Bunn, Derek, Andresen, Arne, Dipeng Chen, and Westgaard, Sjur
Energy Journal. Jan2016, Vol. 37 Issue 1, p101-122. 22p.
Prices, Market volatility, Risk management in business, Coal sales & prices, and Electricity research
Forecasting quantile and value-at-risk levels for commodity prices is methodologically challenging because of the distinctive stochastic properties of the price density functions, volatility clustering and the importance of exogenous factors. Despite this, accurate risk measures have considerable value in trading and risk management with the topic being actively researched for better techniques. We approach the problem by using a multifactor, dynamic, quantile regression formulation, extended to include GARCH properties, and applied to both in-sample estimation and out-of-sample forecasting of traded electricity prices. This captures the specification effects of mean reversion, spikes, time varying volatility and demonstrates how the prices of gas, coal and carbon, forecasts of demand and reserve margin in addition to price volatility influence the electricity price quantiles. We show how the price coefficients for these factors vary substantially across the quantiles and offer a new, useful synthesis of GARCH effects within quantile regression. We also show that a linear quantile regression model outperforms skewed GARCH-t and CAViaR models, as specified on the shocks to conditional expectations, regarding the accuracy of out-of-sample forecasts of value-at-risk. [ABSTRACT FROM AUTHOR]
Energy Journal. 2010, Vol. 31 Issue 2, p173-198. 26p.
Market volatility, Arbitrage, Interest (Finance), Prices, Corporate profits, Energy consumption, and Electricity
Increases in electricity price volatility have raised interest in electricity storage and its potential arbitrage value. Large utility-scale electricity storage can decrease the value of energy arbitrage by smoothing differences in prices on- and off-peak, however this price-smoothing effect can result in significant external welfare gains by reducing consumer energy costs and generator profits. As such, the incentives of merchant storage operators, consumers, and generators may not be properly aligned to ensure socially-optimal storage use. We examine storage use incentives for these different agent types and show that under most reasonable market structures a combination of merchant and consumer ownership of storage maximizes potential welfare gains from storage use. [ABSTRACT FROM AUTHOR]
This paper investigates the intraday price volatility process in four Australian wholesale electricity markets; namely New South Wales, Queensland, South Australia and Victoria. The data set consists of half-hourly electricity prices and demand volumes over the period January 1, 2002 to June 1, 2003. A range of processes including GARCH, RiskMetrics, normal Asymmetric Power ARCH or APARCH, Student APARCH and skewed Student APARCH are used to model the time-varying variance in prices and the inclusion of news arrival as proxied by the contemporaneous volume of demand, time-of-day, day-of-week and month-of-year effects as exogenous explanatory variables. The skewed Student APARCH model, which takes account of right skewed and fat tailed characteristics, produces the best results in all four markets. The results indicate significant innovation (ARCH effects) and volatility (GARCH effects) spillovers in The conditional standard deviation equation, even with market and calendar effects included. Intraday prices also exhibit significant asymmetric responses of volatility to the flow of information. [ABSTRACT FROM AUTHOR]
Market volatility, Risk, Prices, Electricity, and U.S. states
This paper examines the volatility of wholesale electricity prices for five US markets. Using data covering the period from May 1996 to September 2001, for the California-Oregon Border, Palo Verde, Cinergy, Entergy, and Pennsylvania-New Jersey-Maryland markets, we examine the volatility of electricity wholesale prices over time and across markets. We estimate volatility using a TARCH model to study the differences among markets and the seasonal characteristics of each market. For all markets, we find strong evidence for a downward trend in the ARCH term and a significant negative asymmetric effect over the sample period. We also document important differences among the regional electricity markets not only with respect to wholesale price volatility and seasonal variations, but also with respect to asymmetric properties and persistence of volatility. [ABSTRACT FROM AUTHOR]