European natural gas seasonal effects on futures hedging

Martínez, Beatriz; Torró, Hipòlit

doi:10.1016/j.eneco.2015.04.002

Cited by 28 publications

(9 citation statements)

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“…Martínez and Torró (2015) find significant differences during winter and summer seasons in the natural gas basis, spot and futures returns mean and volatility. For example, it has been well recognized that in periods of low stocks, positive demand shocks cannot be absorbed by storage and spot prices are likely to exceed the futures prices (backwardation); conversely, abundant inventories provide a buffering effect against shifts in demand, and the basis is likely to be positive (contango).…”

Section: Performance Under Different Market Conditionsmentioning

confidence: 88%

“…Following Ederington and Salas (2008) and Martínez and Torró (2015) we set Y t equal to the basis, that is F S − t t , as this spread indicates expected future price changes for the spot commodity, if markets are efficient. Following Ederington and Salas (2008) and Martínez and Torró (2015) we set Y t equal to the basis, that is F S − t t , as this spread indicates expected future price changes for the spot commodity, if markets are efficient.…”

Section: Methodsmentioning

confidence: 99%

“…Martínez and Torró (2015) consider seasonality when OHRs are computed in European gas markets. Ederington and Salas (2008) postulate that, when spot prices are partially predictable, traditional regression estimates the OHR inefficiently, leading to upward-biased riskiness levels for both hedged and unhedged positions and downward-biased risk reduction levels.…”

Section: Pouliasis Et Almentioning

confidence: 99%

“…We use data covering the period December 30, 1998 to May 16, 2018; this results in 1,011 weekly (233 monthly) return observations. Therefore, the traditional HE underestimates the risk reduction potential of hedging; in line with Martínez and Torró (2015) or Ederington and Salas (2008). Table 3 presents the NG (Panel A) and NBP (Panel B) IS variance reduction against the unhedged position for weekly and monthly horizons using either the traditional measure of hedging effectiveness HE 1 (Equation (3)) or the Edernigton and Salas (2008) HE 2 (Equation (5)).…”

Section: In-sample (Is) Hedging Performancementioning

confidence: 99%

“…Martínez and Torró (2015) consider seasonality when OHRs are computed in European gas markets. Despite the substantial progress made in developing hedging models, forecast combinations have not been explored.…”

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confidence: 99%

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A novel risk management framework for natural gas markets

Pouliasis

Visvikis

Papapostolou

et al. 2019

Journal of Futures Markets

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This paper examines dynamic hedges in the natural gas futures markets for different horizons and explores the gains from devising risk management strategies. Despite the substantial progress made in developing hedging models, forecast combinations have not been explored. We fill this gap by proposing a framework for combining hedge-ratio predictions. Composite hedge ratios lead to significant reduction in portfolio risk, whether spot prices are partially predictable or not. We offer insights on hedging effectiveness across seasons, backwardation-contango conditions and the asymmetric profiles of long-short hedgers. We conclude that forecast combinations better reconcile realized performance with the hedging process, mitigating model instability. K E Y W O R D S dynamic futures hedging, forecast combination, natural gas J E L C L A S S I F I C A T I O N C32; C53; G11; G32; L95 3Gagnon and Lypny (1995) provide evidence in support of GARCH models. In contrast, Lien and Tse (2002) support the traditional regression approach. GARCH models exhibit few limitations. For example, the observed nonnormalities in return distributions are more pronounced than those implied by GARCH; the model fails to reproduce time variability in higher moments unless explicitly modeled, and a strong degree of persistence is imputed to volatility which may be due to structural breaks (Lamoureux and Lastrapes, 1990). POULIASIS ET AL.| 431 differ for different hedging horizons (weekly and monthly), between long and short hedges, during seasons (winter and summer) and across market conditions (backwardation and contango).Finally, we also assess hedging performance under the supposition of partially predictable spot prices. Ederington and Salas (2008) postulate that, when spot prices are partially predictable, traditional regression estimates the OHR inefficiently, leading to upward-biased riskiness levels for both hedged and unhedged positions and downward-biased risk reduction levels. Martínez and Torró (2015) consider seasonality when OHRs are computed in European gas markets. Their results indicate that hedging effectiveness is much higher when the seasonal pattern in spot price changes is approximated with the basis (futures-spot spread). Fama and French (1987) and Viswanath (1993) also find that the basis is a useful predictor of future changes in spot commodity prices.The structure of this paper is as follows. Section 2 presents the OHR methodology and demonstrates the forecast combination procedure. In Section 3, the data and their properties are described. Section 4 discusses the empirical results and evaluates the hedging effectiveness of the proposed strategies. The reality check for superior hedging ability is also discussed, while this section presents information on weight and hedge ratio stability, transaction costs, performance fees, downside risk and segmentation to market conditions. Last section concludes.How to cite this article: Pouliasis PK, Visvikis ID, Papapostolou NC, Kryukov AA. A novel risk management framework for nat...

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Section: Performance Under Different Market Conditionsmentioning

confidence: 88%