Events > Four Elements Announces Partnership with AI Singapore and NExT++

Four Elements Announces Partnership with AI Singapore and NExT++

31 August, 2018 by Yi Hao Chua

Four Elements announces partnership with AI Singapore and NUS-Tsinghua-Southampton Centre for Extreme Search (NExT++), a joint research center in big unstructured data analytics established by the National University of Singapore, the Tsinghua University of China and the University of Southampton, UK.

The project aims to leverage machine learning techniques to learn and discover relevant knowledge from large scale alternate data sources for the estimation of commodity prices, notably base metals, and their applicability to other markets. Machine learning techniques, in particular deep neural networks, have recently achieved significant success in various real-world applications such as medical image recognition, product recommendation, and user profiling. Specifically, the objective of this project is to build a neural network-based solution for predicting future contract prices of base metals. NExT++ will contribute its expertise in machine learning and unstructured multi-source data analytics and involve students and professors to work alongside Four Elements’ team of quants. The Centre will also be deploying resources such as IT infrastructure for the project. The research will be conducted on the financial data and research platform, Alphien (


The collaboration between Four Elements and NExT++ is through AI Singapore’s 100 Experiments (“100E”) program, where both institutions will jointly develop innovative AI products and solutions for the local industry. AI Singapore is a national program launched by the National Research Foundation to anchor deep national capabilities in artificial intelligence. The 100E program is AI Singapore’s flagship program to solve industries’ artificial intelligence (AI) problem statements and help them build their own AI team.

Four Elements is a Singapore-based commodity fundamental research house with a focus on macro and manages USD 52.1 Mio as of 31st August 2018.