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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Machine Learning and Artificial Intelligence News for the week ending Oct 2, 2017 that we found interesting from our FINTECH and CrowdSourcing perspective
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.
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.
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.
CloudQuant is THE trading strategy incubator. We’re building a free python data research tool for ordinary people with extraordinary trading ideas. We license and fund the best trading strategies and pay our users a share of the profits. Our group is a FINTECH startup housed under the umbrella of a trading firm with existing infrastructure and financial resources.
CloudQuant’s innovative Trading Strategy Incubator has managed to attract new users from 72 countries. The users represent developers, financial analysts, data scientists, traders, and other trading enthusiast who are interested in developing a trading strategy that may be funded if it proves to be profitable.