2nd Annual Quantitative Modelling in Commodity Markets 2021 | Marcus Evans Group | 19 April 2021 | London, UK

Build capability for advanced quantitative techniques such as machine learning for improved data cleaning, correlation and scenario modelling in the commodities markets

Why You Should Attend?
Energy and Commodity Trading firms are looking to apply advanced quantitative techniques and machine learning to increase data supply and to ensure effective usability of this supply. Applying machine learning and AI in the energy and commodity trading market would also allow for accurate and more efficient risk management and trading decisions. Currently the use of machine learning and AI is in its infancy, there are certain stages to which it is being deployed, and some use cases in the market. With this in mind, this marcus evans conference will look to build capability for advanced quantitative techniques and analytics such as machine learning for improved data cleaning, correlation and scenario modelling in the commodities market.

Key Topics:
• Centrica explore how best to utilise alternative data sources and enrich datasets using advanced quantitative techniques
• Citi discuss the development of advanced quantitative techniques to model future unforeseen black swan events
• EDP explore the reliability of utilising alternative market data through AI
• RWE npower utilise advanced techniques of data visualisation to strengthen data correlations and build accurate model parameters

2021 Speakers

George Levy
Quantitative Analyst and Developer, RWE nPower

Nazim Osmancik
Chief Risk Officer, Centrica

Dario Ghazi
Director of Trading, Pricing and Business Intelligence, iSupply Energy

Valentina Fogli
Head of Methodologies and Performance Analysis, Eni gas e Luce

Mario Dell脱ra
VP Market Risk Senior Manager, Commodities, Team Quant Model Validation, Citi

Roberto Medina
Lead Data Scientist, EDP

Vlatka Komaric
Head of Quantitative Risk Management, Axpo

Uwe Vramming
Head of Fundamental Analysis, Vattenfall