for emission allowances (EUA) futures contracts. Our results also illustrate a negative relationship between convenience yields and the increasing level of inventory during the first Kyoto commitment period, providing an explanation for the high negative convenience yields. Finally, we find that market participants are willing to pay an additional risk premium in the futures market for a hedge against increased volatility in EUA prices. Overall, our results contribute to the literature on the determinants and empirical properties of convenience yields and risk premiums for this relatively new class of assets. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:587–611, 2016

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On the risk premium in Nordic electricity futures prices

Cited by 50 publications

References 11 publications

The forecasting power of medium-term futures contracts

The forecasting power of medium-term futures contracts

Electricity futures price models: Calibration and forecasting

Convenience Yields and Risk Premiums in the EU‐ETS—Evidence from the Kyoto Commitment Period

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