Machine Learning and Big Data in Quantitative Investing

May 31, 2019

Machine learning enables computers or machines to learn from data directly without being explicitly programmed. By nature, machine learning models can capture nonlinearities better than traditional models can. To extract valuable information hidden in a large dataset, you need to use modern tools for processing big data and machine learning together. Big data generally refers to a large volume of data that is hard to process using existing techniques that require in-memory computation. Data used in or stored by financial institutions that is typically considered big data includes: The most basic example of the role of data in finance is technical analysis in which the relationships among price, volume, and time are aggregated into technical indicators for predicting future movements in price.

Spotlight

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The Data Guild is a data product studio based in Palo Alto, California. Founded by three seasoned data entrepreneurs, we create data­driven solutions that serve our clients’ highest strategic priorities. We’re on a mission to use data to impact the world. Consider us your strategic partner throughout the design and development of compelling data products.We offer a variety of ways to collaborate. We take a design thinking approach to our engagements that puts users at the center of our process. We work closely with client teams to co­create solutions, from brainstorming data product ideas and collection strategies to building prototypes. For some clients, we act as an advanced R&D capability that can take on problems outside their current capabilities. For others, we work closely with internal groups as an expansion team and gradually transition our output to them.

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