May 11, 2022
RavenPack team will share the five most recent research that illustrates the new ways to leverage NLP earnings intelligence to capture more alpha in the Worldwide Business Strategies Webinar.
With hundreds of companies holding earnings conference calls within narrow timeframes, the challenge of capturing the full breadth of information they contain is ubiquitous. Analysts and investors are left with no choice but to prioritize their attendance — a decision that hampers their ability to capture the full breadth of short-term opportunities. Natural Language Processing (NLP) is the trump card for analysts and investors to capture alpha in Earnings Season.
RavenPack’s Chief Data Scientist Peter Hafez and his team will discuss the five most recent research papers that illustrate the new ways to leverage NLP earnings intelligence to capture more alpha.
See full agenda here.
When: 11th May 2022 3pm BST/4pm CET/ 10am EDT
Where: Online Webinar
Peter Hafez -
Chief Data Scientist
Topic: From Earnings Call Transcripts to Earnings Intelligence
Synthesizing the extensive volume of information embedded throughout the earnings cycle can help investors generate more alpha. In this presentation, Peter will talk about how to combine insights from earnings call transcripts, earnings news, and insider transactions data to arrive at a more advanced framework we refer to as RavenPack Earnings Intelligence.
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.
Anmar Al Wakil -
Senior Data Scientist
Topic: Enhancing equity and credit investing with Earnings Conference Calls
Anmar Al Wakil will demonstrate how security-selection skills and risk-adjusted-performance can be substantially enhanced in equity and credit systematic investing, capturing complementary and incremental informativeness from NLP-driven earnings news and transcripts.
Anmar has over 8 years of experience in developing systematic investment strategies. He holds a Ph.D. in Quantitative Finance from the University of Paris Dauphine-PSL along with a Master’s degree in Mathematical Finance. At RavenPack, Anmar excavates cutting-edge insights from news sentiment to elaborate alpha-generating strategies across equity, credit, and derivatives instruments. Also, he advises some of the world's top hedge funds and asset managers on the use of NLP-driven analytics in finance.
Anmar’s article about asset pricing won the Best Doctoral Paper of the Multinational Finance Society. He is also a part-time Associate Professor at the University of Paris-Est where he heads the MSc in Portfolio Management.
Paolo Andreini -
Senior Data Scientist
Topic: Tracking Economic Activity from Earnings Call Transcripts
Paolo will demonstrate how to leverage RavenPack EDGE event detection to analyze earning call transcripts and create a real-time Transcript Economic Sentiment Indicator (TESI) able to predict the business cycle phases and create profitable investment strategies based on assets rotation.
Paolo holds a Ph.D. in Economics and Finance from the Tor Vergata University of Rome and he is a Senior Data Science at RavenPack. Before joining RavenPack, he worked at Now-Casting Economics in London as Senior Economist. Today, Paolo focuses on ways of leveraging RavenPack news analytics for global macro investment strategies and develops forecasting macroeconomic models.
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