Human vs algorithm decision-making in power trading: finding the right balance
The growth of algorithmic trading has drastically transformed the way power markets are traded. Automated systems are now key in generating signals,
-
-
P&L attribution in power trading: separating skill from luck
Profit and loss in electricity trading is rarely driven by a single factor. Strong portfolio performance can be attributed to accurate forecasting,
-
Power price scenarios as the key to sound investment decisions
The energy transition is no longer just a political goal - it is an investment market. From solar and wind parks to storage solutions and hydrogen
-
Battery trading strategies: optimising dispatch across wholesale and ancillary markets
Batteries are touted as one of the key technologies that will help us transition to a flexible energy grid. The energy industry can utilise batteries firstly
-
Machine learning for power price forecasting: what works and what doesn’t
Machine learning (ML) has become a widely discussed tool in power trading, often seen as a way to achieve more accurate price forecasts and automate
-
Portfolio positioning using forward curves: from signals to strategy
The core concept of portfolio positioning using forward curves is identifying when a market features prices higher in the current market or in the future
-
Fuel switching and carbon prices: when gas displaces coal in the generation stack
Generation economics change with EUA movements, so it's key that traders can highlight cross-commodity trading signals when they occur. One key process
-
Governance and decision-making in power trading portfolios
Modern electricity trading portfolios navigate increasingly complex environments, making the field both challenging and exciting. It's a fascinating
-
Decarbonisation and long-term power pricing dynamics
Carbon pricing dynamics have been designed to help reach global decarbonisation goals efforts and they have a considerable effect on trading strategies as a