NLP and Sentiment Analysis in Investment Management

Participants are invited to a subsequent networking aperitif.
Datum17 Sep. 2024
Zeit13:00 - 17:00
StandortWarwick, Geneva
Norman Schürhoff, SFI Senior Chair, Universität Lausanne
Matthias Uhl, Head of Analytics & Quantitative Modelling (AQM) in Investment Solutions, UBS Asset Management

This SFI Master Class is offered in cooperation with the Geneva Financial Center (GFC).

 

In the modern era of finance, it is paramount that investment professionals seeking to gain a competitive edge using machine learning/artificial intelligence (ML/AI) and natural language processing (NLP) techniques. This Master Class delves into the innovative intersection of ML/AI and investment strategies. The Class is designed to equip the investment professional with a comprehensive understanding of sentiment analysis, a cutting-edge technique that leverages ML to interpret and use sentiment information extracted from textual data sources such as news articles, social media, and financial reports.

 

Current Situation

The past decade has witnessed an explosion in the amount of data produced by companies and individuals, newspapers such as the Financial Times and The Wall Street Journal, and web presences such as Google, Wikipedia, and X. The recent widespread availability of text-based data has coincided with major advances in the fields of ML/AI and especially in NLP. The analysis of sentiment in natural language holds the promise of addressing a range of challenges faced by the banking and financial sectors. Can investment managers use sentiment analytics to "look through" noise in financial markets? Can they identify longer-term cycles in news sentiment data and formulate a model that pinpoints longer-term trends in the data to address the market-timing challenges faced by asset managers?

 

Objective

This Master Class provides participants with an overview of natural language processing and sentiment analysis. It explores the economics of sentiment and highlights its applications in investment management. Best practices and trends are also discussed, via an interactive format.
The program includes:
•    An understanding of big data & AI trends
•    An introduction to sentiment analytics and natural language
•    Sentiment, definition and classification
•    Natural language generation (NLG), natural language understanding (NLU), and natural language processing (NLP)
•    A breakout session with group work on natural language
•    An understanding of the economics of sentiment analytics and natural language
•    The application of natural language in investment management
•    Sentiment analytics in the investment process
•    News sentiment cycles
•    Case studies across various asset classes
•    A study of best practices, trends, and outlook

 

SFI Master Class Features and Target Audience

SFI Master Classes offer seasoned banking and finance professionals a unique opportunity to exchange knowledge and share their professional views with peers, top-level academics, and industry experts in an interactive learning environment. Master Classes incorporate hands-on group work and opportunities for discussion. An on-site networking event will follow this Master Class.

This SFI Master Class is designed to provide all interested parties with invaluable insights into the world of machine learning and its application to investment management.

 

SAQ Recertification

This SFI Master Class is an acknowledged SAQ recertification measure and comprises four learning hours for the following SAQ profiles: 

  • Wealth Management Advisor CWMA

This SFI Master Class covers the aspect "industry knowledge."

 

Late cancellations and no-shows

If you have registered for a Master Class but are unable to attend, we kindly ask that you inform us as soon as possible. Places are limited, and late cancellations and no-shows not only prevent those on the waiting list from attending, but also result in an inefficient allocation of valuable resources. Your cooperation in communicating any unexpected changes regarding your participation at this Master Class is greatly appreciated.

Register here if you have already participated in an SFI Master Class

Personal Information

Persönliche Angaben

Informations personnelles

*
*
*

Terms and Conditions

Geschäftsbedingungen

Conditions générales

*
*

Register here if you are attending your first SFI Master Class