Press
Jason Cornez, Chief Technology Officer, RavenPack | September 19, 2017
What if you could develop new signals on demand, in a matter of minutes?
Sentiment signals can add great value to an investment model. But developing a signal from news and social media can be a painful process, often requiring a specialist.
RavenPack introduces a new language for describing market indicators and a cloud-based service for creating signals and downloading them on the fly
Recorded at RavenPack's 5th Annual Research Symposium , that took place September 19, 2017 in New York City.
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High inflation has returned in developed markets after decades of lying low. In our latest paper, we show how to build an inflation-based asset allocation strategy using sentiment data and we illustrate that sentiment-based strategies outperform models that depend merely on past observed inflation values.
This year's RavenPack Research Symposium brought two intense days of knowledge sharing in London and New York, from 25 top experts in natural language processing, quantitative investing and machine learning. Together, we explored how firms can leverage new language models to generate alpha, better manage risk and respond to calls for more sustainable investment practices.
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