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This is Why Data Startups Are Disrupting Financial Analysis
Data Analytics Revolution
Among the new entrants is New York's Thinknum, a five-month old startup building an open financial analysis platform with Web 2.0 technologies to encourage users to share their models and insights.
"Quants already get data and get models. The pain point is really with the non-programmers in finance. We're building tools that target the financial people that don't know how to program," said Justin Zhen, cofounder of Thinknum. The startup is also targeting hedge funds and analysts who are struggling to update their models on spreadsheets and closed platforms. "With a hedge fund, there may be twenty people that want to show each other their models," says Zhen. "Hedge funds want to collaborate with people they trust. We're building communities of trust," says Zhen.
A graduate of Princeton University, who majored in financial engineering, Zhen worked at a hedge fund. He founded the company with Gregory Ugwi, who was a quantitative strategist at Goldman Sachs after majoring in math at Princeton. The idea for Thinknum was partially formedduring earnings season when Ugwi saw traders emailing spreadsheets and scrambling to update their models by hand. They bootstrapped the company with their own life savings. Now both are working out of the living room of their Manhattan apartment.
Thinknum has collected diverse data sets from 2,000 sources so far from a wide variety of public, government sources ranging from Swiss foreign exchange intervention to home prices by state. The startup is doing a lot of macroeconomic analysis of trends in the economy and pulling in XBRL data from SEC filings. "The goal is to collect data that no one else has access to," says Zhen.
The data is updated as earnings are released. One model on the site, known as cash flow model for securities valuations, allows someone to model the price of any stock, such as Google and then change it to a different stock. "It takes all of the inputs and spits out the intrinsic value of where the stock is going," says Zhen. While this can be done on a spreadsheet, "You cannot pull in the data as easily," insists Zhen.With its radically, open model, Thinknum is aiming to threaten the traditional closed data analysis platforms. "We think the next financial revolution is data analytics," says Zhen. "Currently solutions are extremely expensive. By being free and as open as we are, we will be able to reach a greater group of people," he says.
While Wall Street analysts aren't prone to sharing their models, people in finance are inherently social, says Zhen who has studied the rise of Stocktwits and Estimize where people are already sharing their insights. "The goal is to get a large pool of people and the larger the pool, the better the insights will come back." Thinknum has an algorithm that will rank the models, and ultimately rank the users on the site.
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"It's free for everyone to use, but the carrot is they have to share their analysis; they have to collaborate," says Zhen. Since many hedge fund and financial institutions don't like to share and never will share, Thinknum's business model is to charge them to remain private. Ivy is Editor-at-Large for Advanced Trading and Wall Street & Technology. Ivy is responsible for writing in-depth feature articles, daily blogs and news articles with a focus on automated trading in the capital markets. As an industry expert, Ivy has reported on a myriad ... View Full Bio