Machine Learning Toronto
Sessions will cover machine learning models, recent trends in machine learning and its application to quantitative finance, risk and portfolio construction.
This two day training course will provide delegates with an in-depth understanding of machine learning applications. This course will be a technical look at machine learning and provide suggestions and strategies for integrating it within your organization.
The multi-tutor format will provide attendees with an understanding of key theory, models, and more advanced tools in machine learning solutions through a quantitative approach that will also consider portfolio construction, trading, risk management and other business areas.
Who Should Attend
Relevant deparments may include:
- Machine Learning
- Portfolio Management
- Asset Allocation
- Data Science
- Financial Engineering
- Quantitative Analytics
- Quantitative Modelling
- Infrastructure and Technology
What Will You Learn?
- Best practice approaches to machine learning applications in finance from a quantitative viewpoint
- The capabilities of machine learning tools in portfolio construction, trading, risk management and beyond
- Insight into the big data revolution and the building blocks of machine learning tools in finance
- The theory behind machine learning, deep learning and neural networks, and how these methods can be applied in your organization
- A clear new of ML/AI capabilities, how they can help you solve problems more effectively and drive your business forward
- Future opportunities, regulatory expectations and the evolving landscape of ML
Director of Quantitative Research
Natixis Investment Management
Executive Director, Quantitative Analytics Group
Amit Srivastav, is an Executive Director in Morgan Stanley and manages the Quantitative Analytics Group (QAG) in Internal Audit which is responsible for independent assessment of model risk across the Firm including continuous monitoring, risk assessments, testing and reporting of model risk. Prior to Morgan Stanley, Amit was at Bank of America for 12 year career where he spent different roles as the Head of the Market and Counterparty Credit Risk audit functions, Model Risk audit team and in model validation. Amit has a MS in Mechanical Engineering and MBA from CUNY, NY. He also has a certificate in Statistics from Carnegie Mellon and is a CFA Charterholder.
Turing Technology Advisors Inc
Johannes van de Wetering
Head of Quantitative Risk, Capital Markets Risk Management
Johannes van de Wetering is Head of Quantitative Risk for Capital Markets Risk Management, responsible for providing CIBC with the development, implementation, and maintenance of financial models to ensure effective pricing and risk measurement in meeting the demands of changing global and domestic regulations.
On top of his regular duties Johannes is tasked with building new capabilities in Risk Management, utilizing Artificial Intelligence and Machine Learning, to leverage data and analytics. In a previous role he was Head of Data Science, providing AI/ML solutions to the entire enterprise ranging from Capital Markets to Retail. He is experienced in unlocking value in customer data as well as trading data.
Before CIBC Johannes spent a decade in the London hedge fund industry as a fund manager, risk manager and options trader. Most recently he was fund manager for Partner Capital in Mayfair, trading systematic FX. His first role on the buy-side was as a Senior Portfolio Manager trading Volatility in all asset classes for ABP/APG, one of the world's largest pension funds. Before that he was Head Quant on the Swaps desk for Deutsche Bank in Tokyo.
Johannes started his finance career in New York in Swaps, Credit Derivatives and MBS, worked on the Mortgage desk at Salomon Brothers and was Head Quant for Sanwa New York. He earned a Ph.D. in Physics from Princeton University.
VP Trading Products, Data Science Lead
Head of Content and Location Services, DNA
Arthur Berrill is the Head of Content and Location Services at the Royal Bank of Canada. He has a charter to research, design and guide the use of content and specifically location intelligence across all departments of the bank.
Arthur is a founding board member of the Location Forum that develops best practices and guidelines in the use of location data and technology. Arthur is also the chair of the CRCSI Research Investment Committee, a board responsible for guiding research directions and funding in spatial analytics and applications of spatial technology. And Arthur is a member of the TECTERRA Advisory Committee providing evaluations and guidance on the direction of funded geomatics research and innovation projects.
Arthur has almost 40 years of experience in the architecture, design and development of enterprise spatial systems including WILDMAP (a GIS before the term existed), SYSTEM 9, SpatialWare®, MapInfo products and Location Hub®. He holds numerous key patents in the location intelligence and spatial systems domain.
Fascinated by the use of new technology to solve business challenges, Arthur is working on new or improved algorithms and methods borrowed from other disciplines (such as genetics, deep learning), reinvented for modern architectures (such as massively parallel, share nothing) or imposed on the spatial disciplines by the evolution of technology (such as big data and spatial federation).
Prior to RBC, Arthur led the location intelligence initiative at Scotiabank and before then was president of DMTI Spatial. Arthur was Inventor of the Year for 2008 at Pitney Bowes (MapInfo) and won the TechAmerica 50th Anniversary Innovation Award in 2009.
Arthur is a graduate with Honours from the University of Queensland and did his postgraduate work at the International Institute of Aerial Survey and Earth Sciences in the Netherlands.
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