Fundamental and speculative shocks, what drives electricity prices?

In the paper, Structural Vector Autoregressive models (SVAR) are used to identify fundamental and speculative shocks, in the UK electricity market. The structural shocks are identified via short run restrictions, which are imposed on the matrix of instantaneous effects. In the research, two main types of shocks are considered: fundamental shocks, which result from unexpected changes of demand, supply and generation costs and speculative shocks, which are associated solely with electricity prices. The results indicate that speculative shocks play an important role in the price setting process. Although they account for a significant part (from 30% to 95%) of the price volatility, I do not find evidence that the influence differs between peak and off-peak hours. When fundamental shocks are considered, some dependence between their effects on electricity prices and periods of the day is confirmed. For example, the impact of wind supply shocks on electricity prices is significantly stronger during the peak hours than during the off-peak hours. Moreover, the supply shocks become a major source of electricity price volatility during the peak hours. Finally, it is confirmed that shocks associated with generation costs (prices of fuels) don't have any instantaneous effect on the electricity prices.

[1]  Olivier J. Blanchard,et al.  The Dynamic Effects of Aggregate Demand and Supply Disturbances , 1988 .

[2]  C. Hirschhausen,et al.  First evidence of asymmetric cost pass-through of EU emissions allowances: Examining wholesale electricity prices in Germany , 2008 .

[3]  Helmut Ltkepohl,et al.  New Introduction to Multiple Time Series Analysis , 2007 .

[4]  Risk-adequate pricing of retail power contracts , 2011 .

[5]  R. Weron,et al.  Forecasting spot electricity prices: A comparison of parametric and semiparametric time series models , 2008 .

[6]  C. Sims Are forecasting models usable for policy analysis , 1986 .

[7]  Jakub Nowotarski,et al.  Merging quantile regression with forecast averaging to obtain more accurate interval forecasts of Nord Pool spot prices , 2014, 11th International Conference on the European Energy Market (EEM14).

[8]  H. Mohammadi,et al.  Electricity prices and fuel costs: Long-run relations and short-run dynamics , 2009 .

[9]  C. Harris Electricity Markets: Pricing, Structures and Economics , 2006 .

[10]  A. Eydeland,et al.  Energy and Power Risk Management: New Developments in Modeling, Pricing, and Hedging , 2002 .

[11]  Martin Eichenbaum,et al.  Some Empirical Evidence on the Effects of Shocks to Monetary Policy on Exchange Rates , 1995 .

[12]  M. Obersteiner,et al.  Forecasting electricity spot-prices using linear univariate time-series models , 2004 .

[13]  D. Kirschen,et al.  Fundamentals of power system economics , 1991 .

[14]  R. Weron Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach , 2006 .

[15]  Goran Strbac,et al.  Fundamentals of Power System Economics: Kirschen/Power System Economics , 2005 .

[16]  D. Bunn,et al.  Structural Analysis of Electricity Demand and Supply Interactions , 2010 .

[17]  Derek W. Bunn,et al.  Structural interactions of European carbon trading and energy prices , 2009 .