Machine Learning in Finance 2018

Topics

• Classical and advanced models
• Where the industry currently stands with regards to machine learning applications in finance from a quantitative viewpoint
• Modern data analysis - structured and unstructured data and new models
• Capabilities of machine learning tools in portfolio construction, trading, risk management and beyond
• Challenges related to data infrastructure and technology

Who should Attend

Attendees with responsibilities in:

• Portfolio Management
• Machine Learning
• Data Science
• Asset Allocation
• Quantitative Analytics
• Financial Engineering
• Innovation
• Quantitative Modelling
• Infrastructure and Technology
• Forecasting