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Quantitative Modelling in Commodity Markets

23-25 September 2019
London Marriott Hotel Canary Wharf, United Kingdom

What are some of the keys areas in which Artificial Intelligence (AI) technologies such as machine learning (ML) are impacting commodity markets?

AI and ML are changing the world around us. Energy sector and commodity trading are no exception. AI and ML entered into various applications. In oil and gas, learning algorithms are enabling more optimal asset operations and maintenance. In energy trading, renewables have been disruptive due to intermittency close to actual delivery. Algorithms and automated trading systems help optimise balancing and manage market price exposure. This is facilitating the successful integration of renewables into the energy market, as balancing has already become too complex to be managed manually. We are also seeing applications on the demand side, including in the industry, data centres, and increasingly in homes. What is common across these applications is that ML methods are used to enhance the quality and speed of our understanding of what is going on, forecasting what may happen next, and choosing the optimal response.

How do you begin to improve the accuracy of your forecasts?

Forecasting accuracy will be increasingly important in trading and optimisation as we bring more intermittent renewable energy online in the coming decades. Organisations will have to adopt a systematic approach in acquiring, evaluating and improving the forecasts they use for business decisions across their operations. This is the very first step. Within this framework, the performance requirements for each forecast need to be defined. In other words, accuracy needs to be defined and measured before it can be improved.

What are some of the biggest challenges when applying machine learning and AI?

There is a variety of challenges. One of the challenges is around adoption. Although packaged software solutions are now widespread, AI&ML are fairly complex concepts and specialist knowledge is required. Leaders and decision-makers need to understand the opportunities these technologies can unlock as well as the limitations and risks. Another challenge is around the availability of good “training” data. Without appropriate data, these algorithms cannot “learn” very well and come up with biased outputs. This is a key point as the benefits of these technologies can only be realised after they are appropriately “trained”. The real value to the user will be in what is learned, rather than the algorithms which are already well-developed and widely available open source.

Outside of AI and machine learning, what are the key disruptors in the commodity markets at the moment?

Commodity markets are being disrupted by several mega trends. The first one is decarbonisation of our economy to minimise adverse effects on the climate. This will change the energy mix and subsequently the trading volumes and flows of various energy and other commodities. The second one is the decentralisation of energy supply. The ascent of on-site distributed energy, emergence of IoT, and digitalisation of data are disrupting the business models built around traditional large centralised supply. The third one is about how technology is enabling energy customers to be actively involved in the marketplace. Customers increasingly want more insight and control over their energy use and they can derive economic benefits from doing so. This is facilitated by smart meters and sensors, which are already in their billions and growing rapidly. Centrica alone has sold nearly 2.5 million smart thermostats and other types of sensors under its Hive brand. In this rapidly changing and increasingly complex landscape AI & ML technologies are both disruptors and enablers of change, unlocking new business opportunities.

What would you like to achieve by attending the marcus evans Quantitative Modelling in Commodity Markets Conference?

I would like to attend the conference to learn from and share my own insights with the group of industry experts who will be there. In particular, I am looking forward to hearing about the latest challenges the organisations in our industry are facing and how they are applying quantitative modelling to develop optimal solutions. I also see it as a great networking opportunity and look forward to meeting new people.

An interview with:

Nazim Osmancik, VP & Group Head of Economics and Fundamentals, Centrica Plc.

Trading houses and financial institutions are searching for a competitive edge to stay relevant in the business, frequently that edge is being found in AI techniques, either replacing or being used in combination with the traditional methods of modelling. The key now is to ensure you understand where, how, and which AI techniques will improve your risk management and forecasting models in commodity markets, account for intermittency of renewables and improve your volatility and correlation models.

This marcus evans event will assess how commodity trading firms are utilising AI, ML and data science to enhance risk forecasting and modeling of their commodities in order to gain a competitive edge.

To view the Conference Agenda, click HERE! 

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We would be delighted to provide you with more information on the conference agenda.  Please fill in your details below and we will be in touch.

Nazim Osmancik (Naz) leads Centrica’s global market analysis and price forecasting team since 2011. He is a senior executive with extensive experience in commodity research and market analysis, strategy, hedging, trading, transaction support. Throughout his career, Naz applied quantitative analysis, econometrics, and AI/machine learning methods to solve complex business problems, generate commercial insights, and maximise performance. Prior to Centrica he held various positions in consulting firms including IPA, PwC, and ICFi. He is a regular contributor to industry conferences and publications.

To view the Conference Agenda, click HERE! 

For all enquiries regarding speaking, sponsoring and attending this conference contact:

Yiota Andreou
Email: Yiotaa@marcusevanscy.com
Telephone: +357 22849 404
Fax: +357 22 849 394