Event detail

Name: The 3rd Machine Learning & AI in Quantitative Finance Conference

From: 20 Mar 2019

To: 22 Mar 2019

Address: London, United Kingdom

Organizer: WBS Training

Key speakers: Saeed Amen, Founder, Thalesians Ltd Youssef Elouerkhaoui, Global Head of Credit Quant Analysis, CITIGROUP Mandie Quartly, Manager, IBM Miquel Alonso, Executive Director, UBS Paul Bilokon, Senior Quantitative Consultant, BNP Paribas Alexei Kondratyev, Managing Director Financial Markets, Standard Chartered Bank Ignacio Ruiz, Founder & CEO, MoCaX Intelligence Claudi Camps, Deep Learning Specialist, ABN AMRO Clearing Bank N.V. Grant Fuller, Co-founder and CEO, Blue Lion Research Arun Verma, Quantitative Researcher, Bloomberg LP William McGhee, Global Head of Quantitative Analytics, NatWest Markets Artur Sepp, Manager, Julius Baer Georgios Papaioannou, Trading Strategist, Bank of America Merrill Lynch Jan Novotny, Front Office Quant, Thalesians Alison Lowndes, Artificial Intelligence DevRel, NVIDIA Harsh Prasad, Vice President, Morgan Stanley Tomaso Aste, Professor of Complexity Science, University College London Inder Singh, Vice President, CitiBank

Web page: https://www.wbstraining.com/events/the-3rd-machine-learning-ai-in-quantitative-finance-conference/

Pricing: - variable

Description: Workshop Wednesday 20th March:


Main Conference Topics include:

Derivatives Pricing & Modelling with a Machine Learning Approach
Inherent States of Markets
Identification and Forecast of Market Regimes using Machine Learning
Model Calibration with Machine Learning
Who Cares about the Platform?? (Spoiler alert – you should)
Fuelling the Artificial Intelligence Revolution with Gaming
Unsupervised Learning for Information Compression to Improve Performance and Reduce Training Time and Hardware Requirements of Multi-Task Learning
Quantum Machine Learning
Machine Learning for Trading & Hedging Strategies
Digital Transformation to Optimise the Trading Floor: Automatic Booking and Smart Algorithms
Big Data and Machine Readable News to Trade Markets
Quantitative Factor Investing Using Alternative Data and Machine Learning
From Artificial Intelligence to Machine Learning, From Logic to Probability
Deep Learning in Finance: Prediction of Stock Return with Long Short-Term Memory Networks
Deep learning of Investor Behaviour and Risk Appetite


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