Conference

machineByte Europe 2019

Sep 17–18 2019

Paris, France

machineByte Europe 2019 will be a two-day conference hosted in the centre of Paris on 17-18 September 2019 with a plenary agenda and private breakout sessions that will focus on the key industry topics in machine learning/AI and alternative data.

We have been appointed by global institutional investors to develop this conference to provide not only the theoretical approach to machine learning in investment management, but also case studies/examples of how machine learning can be used in quantitative investment management. Those investors who are currently exploring machine learning and AI by attempting to discover non-linear trends in data, to maximise trade execution and to diversify allocation frameworks. This conference aims to provide education and insights for those institutional investors who are increasingly exploring machine learning in investment management, specifically quantitative investment management.

Our first keynote speaker Mike Tamir, has led teams of Data Scientists in the bay area as Head of Data Science at Uber ATG, Chief Data Scientist for InterTrust and Takt, Director of Data Sciences for MetaScale/Sears, and CSO for Galvanize where he founded the galvanizeU-UNH accredited Masters in Data Science degree and oversaw the company’s transformation from co-working space to Data Science organization.

Keynote speaker

Former Director of Phronesis ML Labs at Uber and Chief Scientist and Head of Machine Learning for Summer School for the Gifted, UC Berkeley Data Science faculty.

NEW KEYNOTE SPEAKER ADDED

Our new academic keynote is Guillaume Coqueret, an associate professor of finance and data science at emlyon business school. His research revolves around applications of numerical methods, especially in financial economics. His work has been published in journals such as Journal of Portfolio ManagementJournal of Banking and Finance and Expert Systems with Applications.

Conference agenda

Day 1

8.30am – 5.30pm

Day 2

8.30am-12.30pm

The agenda will be divided into two sections:

Training and case studies for investors who are new to machine learning and AI and who haven’t explored the use of alternative data yet. With breakout sessions focusing on:

  • Seminar: Python In Investment Management
  • Alternative Data Platform Live Demos – Leveraging Alternative Data In Investment Portfolios

The second section will focus on the experienced investors who would like to connect with peers to talk about specific challenges using machine learning and alternative data. With breakout sessions focusing on:

  • Applying Deep Learning To Factor Portfolios
  • Machine Learning in R

Marriott building

Other agenda topics include:

  • Applying Machine Learning To Quantitative Investment Strategies
  • A Quantitative Approach To ESG Investing Enabled By Machine Learning And Big Data
  • ESG & Sustainable Investing: Using Novel Datasets & Toolkits Through Your Investment Process
  • Can Machine Learning Be Used For Valuation Of Structured Products (Abs, Mbs, Cdo, Clo)?
  • Machine Learning In Alternative Investments
  • Use of Blockchain in Investment Management
  • Slow Growing: Institutionalizing The Crypto Wave

Sponsorship opportunities

The Platinum, Leading Tech Sponsor & Innovation Sponsor package will give the unique opportunity to host a private breakout session with key thought leaders. There are only four private breakout sessions available.

For further information, contact:

Chantal Hermans (chantal@machinebyte.comor Peter Juncaj (peter.juncaj@machinebyte.com).

Agenda highlights from machineByte 2018

Myron Scholes: Big Data Could Restore Faith In Financial Sector

It’s been 10 years since the beginning of the global financial crisis and trust in financial institutions is still in short supply. But according to Myron Scholes — Chief Investment Strategist at Janus Henderson and co-originator of the Black-Scholes options pricing model — big data and artificial intelligence could help restore some faith in the system.

Asset Managers Dig Deep For Granular-Level Data

What do Starbucks’ taxes, programmatic advertising analytics and consumer bank deposits from oil companies all have in common? According to Michael Recce, Chief Data Scientist at Neuberger Berman, all three are examples of unique alternative data sets that his firm and others are analyzing right now.

Could Impact Investing Be Constrained To Discretionary Accounts?

Investors hoping to incorporate a machine-learning element in their impact-investing strategy may be finding it harder than they anticipated. According to a panel of family office leaders, the strategy’s lack of measurability and longer time horizon could mean it remains within the purview of discretionary managers for years to come.

Quants Consider New Algo Choices, Data Onboarding Challenges

Five quants took to the stage in Half Moon Bay for the final session of machineByte’s 2018 conference. On the agenda: Using old machine-learning models in new applications, strategic recommendations for learning more from the data and predictions on the future of consolidation in the industry.

Alt Data Pros Highlight New Applications, Vendor Concerns

Alternative data proved a hot topic at machineByte 2018, with several industry experts sharing their latest successes and failures in the space. Most agreed that new alternative data applications provide value to asset managers but cautioned that practitioners shouldn’t expect the tools to solve all of their problems.

Secular Shift From Tech- To Data-Focus Could Drive Alpha Generation

Alternative data could drive alpha generation over the next 10 years, with investment markets experiencing a secular shift away from tech-oriented investing strategies, according to one panelist.

 


Asset owner registration

Lead sponsors

  • Ravenpack logo

Gold sponsors

  • CME Group logo