Create and disseminate Knowledge
About AI for Energy Finance (AI4EFin)
Energy finance highlights the interdependency of energy and financial markets. Understanding this relationship and answering the crucial question of how to fuel world economies hunger for energy while decreasing greenhouse gas emission requires a new family of tools that turn the vast amounts of data in the energy finance ecosystem into insights for decision-making and ultimately enhance the efficiency, resilience, and sustainability of energy operations and their financing. AI4EFin speaks to these challenges.
Built around a methodological core, we craft novel machine learning (ML) and artificial intelligence (AI) instruments for pattern extraction, explanation, and forecasting of the high-dimensional, non-stationary, temporal data encountered in energy finance to support decision analysis and risk management. These features include probabilistic models to estimate the full conditional distribution of energy derivative prices and other targets, as well as distributional forecasts to facilitate the applicability of risk management tools. Drawing on the potential outcome framework, we also devise ML/AI instruments that model the causal effect of interventions/shocks on price developments and market outcomes.
These new causal approaches are also meant to guide policy-makers in devising/revising regulatory programs and other market interventions, and facilitate estimating the effectiveness of these interventions.
Energy finance highlights the interdependency of energy and financial markets. Understanding this relationship and answering the crucial question of how to fuel world economies hunger for energy while decreasing greenhouse gas emission requires a new family of tools that turn the vast amounts of data in the energy finance ecosystem into insights for decision-making and ultimately enhance the efficiency, resilience, and sustainability of energy operations and their financing. AI4EFin speaks to these challenges.
Built around a methodological core, we craft novel machine learning (ML) and artificial intelligence (AI) instruments for pattern extraction, explanation, and forecasting of the high-dimensional, non-stationary, temporal data encountered in energy finance to support decision analysis and risk management. These features include probabilistic models to estimate the full conditional distribution of energy derivative prices and other targets, as well as distributional forecasts to facilitate the applicability of risk management tools. Drawing on the potential outcome framework, we also devise ML/AI instruments that model the causal effect of interventions/shocks on price developments and market outcomes.
These new causal approaches are also meant to guide policy-makers in devising/revising regulatory programs and other market interventions, and facilitate estimating the effectiveness of these interventions.
Ai4EFIN
Mission & Objectives
AI4EFin involves design-oriented research to develop a set of new ML/AI methods for energy finance. Each design goal is accompanied by large-scale empirical experimentation to demonstrate the effectiveness of the new instruments vis-a-vis established benchmarks in relevant energy finance use cases related to decision analysis and risk management.
AI4EFin involves design-oriented research to develop a set of new ML/AI methods for energy finance. Each design goal is accompanied by large-scale empirical experimentation to demonstrate the effectiveness of the new instruments vis-a-vis established benchmarks in relevant energy finance use cases related to decision analysis and risk management.
- Objective 1: To provide new ML/AI models for finance and energy market time series
- Objective 2: To build XAI methodology for explaining deep learning-based time series forecasts
- Objective 3: To devise probabilistic ML/AI models for energy finance risk management
- Objective 4: To develop methodology for causal discovery and effect estimation in energy finance
- Objective 5: To create and disseminate knowledge
Passionate – Dedicated – Professional
Meet Our Team of Experts
Introducing the Pioneers Behind Our Success: A Diverse Ensemble of Skilled Professionals and Visionaries
CREATE AND DISSEMINATE KNOWLEDGE
Keysubjects
AI4EFin is a research project developed under and financed by Romania’s National Recovery and Resilience PlanPillar III. Smart, sustainable and inclusive growth, including economic cohesion, jobs, productivity, competitiveness, research, development, and innovation, and a well-functioning internal market with strong small and medium-sized enterprises (SMEs), Component C9/I8.
AI4EFin
Contact
Contact person: Prof. univ. dr. Dan Traian Pele