Trading Strategy

A trading strategy is a plan (often implemented in an algorithm) that defines when a trader will place orders to enter and exit an investment. Trading strategies range from simple sets of rules that an individual follows all the way to highly complicated applied artificial intelligence computer systems.

Many successful trading strategies go beyond orders to buy and sell. They often include risk management, hedging, and money management.

Posts

Algo Trading powered by Alternative Data Sets

Conversations: Effects of Alternative Data Sets on Trading Algorithms

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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

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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.
Facebook drop 19%, July 2018

$FB Decline 19%- What did the Social and technical analysis show? - July 26 2018

$FB's 19% drop was preceded by TA-LIB and Social Market Analytics indicators to sell. The $120 Billion drop in market cap could have been an opportunity to short sell before the market close the previous night.
$20M Allocation to Crowd Developed Trading Algorithm

CloudQuant Allocates Millions to Crowd-Resourced Trading Algorithm

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CloudQuant, one of 50’s Most Promising FinTech Solution Providers of the year, has allocated $20 million to a crowd resourced trading strategy. The strategy’s creator, an Australian based crowd researcher, leveraged CloudQuant’s market simulation and python based back-testing tools, to prove the algorithm’s performance and profitably within approved risk parameters.

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

Market Turmoil Generates Opportunity for Proprietary Traders

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In these times of market turmoil and volatility, the Kershner Trading Group stands ready to provide traders with a firm built on a strong foundation of significant capital investment, innovation-focused trading technology and decades of experience in the active and proprietary trading space. Kershner Trading is actively seeking experienced US Equities Traders
Trading Strategy Scorecard from CloudQuant

One Minute Trader Podcast with Tayloe Draughon of CloudQuant

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One Minute Trader with Matt Davio recently interviewed Tayloe Draughon to discuss Crowd Sourced Trading Ideas using our trading strategy incubator.
Backtest Research Life Cycle for Trading Strategies

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.
Harami Sell Signal on Google Dec 20, 2017

Harami Sell Signal with Three Inside Down Demonstrated on $GOOG

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December 19, 2017 Monday Google pressed new highs, but Tuesday closed out the day with a Harami Sell signal. Watch out for today. A negative close today boosts the negative outlook with the emergence of a Three Inside Down pattern. In this event, it will most likely mean that there will be a “little coal in Google stockholders stockings for Christmas”.
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.