Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

 
Only Sessions at Location/Venue 
 
 
Session Overview
Location: Tosca Conference hall
Meeting hall “Tosca”, which can accommodate up to 60 people
Date: Tuesday, 26/Aug/2025
9:00am
-
9:30am
Session 4.01: More Than Meets the Eye (or Ear): Surprising Microstructure Effects of Fed Chair Nonverbal Cues in High-Frequency Markets
Location: Tosca Conference hall
 

More Than Meets the Eye (or Ear): Surprising Microstructure Effects of Fed Chair Nonverbal Cues in High-Frequency Markets

Prof. John Paul Broussard, Prof. Andrei Nikiforov

9:30am
-
10:00am
Session 4.02: Mandatory Central Clearing and Derivative Offsetting
Location: Tosca Conference hall
 

Mandatory Central Clearing and Derivative Offsetting

Prof. John Zhang

10:00am
-
10:30am
Session 4.03: A Comprehensive Business Intelligence Analysis for Cryptocurrency Anomalies Detection
Location: Tosca Conference hall
 

A Comprehensive Business Intelligence Analysis for Cryptocurrency Anomalies Detection

Prof. Dima Alberg, Prof. Elroi Hadad

11:00am
-
11:30am
Session 4.04: Workshop: GNU Taler
Location: Tosca Conference hall
 

GNU Taler: Privacy for Inclusion, Free Software for Innovation

Prof. Christian Grothoff

11:30am
-
12:00pm
Session 4.05: Workshop: GNU Taler
Location: Tosca Conference hall
12:00pm
-
12:30pm
Session 4.06: Workshop: GNU Taler
Location: Tosca Conference hall
2:00pm
-
2:30pm
Session 4.07: Using Net-Zero Alignment Strength for Sustainable Portfolio Choice
Location: Tosca Conference hall
 

Using Net-Zero Alignment Strength for Sustainable Portfolio Choice

Prof. Budha Bhattacharya, Prof. Maxime Kirgo, Prof. Anatoly Schimdt

2:30pm
-
3:00pm
Session 4.08: Modelling Japanese firms’ dividend payout policies using new data
Location: Tosca Conference hall
 

Modelling Japanese firms’ dividend payout policies using new data

Prof. Clinton Watkins