Accurate electricity price forecasting is a formidable challenge for market participants and managers owing to high volatility of the electricity prices. Price forecasting is also the most important management goal for market participants since it forms the basis of maximizing profits. This study investigates the performance of a novel neural network technique called Extreme Learning Machine (E...

This research evaluated forecasting accuracy of hedonic price models based on a number of different submarket assumptions. Using home sale data for the City of Knoxville and vicinities merged with geographic information, we found that forecasting housing prices with submarkets defined using expert knowledge and by school district and combining information conveyed in different modeling strategi...

This survey reviews a dynamic multi-asset framework in which heterogeneous agents with multi-period planning horizons interact. This framework distinguishes between temporary equilibrium maps describing the basic market mechanism of an asset market, forecasting rules which model the way in which expectations are formed, and a model for exogenous random perturbations. Perfect forecasting rules w...

The aim of this study is to test the ability yield curve on US government bonds forecast future evolution in prices commodities often used as raw materials. We consider monthly nine for more than 30 years. Our findings, confirmed by several parametric and non-parametric tests, are robust indicate that performance changes over time. Specifically, between 1986 early 2000s was quite successful for...

Forecasting markets are a promising approach for predicting future events. The basic idea of a forecasting market is to trade virtual stocks whose final value is tied to a particular future event. The market prices can then be interpreted as predictions of the probability of those future events. The results of recent studies on forecasting markets are encouraging. However, various design issues...

This paper contains short term monthly forecasts of crude oil prices using compumetric methods. Compumetric forecasting methods are ones that use computers to identify the underlying model that produces the forecast. Typically, forecasting models are designed or specified by humans rather than machines. Compumetric methods are applied to determine whether models they provide produce reliable fo...

Load forecasting is a central integral process in the planning and operation of electric utilities. Load forecasting has become in recent years one of the major areas of research in electrical engineering. The main problem for the planning is the determination of load demand in the future. Because electrical energy cannot be stored appropriately, correct load forecasting is very essential for t...

The imbalance market is very volatile and often exhibits extreme price spikes. This makes it hard to model; however, if predicted correctly, one could make significant gains by participating on the right side of market. In this manuscript, we conduct a short-term probabilistic forecasting prices, contributing scarce literature in novel subject. performed 30 min before delivery, so that trader m...