19 - 21 October, 2020
Palais des Congrès de Paris
Focus Day - 19 October 2020
Monday, October 19th, 2020
2:05 PM Panel Discussion - What are the new industry initiatives that are driving improvements in data quality?
With the sheer amount of data and variety of sources being applied by investment and trading teams, data quality is paramount to ensure successful integration, analysis and application of this data. Discover how a leading hedge fund, two European asset managers, a leading European agency broker and the CAIA Association, the global organisation committed to education and professionalism in alternative investments, are collaborating to ensure data standardisation across the whole industry.
- What are the data transformation strategies that have successfully reshaped business models and can effectively handle the growing volumes of data now being consumed?
- How are new priorities in data governance improving data quality and what does this look like within an asset manager?
- How are all stakeholders across the trading ecosystem working together to ensure consistency and improved quality of data?
- Advancements in data security and firm wide platforms- what has this enabled concerning trust in data sources and use?
Day One - 20 October 2020
Tuesday, October 20th, 2020
3:25 PM Panel - How to get the most value from alternative data sources and translate it into actionable information
- How to best find the risk angle in new data sources
- How to best catch this data then build an effective machine model through effective signals
- What are the best strategies for tweaking base point data patterns to get more from your data?
- How to build signals around current asset markets
- How to best work with alternative data providers and assess the quality of the data
- How to look around the noise and find value from more granular information
Day Two - 21 October 2020
Wednesday, October 21st, 2020
9:05 AM Fire Side Chat – To what extent do you need to leverage machine learning and artificial intelligence techniques to make a real impact in your front office and how can you best overcome the common pitfalls to get it right first time?
Outside of the technology sector, financial services is the biggest spender on AI services and this only looks to continue. Witness two of the biggest asset managers by AUM, two leading European brokers and the 4th largest exchange in Europe disclose how they are leveraging AI and ML to advance execution and algorithmic trading.
- Where is robotic process automation (RPA) successfully being used and how does this compare to the needs/requirements of the front office?
- To what extent is it beneficial and when does it start to be detrimental?
- What is really working from a performance and execution standpoint?
- How to overcome the bottlenecks of implementation such as cost and infrastructure limitations?