Trading Technologies and CloudQuant Launch Strategic Partnership to Explore Creation of Alternative Data Offering
FinTech Innovators Partner to Turn NLP into Dollars Chicago, Illinois, and San Francisco, California USA, December 21, 2020 – Vectorspace AI in partnership with CloudQuant announce the availability of novel datasets that reveal relationships between global equity products. Vectorspace AI datasets are designed to boost precision, accuracy, signal or alpha based on Natural Language Processing […]
Bayesian Network is a probabilistic graphical model which comprises variables and its relationships. It uses Bayesian inference and learning to develop the algorithm.
Baidu launches a simple AI training platform, simplification is the future, our new offering Cloudquant.AI will make it easier than ever for Data Scientists and Traders to identify/create profitable indicators and utilize or share them for profit. Detecting DeepFake to Thanos to Everyone Can Dance, how AI and ML are making it difficult to believe your eyes. Predicting Popularity of The New York Times Comments with effective use of a python sentiment library. Hardware Stocks to Outperform the Market, can you do better on CloudQuant? Finally, how to approach speech recognition in languages with fewer native speakers, Facebooks method vs an individual Data Scientist.
Google Wants to Dominate AI in 2018. Here’s Why Let’s get this out of the way: ever since the 2001 movie A.I. (and actually way before then, too), people have believed that artificial intelligence would soon emerge in the form of a race of robots that imitate human behavior until they become so smart and successful that […]
Trevor Trinkino presents the final part of his three-part Machine Learning webinar in co-operation with FXCM
“The most promising area of Quantitative Trading is using it (AI & ML) … to identify alpha that you wouldn’t normally be able to find by eyeballing things and looking at regression statistics and visualizations,” said Slade.
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.
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.
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.