January 25, 2023
Peter Hafez, our Chief Data Scientist, will take a deep dive into the power of real-time ESG controversy monitoring using RavenPack's Language AI technology.
ESG continues to build its momentum in Europe, but implementing impact-oriented portfolios requires actionable solutions. Investors are increasingly relying on data-driven processes to enact an efficient, scalable, and timely assessment of events that impact a company’s ESG profile, which in turn has made data access the foundational step in any long-haul ESG strategy.
To provide practical pathways, PwC Austria is gathering a panel of experts on January 25, 2023 at the DC Tower in Vienna
Their discussion will be covering key current topics among ESG investors, including:
Addressing the challenges faced in managing and reporting on ESG
The specific case of investing for impact in sovereign ESG
How to track controversies in real time with language AI
Integrating ESG into investment decisions to achieve an impact in low-income countries.
Peter Hafez, Chief Data Scientist at Ravenpack will present how RavenPack data can help assess the extent of a firm's ESG controversy exposure by incorporating real-time media attention and sentiment into ESG investing models.
Attending this panel will give you a better understanding of the impact of controversies on a company's stock price. It will also equip you to elevate risk management strategies and enable a systematic and transparent communication to both management and clients.
When: Wednesday, January 25, 2023 13:30-20:00
Where: DC Tower, Donau-City-Straße 71220 Wien,Vienna
See full agenda here
Peter Hafez - Chief Data Scientist
Title: “Tracking Real-time ESG Controversy With Language AI”
Peter is a pioneer in the field of applied news analytics, bringing alternative data to banks and hedge funds. He has more than 15 years of experience in quantitative finance with companies such as Standard & Poor's, Credit Suisse First Boston, and Saxo Bank.
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.
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