In-depth, Master-level Online Program in Modern Quantitative Finance
Master-level program in modern quantitative finance
✓ 4 core courses (120 hours): Data Science for Finance, Financial Engineering for Investment, Quantitative Risk Management and Quantitative Portfolio Management
✓ 3 refreshers (25 hours): Mathematics/Coding
✓ All courses delivered online twice a year (Fall/Winter and Spring/Summer)
✓ Access to the ARPM Lab
✓ Customized itinerary via an information session
✓ Live flipped classroom with instructors
✓ Private Q&A forum
✓ Homework assignments and grading
✓ Personal trainer’s reminders
✓ GARP CPD & CFA Institute CE
✓ Certificate of Completion
The Advanced Risk and Portfolio Management (ARPM) Marathon is a master-level program that:
The ARPM Marathon is delivered on the ARPM Lab.
The program includes the most advanced quantitative techniques in:
To ensure a balanced mix of theory and applications, the curriculum is best taught through four all-encompassing, mutually exclusive, core learning modules that cover all the topics of the ARPM Lab.
Refreshers are also offered to brush up on the basic concepts.
Participants can choose to attend one or more of the courses.
Instructors and Guests
Attilio Meucci is the founder of ARPM - Advanced Risk and Portfolio Management. Prior to ARPM, Attilio was the chief risk officer at KKR; and the global head of research for Bloomberg’s risk and portfolio analytics platform. Attilio has taught at Columbia-IEOR, NYU-Courant (New York), Bocconi University (Milan), and NUS-Business School (Singapore). Attilio earned a BA summa cum laude in Physics from the University of Milan, an MA in Economics from Bocconi University, a PhD in Mathematics from the University of Milan and is a CFA charterholder.
Professor at Carnegie Mellon University
Javier Peña is a full professor of operations research at Carnegie Mellon University. He teaches Financial Optimization and Asset Management in the Masters of Computational Finance program at Carnegie Mellon University. He is the co-author of the upcoming second edition of the textbook "Optimization Methods in Finance". His research interests span all aspects of optimization with a particular interest in optimization models for portfolio management and for data science. Javier has published his research in a variety of outlets including Quantitative Finance, the Journal of Risk, and Mathematics of Operations Research.
Professor at Baruch College
Tai-Ho Wang is a full professor in mathematics at Baruch College, City University of New York. He is one of the core instructors in Baruch's MFE program, where he teaches Probability and Stochastic Processes in Finance and Probability Theory for Financial Applications in the PreMFE seminars. His research in quantitative finance specializes in implied volatility modeling, exotic option pricing, optimal execution in market impact models, and information dynamics in financial market.
Angela Loregian is a senior researcher at ARPM, where she has contributed since inception to the creation of the ARPM Lab. In her previous academic career Angela has published on theory and applications of thick tailed processes in asset management. Angela runs research seminars and webinars for ARPM worldwide, including within the ARPM Bootcamp, ARPM's flagship event. Angela earned a Ph.D. in Mathematics for financial market analysis, an M.S. in Economics and Finance, and a B.S. in Economics from the University of Milano-Bicocca.
Partner at Oliver Wyman
Til Schuermann advises private and public sector clients on stress testing, capital planning, enterprise-wide risk management, model risk management and corporate governance including board oversight. Before joining Oliver Wyman, Til was a Senior Vice President at the Federal Reserve Bank of New York where he was head of Financial Intermediation in Research and head of Credit Risk in Bank Supervision. Til has numerous publications in both academic and practitioner journals, and has taught at Columbia University and at the Wharton School where he is a Research Fellow. Til received a Ph.D. in Economics from the University of Pennsylvania.
Partner at Oliver Wyman
Ugur Koyluoglu leads the Americas Finance & Risk and Public Policy practices at Oliver Wyman. Ugur has served as a consultant to senior executives at some of the largest banks, clearing and settlement houses, asset managers, multi-lateral development banks, and private equity houses around the world. Before joining Oliver Wyman, Ugur taught applied mathematics and engineering at Princeton and Koc Universities. He holds a PhD in Civil Engineering and Operations Research from Princeton University.
Head of product management at MathWorks
Stu Kozola leads product management for Computational Finance and FinTech at MathWorks. He has over 15 years of experience in data analytics, quantitative finance, simulation, and designing and implementing large-scale computational system. Stu holds the FRM designation from GARP and an MBA from Carnegie Mellon University.
Xiang Shi is senior researcher at ARPM, where he contributed to the development of the ARPM Lab, focusing on dynamic portfolio strategies and machine learning. Prior, Xiang was part of the risk team at KKR and taught at Stony Brook University. Xiang earned a MSc in mathematics and finance from Imperial College London, and a PhD in quantitative finance from Stony Brook University.
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