Machine Learning in Quant Finance
Practical examples of how quants are driving machine learning forward by finding uses through data selection, and applying machine learning techniques such as regression and reinforcement learning
12-14 Nov 2018
London, United Kingdom
- Why You Should Attend
Machine Learning in Quant Finance
This marcus evans conference will offer business cases for machine learning to achieve process efficiency and improve analysis through the lens of quants in finance. Industry experts will come together to discuss how quants have acquired large data sets and developed the programming for machine learning with appropriate controls in order to extract meaningful insights for the business.
Using data to make smart business decisions through analysis is nothing new, and is something the leading market players have done to their advantage. But with data increasing in financial institutions, the ability to do this well and use all the factors and information to derive analysis becomes a harder task. Machine learning is stepping in to handle this problem with its ability to form patterns from structured and non-structured data. With this in mind, the march towards machine learning, with all its benefits and solutions it has to offer for optimisation and risk analysis, has been difficult to ignore, and quants are one of the key stakeholders flying the flag for this march. The skill set of quants - considering their experience in statistical analysis, quantum programming and maths - lends itself to driving forward machine learning projects, so it is only natural that financial institutions use existing resourcing to drive forward new projects.
- Key Topics
- Discover how quants are selecting and applying data to machine learning to gain statistical analysis and answers to business problems
- Explore best practices in machine learning techniques with a focus on reinforcement learning and regression
- Validate machine models throughout their programming and continuously test the patterns formed
- Practical examples of how quants have developed machine models and embedded this into the business
- Advance calibration and estimations of models using machine learning methods
- Previous Attendees Include
Bank of England
BNP Paribas Ltd
Daiwa Capital Markets
Federal Reserve Bank of New York
Global Valuation Limited
Lloyds Banking Group
National Australia Bank
Nomura International PLC
Royal Bank Of Canada
VTB Capital PLC
- Why Choose GFMI marcus evans?
marcus evans specialises in the research and development of strategic events for senior business executives. From our international network of 63 offices, marcus evans produces over 1000 event days a year on strategic issues in corporate finance, telecommunications, technology, health, transportation, capital markets, human resources and business improvement.
Above all, marcus evans provides clients with business information and knowledge which enables them to sustain a valuable competitive advantage and makes a positive contribution to their success.
- Practical Insights From
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- Voice of Our Customers
- “Good conference on a different/developing/evolving topic. Please continue to organise this event annually” Quantitative Analytic Manager Wells Fargo
- “It was well-organised and professionally delivered” Quantitative analyst Mizuho
- Join the Discussion
- Event Contact
For all enquiries regarding speaking, sponsoring and attending this conference contact:
PO Box 24797
Telephone: +357 22 849 308
Fax: +357 22 849 394