ARPM Training


Intense or part-time, onsite or online, live or on-demand, overview or in-depth.
Choose the program that fits your schedule and needs.


The Advanced Risk and Portfolio Management (ARPM) training programs are tailored to a variety of different needs, circumstances and learning styles. Whether you are looking for in-depth coursework that builds knowledge at the masters level, an intense training that provides a broad overview of modern quantitative finance in less than a week, or a self-guided experience that lets you work through concepts and exercises at your own pace, ARPM has a training program to fit your needs.

How to Choose

Which ARPM course or program makes the most sense for you depends on the depth of knowledge you wish to acquire, and the time you have to devote to your study. Please review the chart below for a comparison of our training programs, or feel free to Contact us for more information or assistance in planning your ARPM experience.

Bootcamp Quant Tour Marathon
Topics Data Science
for Finance
Financial Engineering
for Investment
Quantititative Risk
Quantitative Portfolio
Lab iconVideo lectures iconTheory iconCase studies iconData animations
iconCode iconDocumentation iconSlides iconExercises
Depth Big picture Understanding Deep knowledge
Location Onsite NY Online Online
Modularity 1 course 1 course 4 courses
When Aug 15-20 Anytime Starts Feb 1|Sep1
Length 6 days 3 months 1-4 semesters
Intensity Full time Part time Part time
Guidance Live instructor - Live instructor
- 30hrs recorded lectures 150hrs recorded lectures
24hr Q&A service 24hr Q&A service 24hr Q&A service
- - Hand-graded homework
- Progress stats Progress stats
Networking Large class - Small class + Alumni


Instruction and Delivery

The training programs are delivered ARPM Lab.

Our Bootcamp, Quant Tour and Marathon include the most advanced quantitative techniques in:

Data science and machine learning
Market modeling
Factor modeling
Portfolio construction

Algorithmic trading
Investment risk management
Liquidity modeling
Enterprise risk management

The ARPM body of knowledge is organized into four all-encompassing, mutually exclusive, topics that cover all the topics of the ARPM Lab.

Preparation courses in Mathematics, Python and MATLAB are also offered to brush up on the basic concepts.


The ARPM Lab contains all the support materials to learn and practice the concepts covered during the lectures:


ARPM Awards a certificate of completion at the conclusion of the Bootcamp, the Quant Tour and each of each of our Marathon courses. In addition, ARPM training prepares students to pass the examinations required for the ARPM Certificate, a trusted credential which indicates broad and deep proficiency in modern quantitative finance, across the financial industry.


Group and affiliate discounts are available.
We work with partner universities for joint delivery of the ARPM Bootcamp. See here for the list of partner Universities.
Contact us for more information.

Instructors and Guests

ARPM training is led by Attilio Meucci and the ARPM staff. The Bootcamp and Marathon include guest lectures from well-known academics and financial industry quants.
Attilio Meucci

Attilio Meucci

ARPM Founder

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.

Javier Peña

Javier Peña

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.

Tai-Ho Wang

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

ARPM Researcher

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.

Til Schuermann

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.

Ugur Koyluoglu

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.

Stu Kozola

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

ARPM Researcher

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.



Our thousands of Alumni include senior executives from world-renowned banks such as Goldman Sachs and Morgan Stanley, funds such as BlackRock, Two Sigma and AQR, and a wide range of other professionals and academics with different backgrounds.


In addition to delivery through the Bootcamp and online programs at, ARPM's programs are also delivered by leading universities as credit coursework, and by financial institutions for the education and the growth of their talent pool. Contact us to learn more about the ARPM Academia and Corporate programs.

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