CloudQuant, one of 50’s Most Promising FinTech Solution Providers of the year, has allocated risk capital to a crowd resourced trading strategy. 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.
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CloudQuant allocates risk capital to another crowd researcher by funding and leasing a crowdsourced trading algorithm. The licensor will receive a direct share of the monthly net trading profits.
FintekNews recently asked 3 Questions of our CEO Morgan Slade. This is in response to our recently announced launch with a $15M allocation to a crowd based trading strategy algo creator.
Quantitative Trading and Data Science in the News August 28 2017: CloudQuant opens door to crowd algo traders, RBC AI pilot, RBC pilots AI-based financial insight tools, AI focussed Chip, Momentum trading guide…
CloudQuant, the trading strategy incubator, has launched its crowd research platform by licensing and allocating risk capital to a trading algorithm. The algorithm licensor will receive a direct share of the strategy’s monthly net trading profits.
“We’re tapping into the new skills coming out of educational institutions and students’ and graduates’ new ways of looking at things, but there are also opportunities for experienced people to connect the dots related to the ontological relationships between the data and the stock markets and other assets,” Slade said. “There are huge untapped resources out there, and we try to engage with the researchers as if they were employees and support them as such.”
Your Proprietary Trading Algorithm is always your property on CloudQuant. Any trading strategy that you develop is yours. Not ours. You do not transfer ownership of the algo to CloudQuant. You do not transfer any copyrights to CloudQuant. This is fundamental to the operations and success of CloudQuant.