After the success of last year’s conference in Zurich, OptiRisk will be participating and presenting at the 2019 Zurich conference on "Financial Evolution: AI, Machine Learning & Sentiment Analysis". We’re excited to hear more about what the Swiss Finance community is doing in this space and
The biggest event in our annual calendar is set to take place on 25 – 26 June 2019. The London stop of the “Financial Evolution” conference series congregates hundreds of investment professionals all eager to explore deeper into the fields of AI, Machine Learning and Sentiment
Malta’s economy is booming as it strives to become an international finance centre. As a new wave of fintech companies establish themselves on this small island, OptiRisk are also travelling there to unveil our work and find out more about this buzz. In partnership with UNICOM, we will be in Malta to present at the conference as well as attending the workshops on AI and Behavioral Finance, offered by Panthera Solutions.
In 2019, OptiRisk will be returning to Hong Kong again for the third consecutive year. As a Knowledge Partner of the event, we will be showcasing the work we’ve done in sentiment analysis for equities and fixed income. Additionally, we are also looking forward to learning and exploring more about what this financial hub in Asia has to offer in the Fintech space.
To kick off the global series of Finance conferences for 2019, OptiRisk is proud to announce that they will be participating in the upcoming Mumbai conference held at the prestigious location of the National Stock Exchange. This will be OptiRisk’s first time presenting in India’s Finance capital of Mumbai, alongside an array of global experts from institutions such as Yes Bank, IBM and more.
Presentations at this conference explain how Sentiment Analysis, AI and Machine Learning are impacting on and benefiting the Finance Sector; explores the most essential issues at the intersection of research and practice, and demonstrates the latest models and methods, demonstrating how AI and Machine Learning methods can be used to generate investment decisions successfully.
This is the 8th consecutive year that this event has been held in London. It is expected to be a great success with 150+ attendees from 25 different countries and counting. Gautam Mitra, Xiang Yu and Christina Erlwein-Sayer from OptiRisk are all giving presentations, along with Peter Hafez, RavenPack; Pierce Crosby, StockTwits; James Luke, IBM; Richard Peterson, MarketPsych Data; Sanjiv Das, Santa Clara University; Nishant Chandra, AIG Science; Ivailo Dimov, Bloomberg; Dan Joldzic, Alexandria; Technology; Christopher Kantos, Northfield; Jordan Mizrahi, FIRST TO INVEST; Andreas Zagos, Intracom GmbH.
AI, Machine Learning and Sentiment Analysis Applied to – Financial Markets – Retail and Consumer Markets, 13 – 14 March 2018, Bangalore, India
For the second time, OptiRisk are travelling to Bangalore, India for UNICOM’s event. This conference expands the focus of AI and Sentiment Analysis to include Retail and Consumer Markets as well as Financial Markets. OptiRisk will be joined by many international and local experts including Krishma Singla, IBM, Nishant Chandra, AIG, Vijay Srinivas Agneeswaran, SapientRazorFish and Prof. Ashok Banerjee, IIM Calcutta.
As part of our growing interest in the Asian markets, OptiRisk has agreed to speak at this conference: AI and Sentiment Analysis in Finance, Hong Kong. The keynote speakers at this event are Prof. Lei Chen, Hong Kong University of Science and Technology (HKUST) and Johnson Poh, Singapore Management University. Joining them on stage will be Wendy Cheong, Moody’s Investors Service Hong Kong; Mohammad Yousuf Hussain, HSBC and Satoshi Shizume, Financial Technology Research Institute (Japan).
Optimisation technologies have become key tools in making intelligent business decisions and are often adopted in the finance industry. This week-long interactive workshop is entirely presented by OptiRisk experts. Participants learn how to formulate and develop their own optimisation models and how to use state-of-the-art commercial solvers. They will acquire a good knowledge of how to embed optimisation models into applications.