Machine Learning Models for Investment
Dipole Technologies is applying ML models on data sets traditionally overlooked by large investment funds to inform investing decisions.
We believe the key to unlocking the future of investment lies with high-growth companies. As traditional markets in retail and manufacturing continue to slow down, the big question is identifying the disruptive technology companies that are driving the majority of growth in the overall market. Our hypothesis is that young retail investors are more likely to identify these key disruptors compared to institutional investors. By leveraging the power of big data and machine learning, we can use the information found on public forums like Twitter or Reddit to identify promising candidate companies before the market moves.
The Team
Jonathan Chiang, CEO & Co-Founder
University of Toronto
Stewart Foster, Co-CTO & Co-Founder
University of Alberta
Jeffrey Gao, Co-CTO & Co-Founder
University of British Columbia
Umar Rajguru, Lead Engineer
St. Catharines Collegiate