How to build a long-term market vision?

As Niels Borh used to say “Prediction is very difficult, especially if it’s about the future”. From elections to pandemics, recent history is littered with forecasting errors. Nevertheless, the exercise remains indispensable, particularly on the energy markets, for those who wish to make an investment or procurement decision, or optimise an asset.

In this article, we provide an overview of thetools available to build a forecast on Futures products, whose price, and therefore variations, are linked to the evolution of a consensus among the various players.

Technical analysis

It consists of the analysis of stock price evolution graphs and various indicators deduced from historical behaviour, in order to evaluate future behaviour. MACD, Bollinger, RSI are among these indicators. It is often criticised for its “self-fulfilling prophecy” side, but it cannot be totally neglected, as it is widely used by market players. Its limits are nevertheless particularly marked in the electricity market, where fundamentals often take over.

At COR-e we use machine learning to replicate these different indicators, in order to offer you a forecast of future price trends.

Modelling

While spot prices can be modelled using deterministic models, long-term price simulation requires a broader approach, using scenarios.

The reliability of the forecast will thus depend on two factors:

• The ability of the model to convert Megawatt to €/MWh, which has to be verified via backtesting on historical data
• The quality and completeness of the scenarios, which require a combination of sector knowledge and data analysis

Different methodologies have proven themselves on the first point, at COR-e we use Machine Learning, which has proven itself with our clients, and we are able to accompany you in the construction of realistic and personalised scenarios on the following elements:

• Evolution of fuel and CO2 prices
• Evolution of installed capacity (renewable, nuclear, coal, gas)
• Changes in consumption (weather scenarios, structural changes)