CloudQuant Launches with Unprecedented $15 Million Allocation to Crowd Researcher | Business Wire

CHICAGO–(BUSINESS WIRE)–CloudQuant, the trading strategy incubator, has launched its crowd

research platform by licensing and allocating $15 Million (USD) to a

trading algorithm. The algorithm licensor will receive a direct share of

the strategy’s monthly net trading profits.

The crowd researcher leveraged our free market simulation and python

data science tools to build an effective trading strategy. The strategy

began trading immediately upon approval of the licensing agreement.

“We're excited to launch CloudQuant. The launch represents the first

significant funding of a crowd-based quantitative analyst thereby

proving the opportunity for independent data scientists and market

enthusiast to join the ranks of institutional algorithmic traders,” said

Morgan Slade, CEO.

CloudQuant provides research, backtesting tools. Execution

technology conceived and developed by proprietary traders over the last

20 years in its parent company, Kershner Trading Group.

About Us

CloudQuant is the trading strategy incubator for data scientists and

traders around the world to create and test trading strategies. Proven

strategies are individually licensed from the owner, provided trading

capital and an execution team. Algo creators are paid a monthly

licensing fee from the net profits similar to a professional portfolio

manager. CloudQuant offers a mutually beneficial profit sharing license

enabling both parties to profit.

CloudQuant LLC, established in 2016, is a wholly owned subsidiary of

Kershner Trading Group LLC.

www.cloudquant.com

Disclaimer

The information contained herein doesn't constitute investment advice,

or an offer to sell. The solicitation of any offer to buy any

interests in CloudQuant LLC or its parent Kershner Trading Group LLC,

nor is it intended to be used for marketing purposes to any existing or

prospective investor in any jurisdiction. Is subject to correction,

completion and amendment without notice.