Big Data in Quantitative Trading Research and Algo Development

Big Data is data sets that are complex data sets, typically with large volume. Examples of Big Data in FINTECH include historical market data, news service information, tweets, and sentiment data.  Challenges in using big data include capture, storage, security, analysis, and visualization. Data scientists use Big Data (including alternative data) for predictive analytics. CloudQuant’s quantitative crowd researchers use historical market data, news data, and sentiment data to develop predictive trading strategies that are tested using a complex, proprietary backtesting trade simulator.


Quantitative Strategy, Trading, and Algo Development Industry News

Industry News: Machine Learning and Artificial Intelligence News October 16, 2017

FINTECH perspective on AI & ML: Barclays, big banks, Data Science Questions, Linear Optimizations, Robo-Advisors, Augmented Intelligence, and more …
Researcher reading iPad

Big Data, Data Analytics, Data Science in the News October 5, 2017

Data Science Topics: UBS, data quality, cloud-native, Morgan Stanley, wildlife monitoring drones, targeted marketing, retirement planning, Boeing, Google AI
Quantitative Strategy, Trading, and Algo Development Industry News

Big Data, Data Analytics in the News September 26, 2017

Big Data, Data Analytics News: Wall Street Robots, SEC, Microsoft, Nvidia, REGTECH, financial services firms, KPIs all using Data Science
Quantitative Strategy, Trading, and Algo Development Industry News

Big Data, Data Analytics in the News September 19

Big Data, Data Analytics in the News September 19 that the CloudQuant team found interesting this past week.
World Market Access

2017 – The Year of Artificial Intelligence

2017 is the year of artificial intelligence. Here’s why

World Economic Forum published that Artificial Intelligence (AI) is a rapidly growing discussion point in corporations and governments. This is driven by: 1. Everything is now becoming a connected device

The internet of things is collecting data in ways never before possible.

2. Computing is becoming free

The cost of computing continues to drop, especially with crowdsourced research platforms like CloudQuant.

3. Data is becoming the new oil

“The amounts and types of data available digitally have proliferated exponentially over the last decade, as everything has moved online, been made mobile with smartphones, and tracked via sensors. New sources of data emerged through things like social media, digital images and video.” 

4. Machine learning is becoming the new combustion engine

“new machine learning models have emerged recently that seem to be able to take better advantage of all the new data. For example, deep learning enables computers to ‘see’ or distinguish objects and text in images and videos much better than before.”

At CloudQuant our crowd researchers are finding that access to markets, and to data is allowing them to research and develop profitable algos in ways never before conceived. Access to new data sets, like social sentiment, allow new dimensions of quantitative strategies that were not conceived even five years ago. We anticipate that the new data “oil” and machine learning “engines” will continue to grow our world of trading.   See the full article on World Economic Forum’s web site by Sandhya Venkatachalam (24 May 2017).
Quantitative Strategy, Trading, and Algo Development Industry News

Discretionary Managers Seek Alpha in Alternative Data

Alternative data providers see huge potential in providing their data to discretionary asset managers who are losing assets to quantitative and systematic funds.

As active managers trail the performance of passive index funds and exchange-traded funds (ETFs), discretionary fund managers are scrambling to consume big data analytics into their decision making process.
While early movers in the big data analytics industry have mainly been quant hedge funds and systematic fund managers, the next wave is going to be discretionary fund managers, according to panelists at an event sponsored by Wall Street Horizon, EstimizeOTAS Technologies and FlexTrade Systems.
Read the full story on Traders Magazine Online