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Analysis of long-term natural gas contracts with vine copulas in optimization portfolio problems

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Abstract

In Europe gas is sold according to two main methods: long-term contract (LTCs) and hub pricing. Europe is moving towards a mix of long term and spot markets, but the eventual outcome is still unknown. The fall of the European gas demand combined with the increase of the US shale gas exports and the rise of Liquefied Natural Gas availability on international markets have led to a reduction of the European gas hub prices. On the other side, oil-indexed LTCs failed to promptly adjust their positions, implying significant losses for European gas mid-streamers that asked for a re-negotiation of their existing contracts and obtained new contracts linked also to hub spot prices. The debate over the necessity of the oil-indexed pricing is still on-going. The supporters of the gas-indexation state that nowadays the European gas industry is mature enough to adopt hub-based pricing system. With the aim of analyzing this situation and determining whether oil-indexation can still be convenient for the European gas market, we consider both spot gas prices traded at the hub and oil-based commodities as possible underlyings of the LTCs. We investigates the dependence risk and the optimal resource allocation of the underlying assets of a gas LTC through pair-vine copulas and portfolio optimization methods with respect to five risk measures. Our results show that European LTCs will most likely remain indexed to oil-based commodities, even though a partial dependence on spot hub prices is conceded.

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Notes

  1. See http://www.eia.gov/dnav/ng/hist/rngwhhdd.htm.

  2. The liquidity of a gas hub can be defined as the ratio between the total volume of trade on the hub and the volume of gas consumed in the area served by the hub.

  3. Copula family type: 0 = Independence copula; 1 = Gaussian copula; 2 = Student-t copula (t-copula); 3 = Clayton copula; 5 = Frank copula; 13 = Rotated Clayton copula (180 degrees); 14 = Rotated Gumbel copula (180 degrees); 16= Rotated Joe copula (180 degrees).

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Acknowledgements

We are grateful to the Editor and the anonymous referees for valuable comments. The work of the author M.E. De Giuli has been partially supported by MIUR, Italy, PRIN MISURA 2010RHAHPL. E. Allevi and G. Oggioni are grateful to the UniBS H&W Project “Brescia 20-20-20” for the financial support.

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Correspondence to G. Oggioni.

A Appendix: Additional results

A Appendix: Additional results

See Figs. 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19.

Fig. 5
figure 5

Log returns (a), 30-days horizon rolling standard deviation on log returns (b), and volatility (c) associated with the Brent series

Fig. 6
figure 6

Log returns (a), 30-days horizon rolling standard deviation on log returns (b), and volatility (c) associated with the Gasoil series

Fig. 7
figure 7

Log returns (a), 30-days horizon rolling standard deviation on log returns (b), and volatility (c) associated with the JetF series

Fig. 8
figure 8

Log returns (a), 30-days horizon rolling standard deviation on log returns (b), and volatility (c) associated with the Naphtha series

Fig. 9
figure 9

Log returns (a), 30-days horizon rolling standard deviation on log returns (b), and volatility (c) associated with the Lsfo series

Fig. 10
figure 10

Log returns (a), 30-days horizon rolling standard deviation on log returns (b), and volatility (c) associated with the Gas HenryHub series

Fig. 11
figure 11

ACF and PACF of Gas NBP log return series

Fig. 12
figure 12

ACF and PACF of Brent (a), Gasoil (b), and JetF (c) log return series

Fig. 13
figure 13

ACF and PACF of Naphtha (a), Lsfo (b), and Gas HenryHub (c) log return series

Fig. 14
figure 14

ACF and PACF of Gas NBP residuals

Fig. 15
figure 15

ACF and PACF of Brent (a), Gasoil (b), and JetF (c) residuals

Fig. 16
figure 16

ACF and PACF of Naphtha (a), Lsfo (b), and Gas HenryHub (c) residuals

Fig. 17
figure 17

ACF of the squared mean adjusted log return series and ACF of the squared mean adjusted residuals of Gas NBP log return series

Fig. 18
figure 18

ACF of the squared mean adjusted log return series and ACF of the squared mean adjusted residuals of Brent (a), Gasoil (b), and JetF (c) log return series

Fig. 19
figure 19

ACF of the squared mean adjusted log return series and ACF of the squared mean adjusted residuals of Naphtha (a), Lsfo (b), and Gas HenryHub (c) log return series

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Allevi, E., Boffino, L., De Giuli, M.E. et al. Analysis of long-term natural gas contracts with vine copulas in optimization portfolio problems. Ann Oper Res 274, 1–37 (2019). https://doi.org/10.1007/s10479-018-2932-x

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