The PhD Program in Models for Economics, Territory and Finance has entered into an agreement with Advanced Risk and Portfolio Management (New York). Through this collaboration, PhD students can take part in the Quant-Bootcamp (https://www.arpm.co/quant-bootcamp) and related activities.
The Quant-Bootcamp is a course that provides a comprehensive overview of the most advanced Data Science and Machine Learning techniques and their applications in Quantitative Finance. In addition to foundational theoretical and applied lectures, the program includes access to the ARPM Lab online laboratory, conferences delivered by world-renowned speakers, and networking opportunities with industry leaders and with hundreds of participants from the professional world and other universities.
The Quant-Bootcamp is free of charge for students of the PhD Program in Models for Economics, Territory and Finance and can be attended via live streaming or on-site at the New York University.
The PhD Program in Models for Economics, Territory and Finance has agreements with numerous universities abroad aimed at hosting doctoral students for visiting periods, also with a view to the awarding of the Doctor Europaeus title.
Advanced Risk and Portfolio Management (ARPM), founded by Attilio Meucci, offers the ARPM Quant Bootcamp - a 6-day intensive program at the intersection of machine learning and quantitative finance.
In a space often driven by ML/AI hype, ARPM has spent nearly two decades building a unified mathematical framework that connects machine learning with finance.
The Quant Bootcamp, well established in quant circles, takes participants from ML foundations to real-world applications in financial engineering, risk management, and portfolio construction. With 19 editions, 5,000+ graduates, and participants from 20+ countries, it brings together students, researchers, and practitioners from leading institutions worldwide.
Delivered at New York University and via live streaming, and led by Dr. Attilio Meucci, the program combines theory, hands-on work, and guest lectures from world-renowned practitioners.
Participants gain:
A clear understanding of how machine learning is applied in quantitative finance
A balance of theoretical foundations and practical implementation
Access to the ARPM Lab ecosystem (interactive theory, code, and case studies)
Exposure to a global network of professionals
