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Electricity price forecasting is an inherently difficult problem due its special characteristics and has been an especially challenging to model. Neural networks are increasingly used to attack the problem and in this series we'll delve we start with an introduction to Machine Learning, will then look at the models and finally build our own.
Choosing the appropriate process for modelling energy prices is essential to calculate value, risk and hedging for energy derivatives and assets. The best choice of which price process to is especially vexing in the energy sector since energy spot prices are particularly difficult to model when compared to other asset classes. This post takes a formula free first step into modelling energy spot processes