Built in Chicago discusses CloudQuant, a Chicago-based algorithmic trading startup, lets anyone try their hand at devising their own strategies.
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…
“You have a chance to try and change an industry” said Slade, CEO of CloudQuant at the MarketsWiki Education’s World of Opportunity event in New York.
“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.
World Economic Forum published that Artificial Intelligence (AI) is a rapidly growing discussion point in corporations and governments. This is driven by: 1. Everything is now becoming a connected device. 2. Computing is becoming free. 3. Data is becoming the new oil. 4. Machine learning is becoming the new combustion engine.
The next wave of broker innovation likely will be geared toward democratizing quantitative trading, according to Kershner Trading Group Founder and CEO Andy Kershner. That would vastly expand the universe of high-level quant traders globally, which Kershner roughly estimated stands at perhaps 5,000 today.
Crowdsourcing in fund management and trading is the move to utilize anyone with an internet connection to participate in the research with the goal of finding new and better ways of trading. During the discussion the differing approaches being taken with the business models, and the technology, and the challenges each are facing.
Join us at the NY MarketsWiki Education to hear Morgan Slade’s thoughts on the The Algorithmic Trading Tesseract brings cloud computing, alternative data, machine learning, and crowd researchers together forming a revolutionary crowd in the financial industry.