We invite submissions of both theoretical and applied research. Authors are strongly encouraged to submit full papers, which will be given preference. However, extended abstracts (maximum 1,000 words), including methodology, data, and key hypotheses, will also be considered.
Key Dates
Application deadline for the summer school: April 30, 2025.
Paper submission deadline for the conference: April 30, 2025.
The fees
Fee for Ph.D. students
Summer school and conference 450 CHF.
Summer school 300 CHF.
Conference: 150 CHF.
Fee for Researchers and Professors
Summer school and conference 700 CHF.
Summer school 450 CHF.
Conference: 250 CHF.
Fee for online participants (summer school only)
Summer school 100 CHF (Online participation is limited to streaming only, and chat responses will not be available.)
Overview
Join us for an immersive Summer School and Conference dedicated to Deep Learning for Dynamic Stochastic Models. This program provides a unique opportunity to gain hands-on computational training and theoretical insights from leading experts in economics and finance.
Why Deep Learning for Economic and Financial Models?
Modern economic and financial models are often high-dimensional, nonlinear, and stochastic, making them difficult to tackle with traditional methods. Recent breakthroughs in deep learning have broadened the possibilities, enabling models once considered infeasible. These advances boost computational efficiency and enhance precision in economic and financial forecasting.
Program Highlights
Intensive Lectures and Tutorials
Three core sessions focusing on foundational theory and practical applications.
Emphasis on two powerful machine learning techniques: Deep Neural Networks and Gaussian Processes.
Demonstrations in finance, macroeconomics, and climate change economics.
Hands-On Coding Sessions
Practical workshops to apply deep learning methods to real-world datasets and models.
Guidance on computational best practices and efficient algorithmic implementation.
Two-Day Conference
A forum featuring leading academics, researchers, and practitioners.
Invited talks, contributed presentations, and panel discussions highlighting the latest innovations in dynamic stochastic modeling and deep learning.
Networking opportunities designed to foster collaboration and knowledge exchange.
Who Should Attend
Early and mid-stage researchers, including advanced Ph.D. students.
Senior researchers and professors interested in deep learning applications.
Practitioners aiming to expand their skill set in quantitative modeling.
The Host
The Summer School and Conference will be held at the Department of Economics, Social Studies, Applied Mathematics and Statistics, University of Turin, Italy. The department has been recognized among the Italian "Departments of Excellence" and has been granted funding from the Ministry of University and Research (MUR) for a five-year development project with the aim of further increase the quality of research and the scientific, organizational and didactic planning abilities. The organization of the Summer School and Conference is part of this project, and Turin’s rich cultural heritage, historical significance, and vibrant academic setting make it an ideal location for intensive learning and professional networking.
Supporting partners/institutions