In this paper, I examine the potential of mobile alerting services empowering investors to react quickly to critical market events. Therefore, an analysis of short-term (intraday) price effects is performed. I find abnormal returns to company announcements which are completed within a timeframe of minutes. To make use of these findings, these price effects are predicted using pre-defined extern...

This project is focused on the design of price forecasting tools for market operators and for market traders, taking into account the distinct purposes, data availability, and time horizons of the distinct users. Empirical price data from the MISO and RTE have been analyzed. A combined model is developed to forecast MISO day-ahead nodal prices. An ARIMA model is constructed to forecast RTE week...

This paper proposes an Artificial Neural Network (ANN)-based short-term load forecasting technique that considers electricity price as one of the main characteristics of the system load, demonstrating the importance of considering pricing when predicting loading in today’s electricity markets. Historical load data from the Ontario Hydro system as well as pricing information from the neighboring...

 Cost-competitive with petroleum fuels  Long-term stable price for budget forecasting  Made from sustainable, renewable Biomass residuals  Storable and pumpable liquid similar to petroleum fuels  Clean burning fuel without the sulfur and particulates from petroleum fuels  Low greenhouse gas emissions Sustainability issues have become an important part of the supply chain for operati...

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...

In this paper, we study the efficiency of the Chinese wheat and soybeans futures markets and assess the conditions in agricultural commodity futures and cash markets in China. Formal statistical tests are conducted through Johansen's cointegration approach to identify the long-term equilibrium relationship between futures and cash markets. Three different cash prices from Zhengzhou Grain Wholes...

The photonic component industry is a highly innovative industry with a large value chain. In order to ensure the growth of the industry much effort must be devoted to road mapping activities. In such activities demand and price evolution forecasting tools can prove quite useful in order to help in the roadmap refinement and update process. This paper attempts to provide useful guidelines in roa...

energy price forecast is the key information for generating companies to prepare their bids in the electricity markets. however, this forecasting problem is complex due to nonlinear, non-stationary, and time variant behavior of electricity price time series. accordingly, in this paper a new strategy is proposed for electricity price forecast. the forecast strategy includes wavelet transform (wt...