Advanced Risk and ℙortfolio Management®
Quant Marathon
In-depth, master-level online program in modern quantitative finance
Quant Bootcamp | Quant Marathon | |
---|---|---|
Topics | Data Science Mathematics Data Science Foundations Advanced Data Science Data Science for Finance Financial Engineering for Investment Quantitative Risk Management Quantitative Portfolio Management | |
Lab |
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Depth | Understanding | Deep knowledge |
Location | Streaming | In Person (**) | On Demand | Online |
Modularity | 1 course | 7 courses |
When | Live Aug 16-21 | On demand anytime | Starts Feb 15 | Sep 6 |
Length | Streaming/In Person: 5 days On Demand: part time |
1-4 semesters |
Intensity | Streaming/In Person: full time On Demand: part time |
Part time |
Guidance | Recorded and Live (*) Sessions | Live instructor |
Guest Lectures from Leading Industry Quants (*) | Guest Lectures from Leading Industry Quants | |
30 hrs recorded lectures | 150hrs recorded lectures | |
24hr Q&A service | 24hr Q&A service | |
- | Human-graded homework | |
Progress tracking | Progress tracking | |
Networking | Large class | Small class + Alumni |
(*) Live instructor sessions are not included in Quant Bootcamp On Demand |
Overview
The Advanced Risk and Portfolio Management (ARPM) Quant Marathon is a master-level program that:
- Provides in-depth training across all fields of modern quantitative finance, applicable to asset management, banking and insurance
- Enables mastery of topics across theory and implementation and the ability to create models anew
Instruction
The ARPM Quant Marathon is delivered on the ARPM Lab.
The program includes the most advanced quantitative techniques in:
Econometrics
Factor modeling
Portfolio construction
Investment risk management
Liquidity modeling
Enterprise risk management
To ensure a balanced mix of theory and applications, the curriculum is best taught through seven all-encompassing, mutually exclusive, core learning courses 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.
Practice
All the core courses of the ARPM Quant Marathon include access to the ARPM Lab.
The ARPM Lab contains the study materials to learn and practice all the concepts introduced during the lectures.
Guidance
During the Quant Marathon we provide you with access to ARPM's Virtual Classroom, which includes:
- Live flipped classroom lectures with breakout sessions
- 150 hours of recorded lectures
- 24 hour Q&A forum for theory and code questions
- Human-graded homework assignments
- Networking e-Café/chat with a group of like-minded attendees
- Personal trainer's reminders
- Detailed progress tracking
Before you begin, we can customize an itinerary to divide your workload across one or more terms and provide a detailed weekly schedule.
Certification
- Data Science Mathematics
- Data Science Foundations
- Data Science for Finance
- Financial Engineering for Investment
- Advanced Data Science
- Quantitative Risk Management
- Quantitative Portfolio Management
- Active engagement in ARPM Lab
- Forum Q&A participation
- Live classroom participation
- Homework
Further, the ARPM Quant Marathon prepares the participants for the examination-based comprehensive ARPM Certificate. The ARPM Certificate examinations are sold at a special price when purchased together with the Quant Marathon.
In addition, GARP certified FRMs earn 40 CPD credits upon completion of each Quant Marathon core course.
Discount
- Group and affiliate discounts are available. Refer to Pricing
- We also deliver the ARPM Quant Marathon as in-house training to corporations with itinerary customization, tailored to suit their requirements.
Instructors

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
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.

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.

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 Quant 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.

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.

Sophie King
ARPM Researcher
Sophie King is a researcher at ARPM, where she develops and delivers course materials, with a focus on straightforward communication. Sophie earned a Bachelor of Science in Mathematics from the Australian National University and a Master of Applied Statistics from Macquarie University. Her prior experience includes 7 years of statistical modeling in the insurance and marketing industries..

Milena Kojić
ARPM Researcher
Milena Kojić is a researcher and lead of the Data Visualization Center at ARPM. She received a Ph.D. in Stochastic optimization, M.S. in Applied Mathematics, and a B.S. in Financial Mathematics at the Department of Mathematics and Informatics, Faculty of Sciences, University of Novi Sad, Serbia. Her research interests revolve around numerical optimization, data mining, and statistical/mathematical modeling. Prior to ARPM, Milena has more than 8 years of experience in university-level teaching and research. She is co-founder of the R-ladies Novi Sad group which is a part of R-ladies’ global community.
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In addition to delivery through the Quant Bootcamp and online programs at arpm.co, 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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