Industry Events
March 01, 2018
Peter Hafez will give a session on Machine Learning & Event Detection for Trading Energy Futures at this RavenPack-sponsored event.
The emergence of big data in finance has had a major impact on equities trading. However, other asset classes have seen less of an impact, since fewer alternative data sets are available to support these. In recent years this has changed with the proliferation of various social media sources and with the development of more advanced knowledge graphs that support a global macro theme.
During this talk Peter Hafez will show how RavenPack Analytics (RPA) can be used to uncover profitable trading signals for commodities based on news events detected across thousands of sources. In particular, he utilizes ten well-known machine learning algorithms to predict next day returns across a broad energy commodity basket.
At the event we'll also be showcasing our new product line called "RavenPack Text Analytics", that can systematically analyze your emails, instant messages, pdfs and any other textual content, to enhance Alpha generation, risk mitigation and compliance.
When : March 1-2, 2018
Where Downtown Conference Center 157 William Street, NYC 10038
Please use your business email. If you don't have one, please email us at info@ravenpack.com.
We will process your personal data with the purpose of managing your personal account on RavenPack and offering our services. You can exercise your rights of access, rectification, erasure, restriction of processing, data portability and objection by emailing us at privacy@ravenpack.com. For more information, you can check out our Privacy Policy.
Your request has been recorded and a team member will be in touch soon.
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.
Human capital is at the heart of value creation. Our latest research demonstrates how unprecedented workforce insights, sourced from over 200 million job postings, can generate more alpha.