A Nigerian and a Kenyan are disrupting NewYork City financial markets with their startup called Thinknum.
The two, Gregory Ugwi and Eric Omwega say Thinknum is indexing all of the world’s financial data and making it available on an open platform. The two were inspired by Bloomberg terminal, a real-time financial markets data, news and analytics tool founded by his worship the Mayor Mike Bloomberg.
Ugwi told TechMoran, “The question that inspired us to launch our firm was “How would markets be different if everyone had access to a Bloomberg terminal?”
Ugwi studied Math at Princeton and worked at Goldman Sachs, prior to founding Thinknum. He grew up in Lagos and recorded the highest score in the Nigerian JAMB exams of 2003. His cofounder, Eric Omwega, graduated from Staford Business school earlier this year and currently works for McKinsey. Omwega grew up in Kenya.
Ugwi told TechMoran, “Our data is currently being adopted by academics at an accelerating pace, as shown by Francis Smart on R-Bloggers
. We have work to do in order to achieve our mission but we are gaining traction with a more mainstream audience everyday.”
“Traditionally investors have relied on wall street analysts for projections of companies intrinsic values but with our new tool
, individuals can easily build their own models. Unlike Wall street analysts who typically do not disclose the models being used to arrive at their buy, sell or hold recommendations, Thinknum allows our users to view and change any formula or assumption that drives the final valuation,” Ugwi added.
Ugwi then let us to Google DCF 3 Statement Model,
an example of a model he built recently for valuing Google’s stock. To get started all a user needs is a ticker.
The strategists operating in the intersection of mathematics, computer science and the social sciences, say this finanical analysis engine brings the functionality traditionally found on a wall street proprietary trading desk to an open platform. Their analysis engine is powered by a semantic web connecting over two hundred data sources and can be analyzed by an ever growing library which currently exposes over a thousand data analysis algorithms.
“We bring macro data, company-specific fundamental data, and market data together on one platform. This enables strategists to connect the dots in ways that were previously unattainable then give analysis. We provide a comprehensive library of statistical functions for data analysis. We included popular practitioner functions like curve trades and regressions as well as cutting edge machine learning algorithms from academia and quant trading. All functions as fully documented and based on open source libraries whenever possible, for example linest(ge,^spx) is an expression that can be used to plot the regression of GE’s stock price versus the S&P 500 using the popular scipy libraries.”