We crowdsource equity investment ideas from a group of decentralized users. Users post detailed write-ups and our NLP models learn representations of successful investment theses.
Machine learning models employ various financial and valuation metrics in order to evaluate the underlying value of each company. We use these models to learn traditional value investing heuristics and to discover new theories about long-term investment processes.
Users in the community provide responses and votes to each write-up. Models weigh in user opinion, behavior, and credibility to make predictions from the wisdom of the crowd. Users should be compensated for their contributions.
“Use machine learning to take data and do something that is better than what the humans are doing. Take human crowdsourced data and compute something new.”Eric Schmidt