Over the last few years we have seen a significant uptake in teams using programmatic solutions to facilitate their factor research workflows, with languages like Python fast becoming the de-facto standard for how analysts engage with data. With such advancements, adoption is now easier, allowing for easier interaction with large data sets and efficiency gains in programming research workflows.
Watch as our experts explore the capabilities of FactSet’s award-winning Quantitative Research Environment (QRE) and demonstrate how a Python-based platform can speed up the progress of research, using integrated data and allowing for the optimum flexibility by simplifying processes.
The purpose of this webinar is fourfold:
Outline of the main quantitative research steps
Review FactSet Earning Estimates database including its multi dimensionality
Leverage QRE to conduct single signal research
Compare and contrast the signal to generic signals found in FactSet's Quantitative Factor Library
Watch the recording now