CloudQuant Capital for Algorithmic Trading

Morgan Slade CEO CloudQuant

J Morgan Slade
photo by Bauwerks

Morgan has over 20 years of experience as a trader, portfolio manager, researcher, technologist, executive and entrepreneur in the financial services industry.  He is CEO and Head of Global Systematic Trading of CloudQuant, the cloud-based quantitative strategy incubator and systematic investment fund that leverages cloud computing, crowd researchers, machine learning and alternative datasets to generate alpha at scale.  He is excited to bring the opportunities for intellectual challenge and financial reward traditionally reserved for institutional research analysts to independent crowd researcher partners around the world.

Prior to that, he has built quantitative trading businesses at some of the world’s largest Hedge Funds and Investment Banks.  In the past, he has served as a Portfolio Manager for both Citadel Investments and Carlson Capital and has served as Global Head of Equity Trading for several large high-frequency trading firms.  Morgan is a recognized expert in Prediction, Machine Learning, High-Frequency Trading, Autonomous Market Making and is interested in the application of Deep Learning to quantitative trading. Morgan earned a BS and MS in Materials Science and Engineering from MIT.

His full profile can be found on LinkedIn

 

Tayloe Draughon Senior Product Manager

Tayloe has over 25 years of experience in product and technology management. He is Senior Product Manager at CloudQuant where he is responsible for the marketing and management of products through their full life-cycle.

Tayloe has spent much of his career in the financial and regulatory technology space with a focus on bringing new capabilities to the market and publishing product information. With an emphasis on communication and operational efficiency, he ensures a smooth client on-boarding experience. Before joining CloudQuant, Tayloe was the Director of Product Design at Neurensic.com as well as Director of Product Delivery for Futures at Societe Generale CIB-Newedge. He held similar positions at Cargill Investor Services and Capital Markets Consulting, in which he was also a co-founder. Tayloe is an assistant scoutmaster for his local scout troop, serves on the FIA Technology Board and is a former co-chairman of the FIX Protocol Global Derivatives Committee. He graduated from Indiana University, Bloomington with a BS in Decision Science.

His full profile can be found on LinkedIn

The Internal Team

The full-time team is made up of Portfolio Managers, Data Scientists, and technologists who work together to provide the Trading Strategy Incubator. We are looking for you to grow your career on our innovative team.

The Distributed Team – Where you fit in

Our cloud-based approach to algo development and funding allows you to join the team. As a member of the team you will be paid based upon the performance of algos that you develop and submit to CloudQuant for funding and production.

CQ Lite Open Roles

  • Algo Developer: Entry level algo developers.
  • Algo Developer and Backtester: Algo developers who have successfully submitted 10 or more backtests on 2 or more algos.
  • Algo Researcher: Algo developers who have successfully submitted 25 or more backtests on 5 or more algos and have downloaded 20 reports.
  • CQ Lite Subject Matter Experts (SME): Algo developers who have answered 25 or more questions in the online community or who have submitted a sample algo for use in public scripts.

CQ Lite members are eligible to be upgraded to CQ Elite after having achieved Algo Developer and Backtester or Algo Researcher roles.

CQ Elite Open Roles

  • Research Analyst: CQ Elite level user who has submitted at least one algo for review for funding.
  • Quantitative Trader: CQ Elite level users who have received an offer for funding of a proprietary algo.
  • Jedi Master (Forum Subject Matter Expert): CQ Elite level users who have answered 75 or more questions in the online community.

CQ Research Partners

The CQ Research Partner program is designed to accommodate professional teams or very successful CQ Elite teammates who have grown their algo development business to a very successful level. The Research Partners are able to work in teams and share information among users. They are given python notebook access to the backtesting system and are able to use their own Python development environments. CQ Research Partners are given much greater access to technology.

CQ Research Partners have greater legal requirements, including signing a non-disclosure agreement.