DUBLIN–(BUSINESS WIRE)–The “Financial Evolution: AI, Machine Learning and Sentiment Analysis” conference has been added to ResearchAndMarkets.com’s offering.
This is a sophisticated conference that not only interrogates and explores the implications of AI & ML in the financial services industry but also goes on to identify the investment opportunities of sharing knowledge and exploiting IP in the finance domain.
Artificial Intelligence and Machine Learning (AI & ML) and Sentiment Analysis are said to predict the future through analysing the past – the Holy Grail of the finance sector. They can replicate cognitive decisions made by humans yet avoid the behavioural biases inherent in humans.
Processing news data and social media data and classifying (market) sentiment and how it impacts Financial Markets is a growing area of research. The field has recently progressed further with many new alternative data sources, such as email receipts, credit/debit card transactions, weather, geo-location, satellite data, Twitter, Micro-blogs and search engine results. AI & ML are gaining adoption in the financial services industry especially in the context of compliance, investment decisions and risk management.
Attend this event and earn GARP/CPD credit hours.
The supplier has registered this program with GARP for Continuing Professional Development (CPD) credits. Attending this program qualifies for 7 credit hours. If you are a Certified ERP or FRM, please record this activity in your Credit Tracker.
Learn how you can benefit from the unprecedented progress in technological advances for yourself and your company
Find out about the impact of Quantum Computing and Alternative Data
Benefit from the experience of world class presenters from the UK, US, Europe and India/Hong Kong
Gain exclusive insights into pioneering projects in AI, Machine Learning & Sentiment Analysis in Finance
Programme includes the latest state-of-the-art research, practical applications and case studies
Enjoy excellent networking opportunities throughout the days with all participants, including presenters, investors and exhibitors.
(Previous Programme 2019 (Hong Kong))
08:30 – Coffee & Registration
Morning Chair: Professor Gautam Mitra, CEO, OptiRisk Systems/Visiting Professor, UCL
09:00 – Welcome and Introduction
09:10 – Blowing Bubbles: Quantifying How News, Social Media and Contagion Effects Drive Speculative Manias
Richard Peterson, CEO, MarketPsych
09:45 – Closing the Data Gap in the Artificial Intelligence Age with Semi – Supervised Learning
Sam Ho, CEO, ThinkCol.AI
10:15 – Panel 1: Alternative Data
Moderator: Gautam Mitra, CEO, OptiRisk Systems
10:45 – Coffee
11:15 – Regulation Of Fintech
Katherine Liu, Of Counsel, Stephenson Harwood
11:30 – Application of Generative Adversarial Networks (GANs) in Algorithmic Trading
Mohammad Yousuf Hussain, Data Scientist, Jasmine 22
12:00 – Panel 2: Protecting New Technologies in Finance
Moderator: Jonathan Chu, Partner, Stephenson Harwood
12:30 – Lunch
Afternoon Chair: Xiang Yu, Chief Business Development Officer, OptiRisk Systems
13:30 – Doing Business in Malta
Jennifer Shen May, Investment Promotion, Malta Enterprise
13:45 – Equity Trading Strategy using Sentiment and Technical Indicators
Xiang Yu, Chief Business Development Officer, OptiRisk Systems
14:15 – Technology Innovation for Asset Managers: the journey from traditional to systematic and AI investments
Kevin Kwan, Greater China Lead Financial Model Developer, Bloomberg
14:45 – Panel 3: Impact of AI in Finance
Moderator: Antoine Freches, Senior VP – FICC Trading, Haitong International Securities
15:15 – Tea
15:45 – Business Applications for AI in Finance
Carolina Hoffmann – Becking, Senior Consultant, Ernst & Young
16:15 – Reinforcement Learning and Quantitative Finance
Yifeng Hou, Quantitative Trading Lead, FinFabrik
16:15 – Using Machine Learning Techniques for Quantitative Investment Strategies: A Commodity Case Study
Antoine Freches, Senior VP – FICC Trading, Haitong International Securities
17:15 – Close of conference; Networking Drinks
Quant Research Solutions, CTO Office
Ivailo Dimov is a senior quant at the Bloomberg L.P. CTO Office, where he provides quantitative and data science solutions to management, external and internal clients. He has worked on both traditional derivative, risk and alpha modeling as well as alternative data research. At Bloomberg, he has led projects on market consensus, broker-algo selection, recommendation systems, automated news and news topic modeling. Ivailo is also an Adjunct Professor at the NYU Courant Institute, where he teaches Data Science in Quantitative Finance.
For more information about this conference visit https://www.researchandmarkets.com/r/hvpfhb