CloudQuant allocates millions to crowd-resourced trading algorithm

CloudQuant has allocated $20 million to a crowd resourced trading strategy, according to the company in a press release.

CloudQuant is the cloud-based trading strategy incubator. Quantitative analysts, algorithmic developers, data scientists and traders around the world create and test trading strategies leveraging CloudQuant’s superior infrastructure.

The strategy’s creator, an Australian based crowd researcher, leveraged CloudQuant’s market simulation and python based back-testing tools, to prove the algorithm’s performance and profitably within approved risk parameters. As a funded partner, the researcher will receive a share of the trading net profits.

“Striking a balance between complexity and simplicity can be a major key towards success,” said the crowd researcher when giving advice to other researchers.

The U.S. equity strategy began trading immediately upon approval of the licensing agreement from both the Quantitative Trader and CloudQuant management.

“Market enthusiasts are finding new alpha signals in alternative data sets, fundamental data, and market data. Our users are building exciting new trading strategies,” said CEO Morgan Slade. “We are excited about the talent we see emerging within our network of crowd researchers and confident new users will find trading opportunities.”

Using research tools originally conceived and developed by proprietary traders in the parent company, Kershner Trading Group, CloudQuant provides data driven resources to test an algorithm’s profitability. CloudQuant is proving that innovative trading strategies emerge when market enthusiasts are provided institutional grade research tools. The algorithm creator and CloudQuant can then enter into a profit sharing agreement to trade the algorithm using CloudQuant provided risk capital.