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This is Why Data Startups Are Disrupting Financial Analysis

A new generation of startups is making financial analysis easier, with open, collaborative and visually intuitive, cloud-based platforms.

Using sophisticated pattern recognition technology, Eidosearch can provide equity traders, analysts and portfolio managers, with the ability to project return expectations for thousands of stocks, based on decades of history -- all within seconds, notes its web site.

"We offer the ability to uncover the recurring patterns throughout time, in a very fast and accurate exercise," says Kedmey, who previously worked in the mergers and acquisitions department in the investment banking division at Oppenheimer & Co. He cofounded the company with Xaio-Ping (Steven) Zhang, whom Kedmey met at the University of Chicago Booth School of Business, and is expert in information processing technologies and content search engine.

Zhang, who is CEO of Eidosearch, has applied content-based search to photo matching and the human genome project. "When we met at the University of Chicago we realized that these search techniques were well suited for financial data," says Kedmey. Unlike looking for data in Youtube and in social media, in finance the data is well defined and well structured," said Kedmey. Also, if someone wanted to describe the behavior of the VIX and picture the curve and how it trades over time, language is not well suited to describing that path, says Kedmey. "With patterns recognition you can search with patterns, there really is no semantic gap," he explains.

Ultimately, Eidosearch is trying to quantify investor behavior. For example, last year, investors shot Tesla Motors from $40 in early April up to $193 by the end of September. In response to reports of three battery fires in early October, investors became fearful and began to bail out of the stock, producing a chain reaction that pushed the stock down to $121 by late November. Though Tesla's fundamentals did not justify a drop of $70 in two months -- just like it didn't justify a 400% price increase in five months, says Kedmey -- investors became fearful and overreacted to the negative news. For an investor holding Tesla stock, the question was going to be would the stock rebound. With Eidosearch, the trader is able to find similar occurrences of this price trend historically and to see how investors reacted in the next three months. Using the pattern of Tesla's stock one-year stock price through September 2013, Eidosearch discovered 55 similar stocks found based on comparing the price behavior of Tesla to all other consumer cyclical stocks in its sector throughout history. The average return in the next three months was 20%, according to Eidosearch.

1. Search by example using Tesla's price through Sept 2013
View Larger

1. Search by example using Tesla's price through Sept 2013

2. 55 similar stocks found based on comparing the dynamic price behavior of Tesla to all other stocks in its sector throughout history (overlay view of top 8 charts shown below)
View Larger

2. 55 similar stocks found based on comparing the dynamic price behavior of Tesla to all other stocks in its sector throughout history (overlay view of top 8 charts shown below)

Clients include major mutual fund companies, futures and currency firms and those on the equities and global macro thinkers --who are forecasting a day or a week out, and those forecasting six months or even 12 months out.

Like the other startups Eidosearch is hosted on the Amazon cloud. "We bring in data from various data vendors for our off-the-shelf solution, and some clients send it their data over night and we ingest it and make it searchable, and we can use it in conjunction with all of our data sets," says Kedmey. 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

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IvySchmerken
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IvySchmerken,
User Rank: Author
2/24/2014 | 3:15:47 PM
re: This is Why Data Startups Are Disrupting Financial Analysis
Making life dramatically easier for institutional investors is definitely the way to attract attentions from customers. The quality and accuracy of the financial analysis is important, but without ease of use, why would anyone switch or take on a new provider? I agree that disruption doesn't mean destruction. Startups can partner with the larger financial information or software providers to gain distribution since they already have the audience.
IvySchmerken
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IvySchmerken,
User Rank: Author
2/24/2014 | 3:11:42 PM
re: This is Why Data Startups Are Disrupting Financial Analysis
I totally agree. Startups today can test their ideas with cloud-based infrastructure without incurring the cost of a fixed capital investment. This elastic model is helping startups scale up when they need to. They can develop their products, sales/marketing and distribution without allocating scant resources to servers and just keeping the lights on.
Nathan Golia
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Nathan Golia,
User Rank: Author
2/21/2014 | 3:44:09 AM
re: This is Why Data Startups Are Disrupting Financial Analysis
Yes, the cloud goes a long way in helping new entrants quickly fill the need for certain capabilities in markets. Defraying the cost of infrastructure goes a long way in making any company effective quickly.
ArielY766
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ArielY766,
User Rank: Apprentice
2/18/2014 | 2:56:03 PM
re: This is Why Data Startups Are Disrupting Financial Analysis
Excellent article on the power of cloud technology and innovation to radically change the ways that financial analysis is performed. Thetica Systems is proud to be one of those cloud based innovators, making life dramatically easier for institutional investors in ABS, CLO, RMBS and CMBS bonds.

I believe itG«÷s also important to note that disruption doesnG«÷t have to equal destruction. By working in partnership with leading industry providers, weG«÷ve been able to greatly enhance the experience for our mutual end users.
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