Algorithmic Developers

Algo Developers also called Quantitative Analysts or Quants, design and implement trading algorithms that apply artificial intelligence, machine learning, and deep learning techniques for the purpose of allowing financial firms to price and trade securities. They are employed primarily by proprietary trading firms, investment banks, hedge funds, and other financial institutions that manage funds or have trading/investment operations.  Quants typically work directly with traders, providing them with algos for the purpose of pricing or trading.


Algo Trading powered by Alternative Data Sets

Conversations: Effects of Alternative Data Sets on Trading Algorithms

What effect can alternative data sets have on trading algorithms? We asked a few of our teammates and systematic traders what the effect of alternative data sets is on trading algos. We thought we could spread some insight as to why our alternative…
Alogo Allocation

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

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.
Trading strategies require thought

Conversations: Recommendations to Someone Starting out at CloudQuant

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The CloudQuant team discusses their helpful thoughts for beginners on CloudQuant. We want to boost everyone starting out on our platform in their algo development and backtesting. Everyone in our company uses the CloudQuant website and coding platform in one way or another. We all use our own application, just like the crowd researchers. When we say that our free backtesting tools are "institutional grade" we really mean it. Every algo we run in our trading and investment strategies is proven in the same backtesting engine as the crowd uses. We rely on the scorecards, the reports, and the simulated trades to ensure that our trading is successful.
backtest chart

Conversations: What we wish we knew when we started AlgoTrading

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CloudQuant's portfolio managers and quantitative algo traders look back on their starts in Algorithmic Trading. This candid overview allows everyone to see the "Things We Wish We Knew When We Started AlgoTrading".  This is a short collection of the interviews with some of our amazing coders here in the office
$QQQ ETH spreads wider than RTH spreads

US Stock Market pre-market and post-market bid-ask spreads are different than regular trading hours

Regular Trading Hours in the US Stock Market is 9:30 a.m. - 4:00 p.m. Trading can happen in the pre-market hours (4:00 a.m. - 9:30 a.m. ET) and in the After Hours market (4:00 p.m. - 8:00 p.m.). The free historical market data in CloudQuant allows you to examine the spread data and the differences between sessions.
Trevor Trinkino Quantitative Trader

Machine Learning FXCM Webinar with Trevor Trinkino of CloudQuant - Part 2/3

On May 15th Trevor Trinkino presented part two of a three-part Machine Learning webinar with FXCM. Part one is here. Part 2  - Preprocess data for Random Forest. PnL and prediciton improvements... In part two Trevor goes over…
Candlestick market data chart

Successful Starts in Algorithmic Trading

Many people have attempted to become the next great trader. They try assets like cryptocurrencies, or futures, or options and soon find out that it isn't as easy as they originally thought. They run into many of the same problems. ... Success comes with diligent work, support, and access to mentors, technology, and data.

CloudQuant presentation for the Students of the University of Chicago Financial Program

A video introduction to the CloudQuant Trading Strategy Incubator by data scientist, Nicolaus Schmandt
Trading Algorithms on CloudQuant

CloudQuant releases new version of free Algorithmic Strategy Backtesting Tools

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The latest version of our Trading Strategy Incubator's free algorithmic development and backtesting tools adds improved Graphical Analysis of Algorithmic Trading Strategies.
Backtest Homepage showing P&L and Sharpe

CloudQuant rolls out Upgrades to Free Stock Market Backtesting System

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.