NCER Working Paper Series

2014

• #103
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  JEL-Codes:

  C32; Q41; Q47

  Keywords:

  Short-term load forecasting, seasonality, intra-day correlation, recursive equation system

  Forecasting day-ahead electricity load using a multiple equation time series approach

  Adam Clements, Stan Hurn and Zili Li

  The quality of short-term electricity load forecasting is crucial to the operation and trading activities of market participants in an electricity market. In this paper, it is shown that a multiple equation time-series model, which is estimated by repeated application of ordinary least squares, has the potential to match or even outperform more complex nonlinear and nonparametric forecasting models. The key ingredient of the success of this simple model is the eective use of lagged information by allowing for interaction between seasonal patterns and intra-day dependencies. Although the model is built using data for the Queensland region of Australia, the methods are completely generic and applicable to any load forecasting problem. The model's forecasting ability is assessed by means of the mean absolute percentage error (MAPE). For day-ahead forecast, the MAPE returned by the model over a period of 11 years is an impressive 1.36%. The forecast accuracy of the model is compared with a number of benchmarks including three popular alternatives and one industrial standard reported by the Australia energy market operator (AEMO). The performance of the model developed in this paper is superior to all benchmarks and outperforms the AEMO forecasts by about a third in terms of the MAPE criterion.

• #102
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  JEL-Codes:

  C22; G10; G13; G14

  Keywords:

  Information flow; Volatility; Oil futures; Gold futures; Trading activity.

  The impact of information flow and trading activity on gold and oil futures volatility

  Adam Clements and Neda Todorova

  There is a long history of research into the impact of trading activity and information on financial market volatility. Based on 10 years of unique data on news items relating to gold and crude oil broadcast over the Reuters network, this study has two objectives. It investigates the impact of shocks in trading activity and traders positions which are unrelated to information flows on realized volatility. Additionally, the extent to which the volume of the information flow as well as the sentiment inherent in the news affects volatility is also examined. Both the sentiment and rate of news flow are found to influence volatility, with unexpected positive shocks to the rate of news arrival, and negative shocks to the sentiment of news flow exhibiting the largest impacts. While volatility is also related to measures of trading activity, their influence decreases after news is accounted for indicating that a non-negligible component of trading is in response to public news flow. After controlling for the level of trading activity and news flow, the net positions of the various types of traders play no role, implying that no single group of traders lead to these markets being more volatile.

• #101
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  JEL-Codes:

  C22; G00

  Keywords:

  Realized volatility; diffusion; jumps; point process; Hawkes process; forecasting

  The role in index jumps and cojumps in forecasting stock index volatility: Evidence from the Dow Jones index

  Adam Clements and Yin Liao

  Modeling and forecasting realized volatility is of paramount importance. Previous studies have examined the role of both the continuous and jump components of volatility in forecasting. This paper considers how to use index level jumps and cojumps across index constituents for forecasting index level volatility. In combination with the magnitude of past index jumps, the intensity of both index jumps and cojumps are examined. Estimated jump intensity from a point process model is used within a forecasting regression framework. Even in the presence of the diffusive part of total volatility, and past jump size, intensity of both index and cojumps are found to significantly improve forecast accuracy. An important contribution is that information relating to the behaviour of underlying constituent stocks is useful for forecasting index level behaviour. Improvements in forecast performance are particularly apparent on the days when jumps or cojumps occur, or when markets are turbulent.

• #100
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  JEL-Codes:

  C23; C51; L94; Q41

  Keywords:

  Smooth transition, binary choice model, logit model, electricity spot prices, peak loading pricing, price spikes

  A Smooth Transition Logit Model of the Effects of Deregulation in the Electricity Market

  A S Hurn, Annastiina Silvennoinen and Timo Terasvirta

  The paper proposes and develops a smooth transition logit (STL) model that is designed to detect and model situations in which there is structural change in the behaviour underlying the latent index from which the binary dependent variable is constructed. The maximum likelihood estimators of the parameters of the model are derived along with their asymptotic properties and a Lagrange Multiplier test of the null hypothesis of linearity in the underlying latent index. The development of the STL model is motivated by the desire to assess the impact of deregulation in the Queensland electricity market by addressing the question of whether or not increased competition has resulted in changes in the behaviour of the spot price of electricity, specifically with respect to the well documented phenomenon of periodic abnormally high prices or price spikes. In testing this conjecture the STL model allows the timing of any change to be endogenously determined and also market participants' behavior to change gradually over time. The main results reported in the paper provide clear evidence in support of the structural change in nature and duration of price spikes in Queensland. The endogenous dating of the structural change by the STL model agrees with the institutional detail surrounding the process of deregulation and indicates that the full effect of the policy change took about a year to occur. Notwithstanding the fact that the STL model was specifically developed to tackle a problem couched in an Australian institutional framework this research will be of general interest and applicability. In particular, it is applicable to any situation in which the impact and dating of policy changes is required and where the outcome of the policy is naturally measurable as a binary variable.