A Holistic Approach to Forecasting Wholesale Energy Market Prices
نویسندگان
چکیده
منابع مشابه
A Holistic Approach to Social Forecasting :
Introduction The goal of this paper is to reflect the theoretical and methodological knowledge and experience gathered during more than ten years of work of the Center for Social and Economic Strategies, Faculty of Social Sciences, Charles University in Prague (CESES) on holistic social forecasts, visions and strategies of the Czech Republic’s development in the contexts of globalization and Eu...
متن کاملMultiple Model Forecasting of Australian Regional Wholesale Electricity Prices
The expertise of electricity load forecasting has developed over decades. Some of the best load forecasting models use this expertise to improve the load forecasting accuracy by splitting the forecasting problem into sub-problems such as for weekend/weekday and peak/off peak. This research is designed to evaluate a method based on boosting algorithms to split the data into sub-problems for pric...
متن کاملSticky prices, inventories, and market power in wholesale gasoline markets
A model with costly adjustment of production and costly inventories implies that wholesale gasoline prices will respond with a lag to crude oil cost shocks. Unlike explanations that rely upon menu costs, imperfect information, or long-term buyer/seller relationships, this model also predicts that futures prices for gasoline will adjust incompletely to crude oil price shocks that occur close to ...
متن کاملMarket-based Approach to Modeling Derivatives Prices
Most classical models for derivatives prices focus on prescribing the time evolution of the underlying stochastic factors. The prices of derivatives are then computed, for example, via the risk-neutral expectations. As markets developed and many derivative contracts became liquidly traded, it appeared necessary, in order to avoid creating arbitrage opportunities and to fully exploit the informa...
متن کاملForecasting Energy Commodity Prices Using Neural Networks
A new machine learning approach for price modeling is proposed. The use of neural networks as an advanced signal processing tool may be successfully used to model and forecast energy commodity prices, such as crude oil, coal, natural gas, and electricity prices. Energy commodities have shown explosive growth in the last decade. They have become a new asset class used also for investment purpose...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Power Systems
سال: 2019
ISSN: 0885-8950,1558-0679
DOI: 10.1109/tpwrs.2019.2921611