Crowdsourcing News & Topics in Algorithmic Trading, Quantitative Finance, …

Crowdsourcing is the internet model where anyone with a computer can be involved in an activity. At CloudQuant this is an opportunity for students, recent graduates, and career-changers to be involved in quantitative research and algorithmic trading. Anyone on the internet can use the free tools provided to create and prove that a trading algorithm works.

This is our CrowdSourced Trading Strategy Incubator. As a member of the crowd, we partner with you to bring your idea to market. This partnership is properly licensed so that you retain your rights to your strategy. When we both agree to the terms of the profit sharing deal, then we fund and run the algo you have already proven. Having a larger amount of capital results in a stronger possibility of succeeding in the markets. Your algo is able to run “At Scale” instead of inside the constraints of your own capital.

Posts

Morgan Slade, Python Data Scientist and Trader

CloudQuant CEO John Morgan Slade presenting at THE TRADING SHOW – CHICAGO 2019

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CloudQuant CEO John Morgan Slade will be taking part in THE TRADING SHOW – CHICAGO 2019 on Wednesday 8th May 2019. At 13:20 (Central) he will be partaking in a Panel to discuss “Deep Neural Networks – how supervised do deep learning machines need to be?” At 14:00 (Central) He will be moderating a discussion on “AI and Machine Learning – how markets will move forward.” See the official website for more information.
backtest chart

CloudQuant Partners with RavenPack to Expand Use of Alternative Data

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FOR IMMEDIATE RELEASE: CloudQuant Partners with RavenPack to Expand Use of Alternative Data Chicago, Illinois, USA, November 20, 2018 – CloudQuant LLC today announced the addition of RavenPack analytics within their trading strategy incubator. Crowd researchers can now use RavenPack historical data to discover tradable alpha signals on CloudQuant’s online Python and JupyterLab-based tools. RavenPack is a leading provider of big data analytics for financial services that enables hedge funds, banks and asset managers to query and visualize unstructured data including insights from thousands of news and social media sources. “We are thrilled to include RavenPack analytics in our ecosystem as they have become a vital source of alpha for quantitative investors,” said Morgan Slade, CEO of CloudQuant. “Our community is already finding promising signals that originate from the very popular RavenPack datasets.” Crowd-based research tools are increasing in popularity along with the rapidly growing data science field. RavenPack and Cloudquant are finding that crowd researchers desire access to Wall Street professional-quality tools and datasets, which enable them to thrive in the professional investment field. “We were impressed with how CloudQuant provides anyone with Python-coding skills the opportunity to mine our datasets for alpha signals and earn compensation for their contributions,” said Amando Gonzalez, CEO of RavenPack.  “We strongly support initiatives designed to give data scientists the tools that liberate ideas to improve financial modeling.”   About CloudQuant CloudQuant is the cloud-based trading strategy incubator. Quantitative analysts around the world create and test trading strategies leveraging free institutional grade technology. By providing the capital, technology, and trading acumen to develop and utilize trading strategies, CloudQuant offers a mutually beneficial profit sharing agreement enabling both parties to profit. CloudQuant LLC, who officially launched in 2017, is a wholly owned subsidiary of Kershner Trading Group LLC.   www.cloudquant.com Twitter: @CloudQuant About RavenPack RavenPack is the leading provider of big data analytics for the financial services industry.  Financial professionals rely on RavenPack for its speed and accuracy in analyzing large analyzing large amounts of unstructured content.  The company’s products allow clients to enhance returns, reduce risk and increase efficiency by systematically incorporating the effects of public information in their models or workflows. www.RavenPack.com Twitter: @RavenPack   For Media Inquiries Please Contact: Jessica Titlebaum Darmoni Jessica@thetitleconnections.com + 1 312 358 3963 – END –
Alogo Allocation

Record First Year Growth and a New Allocation to a Trading Strategy

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Chicago, Illinois, USA, August 29, 2018 – CloudQuant LLC is pleased to announce a new crowdsourced trading strategy license agreement. This marks the eighth successful partnership with a global algo developer, since their public launch one year ago. Researchers receive 10% of net trading profits under the terms of the license agreement.
Backtest Homepage showing P&L and Sharpe

CloudQuant rolls out Upgrades to Free Stock Market Backtesting System

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CloudQuant, the trading strategy incubator, announces upgrades to our free stock market backtesting system. The web application allows any market enthusiasts to develop a trading strategy using easy to learn Python programming. Anyone who has ever written a spreadsheet macro or a simple program can easily use the system.
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.
John "Morgan" Slade

Open Source Meets Quant Trading – Futures Industry Association

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Recording of October 17-19, 2017 Future Industry Associations EXPO panel discussion on Open Source Meets Quant Trading.
Machine Learning, Quantitative Investing News

Industry News: Machine Learning and Artificial Intelligence News 10/30/2017

AI and ML for CloudQuant, ArcaEx, Corporate earnings reports, Hedge Funds, Microsoft, Alexa, Saturday Night Live, the apocalypse, Elon Musk, and more …
World Market Access

Futures Radio Show from FIA Expo 2017

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An interview by Anthony Crudele of Futures Radio Show discussing the success of the Trading Strategy Incubator, crowd researching, and algorithmic trading.
Crowdsourcing Algorithmic Research

​CloudQuant Is a Trade Strategy Incubator That’s Looking to Develop and Fund Algorithm Traders

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A rising population of programmers, data scientists and mathematicians are now looking to write complex codes for automated investment strategies of their own. This is crowdsourced algorithmic trading.