Big Data in Quantitative Trading Research and Algo Development

Big Data is data sets that are complex data sets, typically with large volume. Examples of Big Data in FINTECH include historical market data, news service information, tweets, and sentiment data.  Challenges in using big data include capture, storage, security, analysis, and visualization. Data scientists use Big Data (including alternative data) for predictive analytics. CloudQuant’s quantitative crowd researchers use historical market data, news data, and sentiment data to develop predictive trading strategies that are tested using a complex, proprietary backtesting trade simulator.

Posts

Sarah Leonard, MScA, University of Chicago

Interview with Sarah Leonard, STEM Woman and Data Scientist

“It’s exciting to see the growing number of women in Science, Technology, Engineering and Math (STEM); my advice is to not be afraid to jump in headfirst,” said Sarah Leonard, graduate student at the University of Chicago. “It is a difficult field but also lucrative and rapidly growing.” Leonard sat down with CloudQuant to talk about her experiences in data science, her insight as a female in a male dominated world, and the intensive process it took to find her dream job.
Morgan Slade to Speak at RavenPack in London April 24, 2018

The RavenPack Big Data & Machine Learning Revolution Comes to London

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April 24, 2018, Top finance professionals who will share their latest research and experience with Ravenpack big data and machine learning in London.
Business charts

Industry News: Machine Learning and Artificial Intelligence for January 15, 2018

... While budgets may be tight we believe that innovators always find a way. Look for innovation to happen outside of mainstream information technology. Almost everyone trading today has some technology skills. It may be as simple as someone with an Excel spreadsheet macro, or a data scientists with a Jupyter Notebook. ...
Quantitative Strategy, Trading, and Algo Development Industry News

Industry News: Machine Learning and Artificial Intelligence for January 8, 2018

CloudQuant Thoughts: 80% of trading is being handled by robots? We know that 100% of trades are touched by automation these days. If it isn't in the actual order processing then it is in the clearing process, the risk process, or the account management process. When someone using a retail broker's website sees their portfolio there is added information that is presented. Almost all of that is touched by automation with some form of a "robot" or AI process.
Principles by Ray Dalio: Systemize Decision-Making

Industry News: Machine Learning and Artificial Intelligence for January 2, 2018

... the demand for Quants and Technologists has been "relentless" in FINTECH. We agree. The best source of candidates for these skills are going to be colleges like the University of Chicago where we get many of our interns. However, that doesn't mean that you can't participate. The best people are not the current students. The best people are the subject matter experts that grow their own skills. Pick up your skills. Attend online classes on Python, Math, and AI. Learn how to apply statistics. Many people are using our own platform to grow their quant skills this year.
chicago cityscape and sears tower

STAC MidWinter Conference January 10-11, 2018

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CloudQuant will be participating in the STAC MidWinter Conference on January 10-11 2018. Our CEO, Morgan Slade, will be a panelist on the Artificial Intelligence panel discussion.
Stock Market, Quantitative Strategy, Trading, and Algo Development Industry News

Industry News: Machine Learning and Artificial Intelligence for December 26, 2017

Never Mind Bitcoin. China Loves AI Stocks ...ofit estimates. And yet it’s one of the hottest stocks in China, gaining 117 percent this year as of Dec. 18, thanks to the latest investment craze sweeping the country’s $7.5 trillion equity…
85 Percent of Data is Unstructured

Is Crowdsourced Data Reliable?

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"Bring us your ideas and we will share the money with you,” agreed Morgan Slade, CEO of the crowdsourced algorithmic trading startup CloudQuant. “For us, engagement means breaking it down into a contractible problem."
www.futuresradioshow.com

Futures Radio Show interviews Morgan Slade December 12, 2017

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CloudQuant's CEO was interviewed by Anthony Crudele of Futures Radios show to discuss topic including Artificial Intelligence, Machine Learning, and Deep Learning applied to algorithmic trading. Alternative datasets are a major topic of discussion. People are saying that data is being created faster than ever before. That really isn't true. What is really happening is that data is being captured and stored at a faster rate than ever before. Vendors are now making AltData available for traders to change the way that they interact with the markets. This applies to futures and stocks with the popularity of Deep Learning in algorithmic trading strategy development.
Quantitative Strategy, Trading, and Algo Development Industry News

Industry News: Machine Learning and Artificial Intelligence for December 11, 2017

AI & ML news covering Hedge Funds, Career, Fraud Detection, Vineyards/Winemaking, Quanthouse, Apple, Quantitative Brokers, and more