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.

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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.