Skip to main content
Log in

Price and volatility interrelationships in the wholesale spot electricity markets of the Central-Western European and Nordic region: a multivariate GARCH approach

  • Original Paper
  • Published:
Energy Systems Aims and scope Submit manuscript

Abstract

This paper examines price and volatility interrelationships in five European, day-ahead, wholesale spot electricity markets. These include the French, German, Belgian and Dutch electricity markets, forming the Central-Western European (CWE) region, as well as the Nord Pool Spot electricity market, a pool market for the Nordic region. For this purpose, a novel VAR model with dummy variables was developed to model the conditional mean price, while the CCC-MGARCH model and a DCC-MGARCH model were used to model volatility. The results suggest that evidence of market integration, as measured by cross-mean spillovers and conditional correlation, do exist in the electricity markets under examination. Nevertheless, they also indicate that the CWE electricity markets are stronger integrated, while, on the other hand, weaker integration is observed between them and the Nordic electricity market. We attribute these findings to the fact that physical interconnection capacity is not sufficient for the electricity markets to become fully integrated.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. Although the EPEX Spot Power Exchange also covers the electricity market of Austria and Switzerland, these two electricity markets do not participate in the market integration mechanism and thus, they are not included in the analysis. On the other hand, the NPS is a pool electricity market, with one common system price for the entire Nordic region (Denmark, Norway, Sweden, Finland, and the Baltic states). This common system price is then adjusted internally to several local market nodes, at which the national electricity markets of the region are divided. The market coupling between the CWE and the Nordic region takes place at the level of this common system price. Thus, this common system price is included in our analysis [34].

  2. A feedback relationship between two price series exists when the dependence coefficient \(\varphi _{ij}^k\), which denotes the linear price dependence between markets i and j, for lag k, is \(\varphi _{ij}^k \ne 0\), while at the same time \(\varphi _{ji}^k \ne 0\) [43, p. 349].

  3. A feedback relationship between two price series i and j exists when the dependence coefficient \(\varphi _{ij}^ \ne 0\), while at the same time \(\varphi _{ji}^ \ne 0\). A unidirectional relationship exists when the dependence coefficient \(\varphi _{ij}^ \ne 0\), but at the same time \(\varphi _{ji}^ =0\) [43, p. 349]. Building on this concept we could consider that a feedback relationship between two price series does not exists when one of \(\varphi _{ij}^k \) or \(\varphi _{ji}^k \) is non-significant. In this case, a unidirectional relationship should be considered.

References

  1. Agency for the Cooperation of Energy Regulators—ACER (2012), http://www.acer.europa.eu. Accessed Dec 2012

  2. Bauwens, L., Laurent, S., Rombouts, J.: Multivariate GARCH models: a survey. J. Appl. Econ. 21, 79–109 (2006)

    Article  MathSciNet  Google Scholar 

  3. Bollerslev, T.: Generalized autoregressive conditional heteroscedasticity. J. Econ. 31(3), 307–327 (1986)

    Article  MathSciNet  MATH  Google Scholar 

  4. Bollerslev, T.: Modeling the coherence in short-run nominal exchange rates: a multivariate generalized arch model. Rev. Econ. Stat. 72(3), 498–505 (1990)

    Article  Google Scholar 

  5. Bunn, W.D., Gianfreda, A.: Integration and shock transmissions across European electricity forward markets. Energy Econ. 32(2), 278–291 (2010)

    Article  Google Scholar 

  6. Bystrom, H.N.E.: The hedging performance of electricity futures on the Nordic power exchange. Appl. Econ. 35(1), 1–11 (2003)

    Article  Google Scholar 

  7. Chan, K.F., Gray, P.: Using extreme value theory to measure value-at-risk for daily spot electricity prices. Int. J. Forecast. 22(2), 283–300 (2006)

    Article  Google Scholar 

  8. Chevalier, J.: Time-varying correlations in oil, gas and CO2 prices: an application using BEKK, CCC and DCC-MGARCH models. Appl. Econ. 44(32), 4257–4274 (2012)

    Article  Google Scholar 

  9. De Vany, A.S., Walls, W.D.: Cointegration analysis of spot electricity prices: insights on transmission efficiency in the western US. Energy Econ. 21(3), 435–448 (1999)

    Article  Google Scholar 

  10. Engle, R.F.: Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica 50(4), 987–1008 (1982)

    Article  MathSciNet  MATH  Google Scholar 

  11. Engle, R.F., Kroner, K.F.: Multivariate simultaneous generalized ARCH. Econ. Theory 11(1), 122–150 (1995)

    Article  MathSciNet  Google Scholar 

  12. Engle R. F., Sheppard, K.: Theoretical and empirical properties of dynamic conditional correlation multivariate GARCH, Working Paper, National Bureau of Economic Research (NBER), Working Paper 8554 (2001)

  13. Engle, R.F.: Dynamic conditional correlation: a simple class of multivariate generalized autoregressive conditional heteroscedasticity. J. Bus. Econ. Stat. 20(3), 339–350 (2002)

    Article  MathSciNet  Google Scholar 

  14. EPEX Spot Power Exchange. Market Coupling Documentation (2012), http://www.epexspot.com/. en/market-coupling. Accessed Dec 2012

  15. European Market Coupling Company—EMCC (2012), http://www.marketcoupling.com. Accessed Dec 2012

  16. Escribano, A., Pena, J., Villaplana, P.: Modeling electricity prices: international evidence. Oxf. Bull. Econ. Stat. 73(5) (2011)

  17. Gonzalo, J., Pitarakis, J.: Lag length estimation in large dimensional systems. J. Time Ser. Anal. 23(4), 401–423 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  18. Hadsell, L., Marathe, A., Shawky, A.: Estimating the volatility of wholesale electricity spot prices in the US. Energy J. 25(4), 23–40 (2004)

    Article  Google Scholar 

  19. Higgs, H.: Modeling price and volatility inter-relationships in the Australian wholesale spot electricity markets. Energy Econ. 31, 748–756 (2009)

    Article  Google Scholar 

  20. Higgs, H., Worthington, C.: Systematic features of high frequency volatility in Australian electricity markets: intraday patterns, information arrival and calendar effects. Energy J. 26(4), 1–19 (2005)

    Article  Google Scholar 

  21. Higgs, H., Worthington, C.: Stochastic price modeling of high volatility, mean-reverting, spike-prone commodities: the Australian wholesale spot electricity market. Energy Econ. 30, 3172–3185 (2008)

    Article  Google Scholar 

  22. Huisman, R., Mahieu, R.: Regime jumps in electricity prices. Energy Econ. 25, 425–434 (2003)

    Article  Google Scholar 

  23. Huisman, R., Kilic, M.: A history of European electricity day-ahead prices. Appl. Econ. 45(18), 2683–2693 (2013)

    Article  Google Scholar 

  24. Haldrup, N., Nielsen, M.O.: A regime switching long memory model for electricity prices. J. Econ. 135(1–2), 349–376 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  25. Kalantzis, G.F., Milonas, T.N.: Analyzing the impact of futures trading on spot price volatility: evidence from the spot electricity market in France and Germany. Energy Econ. 36, 454–463 (2013)

    Article  Google Scholar 

  26. Karolyi, G.: A multivariate GARCH model of international transmissions of stock returns and volatility: the case of the United States and Canada. J. Bus. Econ. Stat. 13(1), 11–25 (1995)

    Google Scholar 

  27. Knittel, R., Roberts, R.: An empirical examination of restructured electricity prices. Energy Econ. 27(5), 791–817 (2005)

    Article  Google Scholar 

  28. Koopman, J., Ooms, M., Carnero, A.: Periodic reg-ARFIMA-GARCH models for daily electricity spot prices. J. Am. Stat. Assoc. 102(477), 16–27 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  29. Ku, Hsu Y., Wang, J.J.: Estimating portfolio value at risk-via-dynamic conditional correlation MGARCH model: an empirical study on foreign exchange rates. Appl. Econ. Lett. 15(7), 533–538 (2008)

    Article  MathSciNet  Google Scholar 

  30. Li, Y., Flynn, P.: Deregulated power prices: comparison of diurnal patterns. Energy Policy 32, 657–672 (2004a)

    Article  Google Scholar 

  31. Li, Y., Flynn, P.: Deregulated power prices: comparison of volatility. Energy Policy 32, 1591–1601 (2004b)

    Article  Google Scholar 

  32. Lindstrom, E., Regland, F.: Modeling extreme dependence between European electricity markets. Energy Econ. 34(4), 899–904 (2012)

    Article  Google Scholar 

  33. Mount, T., Ning, Y., Cai, X.: Predicting price spikes in electricity markets using a regime-switching model with time-varying parameters. Energy Econ. 28(1), 62–80 (2006)

    Article  Google Scholar 

  34. Nord Pool Spot Power Exchange—NPS. The Power Market. (2012), http://www.nordpoolspot.com/How-does-it-work/. Accessed Dec 2012

  35. Robinson, T.: Electricity pool series: a case study in non-linear time series modeling. Appl. Econ. 32(5), 527–532 (2000)

    Article  Google Scholar 

  36. Robinson, T., Baniak, A.: The volatility or prices in the English and welsh electricity pool. Appl. Econ. 34(12), 1487–1495 (2002)

    Article  Google Scholar 

  37. Robinson, T.: The convergence of electricity prices in Europe. Appl. Econ. Lett. 14, 473–476 (2007)

    Article  Google Scholar 

  38. Rubin, O., Babcock, B.: A novel approach for modeling deregulated electricity markets. Energy Policy 39(5), 2711–2721 (2011)

    Article  Google Scholar 

  39. Solibakke, P.: Efficient estimated mean and volatility characteristics for the nordic spot electricity power market. Int. J. Bus. 7(2), 17–35 (2002)

    Google Scholar 

  40. Squicciarini G., Cervigni G., Perekhodtsev D., Poletti, C.: The Integration of the European Electricity markets at a turning point: from the regional model to the third legislative package, Robert Schuman Centre for Advanced Studies—Florence School of Regulation, Working Paper RSCAS 2010/56 (2010)

  41. Tashpulatov, Sh: Estimating the volatility of electricity prices: the case of the England and wales wholesale electricity market. Energy Policy 60, 81–90 (2013)

    Article  Google Scholar 

  42. Thomas, S., Ramiah, V., Mitchell, H., Heaney, R.: Seasonal factors and outlier effects in rate of return on electricity spot prices in Australia’s national electricity market. Appl. Econ. 43(3), 355–369 (2011)

    Article  Google Scholar 

  43. Tsay, R.: Analysis of financial time series, 2nd edn. Wiley, New York (2005)

    Book  MATH  Google Scholar 

  44. Tsay, R.: Multivariate volatility models. IMS Lect. Notes Monogr. Ser. 52, 210–222 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  45. Tse, Y., Tsui, A.: A multivariate autoregressive conditional heteroscedasticity model with time-varying correlations. J. Bus. Econ. Stat. 20(3), 351–362 (2002)

    Article  MathSciNet  Google Scholar 

  46. Worthington, A., Spratley, A., Higgs, H.: Transmission of prices and volatility Australian electricity spot markets: a multivariate GARCH analysis. Energy Econ. 27(2), 337–350 (2005)

    Article  Google Scholar 

  47. Zachmann, G.: Electricity wholesale market prices in Europe: convergence? Energy Econ. 30, 1659–1671 (2008)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kyriaki Kosmidou.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sotiriadis, M.S., Tsotsos, R. & Kosmidou, K. Price and volatility interrelationships in the wholesale spot electricity markets of the Central-Western European and Nordic region: a multivariate GARCH approach. Energy Syst 7, 5–32 (2016). https://doi.org/10.1007/s12667-014-0137-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12667-014-0137-1

Keywords

Mathematics Subject Classification

Navigation