The financial sector is making a massive shift towards machine intelligence in capital markets. This panel shares their experience in using data science and domain expertise in understanding data context.
Tag: Data Science
“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.
Moderated by Jessica Titlebaum Darmoni from the Title Connection, Slade was joined by Brian Peterson, Algorithmic Trading Lead at DV Trading, Inderdeep Singh from CME Group’s Innovation Lab and Matthew Dixon, Assistant Professor of Finance and Statistics at Illinois Institute of Technology.
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Backtesting Trading Strategies
If you knew your trading strategy would work 50% of the time, would you commit your scarce savings to trade it? What if it worked 75% of the time? Backtesting gives one the confidence to know that your trading strategy will work.
“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.”
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.
With over 20 years of experience as a trader, portfolio manager, executive, and entrepreneur, Morgan Slade is now the CEO of CloudQuant, a cloud based quantitative strategy incubator and systematic investment fund. He has built quantitative trading businesses at some of the world’s largest hedge funds and Investment Banks …
CloudQuant will be participating in the Newsweek conference on Artificial Intelligence and Data Science for the Capital Markets Industry on December 5th to December 7th, 2017 in New York.
Cloud computing and access to industrial grade investment and data science tools are changing the playing field for quantitative trading firms. CloudQuant’s CEO Morgan Slade participated in a panel at Stocktoberfest West in October 2017. This has raised the discussion of quantamental investment and data science techniques. This is the merger of technology, investment management, and data science.
The impact of machine learning and open source resources on quant trading could be described as explosive. At FIA Expo in Chicago, CloudQuant’s CEO Morgan Slade will be discussing how that’s translating into opportunity for a wider variety of participants.