University partnerships
Bring Machine Learning and Quantitative Finance into the classroom. ARPM supports university programs in finance, economics, engineering, physics, mathematics, computer science, and statistics.
The Academia Program provides the following services, free of charge to faculty and students of partner universities:
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ARPM Lab (opens in a new tab) : faculty and students have access to constantly updated online reference material on Machine Learning and Quantitative Finance: theory, code, animations, and more.
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Quant Bootcamp
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: students are welcome to attend the Live Streaming version of ARPM's flagship event, and a
select group of students are invited to attend the Onsite event in New York.
Completing the Quant Bootcamp grants academic credits towards one's degree at select partner
universities.
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Course enhancement: ARPM researchers help faculty complement their syllabi with interactive links to relevant parts of the Lab, across topics in Machine Learning and Quantitative Finance, and across channels: theory, code, animations, and more.
Upon request, ARPM can build a customized LMS to automatically monitor and report the student's progress in the Lab.
Upon request, ARPM researchers are available to provide remotely guest lectures based on the Lab.
Discover how partner universities integrate ARPM into their teaching and learning.
Ca’ Foscari University of Venice promotes ARPM educational initiatives, scholarships, and quantitative finance training opportunities related to machine learning, risk management, and financial engineering.
ARPM supports the Master of Science in Finance and Banking at the University of Rome Tor Vergata through advanced educational material and research-oriented content in machine learning and quantitative finance.
The Collegio Carlo Alberto highlights ARPM as a resource for advanced education and research in machine learning, quantitative finance, and statistical learning.
The University of Bologna collaborates with ARPM to provide advanced education in machine learning, quantitative finance, financial engineering, and risk management through the ARPM Lab and Quant Bootcamp.
The University “G. d’Annunzio” of Chieti–Pescara references ARPM among the international educational opportunities supporting advanced training in quantitative finance, machine learning, and financial risk management.
The Lisbon School of Economics and Finance promotes ARPM as an advanced training opportunity in machine learning, quantitative finance, and risk management for students in finance-related programs.
Universidad del CEMA highlights its agreement with ARPM to support advanced education in quantitative finance, machine learning, and modern financial risk management.
MCF School of Computing promotes ARPM as an advanced training opportunity in machine learning, quantitative finance, and risk management for students in finance-related programs.
Roma Tre University includes ARPM among the academic resources supporting research and education in quantitative finance, financial markets, and advanced statistical methods.
Sapienza University of Rome references ARPM among the educational resources supporting advanced training in quantitative finance, statistics, and machine learning applications in finance.
Course Outline FRE 6083 Quantitative Methods In Finance
Topics in Mathematical Finance: Advanced Risk and Portfolio Management (ARPM)
The University of Verona promotes ARPM educational initiatives as an advanced training opportunity in quantitative finance, risk management, and machine learning for mathematically oriented students.
The University of Macerata presents ARPM educational initiatives and the Quant Bootcamp as advanced learning opportunities in machine learning, quantitative finance, and modern risk management.
The University of Florence promotes ARPM’s Quant Bootcamp as an advanced learning opportunity in machine learning, quantitative finance, and risk management for students in finance-related programs.
