Quantitative Finance
About
MIDS in conjunction with Duke Math Department offer elective courses prepare students for career and academic research in the field of quantitative finance and actuarial science. Our mission is to equip students with a solid foundation in mathematical analysis and financial data modeling combined with programing languages like Python to solve practical problems in finance. Quantitative Finance is a field of study of using quantitative methods to solve problems in Finance such as those in Trading, Investment, Banking and Insurance. This is truly an interdisciplinary subject that ultimately involves Mathematics, Data Science, Statistics, Computer Science, Economics and Finance. One example is Algorithmic Trading, in which students learn how to develop trading and investment algorithms that automatically interact with financial markets to execute predefined investment objectives. Another closely related field is Actuarial Science, which is the study of mathematical and statistical analysis to the insurance business. For example, our course on Insurance gives a good introduction to Life Insurance business and related mathematics.
We have strong faculty support for the courses in quantitative finance and actuarial science. In addition to many full-time Duke Math faculty, we also have industry Executive in Residences in Quantitative Finance, who brings to students an extensive practice experiences in financial services industry such as trading, banking and insurance sectors.
Within MIDS program, students interested in Quantitative Finance are admitted through normal process and take all MIDS core courses. Then Quantitative Finance students are to focus their educational experiences on their topics of interest by enrolling in Quantitative Finance electives, industry speakers lectures and seminars. We believe such an approach blends well the core quantitative skills in Data Science with their applications to Finance.
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Our approach to education in quantitative finance are based on these three pillars:
Academic Courses
We offer wide range of foundational courses to equip students with solid quantitative skills from the introductory courses in probability and statistics as well as advanced courses in stochastic processes. We also offer course in Python and Machine Learning to develop skills in practical implementation of financial models. Currently we have select courses in quantitative finance and actuarial science.
Number | Title | |
---|---|---|
IDS/MATH 789 | Fundamentals of Finance Business Models | |
MATH 581 | Mathematical Finance | |
MATH 582 | Financial Derivatives | |
MATH 585 | Introduction to Algorithmic Trading – Financial Data and Modeling | |
IDS 690/MATH 590-02 | Special Topics: Case Studies in Quantitative Finance |
Industry Speakers
In certain courses such as those in Algorithmic Trading, as well as Insurance Business, we have regular industry speakers give lectures on topics relevant to the class and students’ interests. Many students find these lectures very informative as they bring fresh perspectives to the concepts and theories that they learn in the class. In addition, industry speakers also speak about their work experiences which many students find helpful to their career plan.
Industry speakers are an important part of the quantitative finance courses given the dynamic nature of the Finance Industry. These industry speakers share three latest developments in their perspective fields as well as providing value career and practical advice to Duke students. Here are select recent industry speakers:
Fall, 2023
Spring, 2023
- “Case Study on Failure of Amaranth Advisors” – Massimo Cutuli. Mr. Cutuli is the Chief Risk Officer at Optiver US, a derivatives market maker. Previously, he held the Head of Risk position for Citadel Securities; worked in banking at JP Morgan and Goldman Sachs. Massimo served as a member of the Chicago Mercantile Exchange and London Clearinghouse risk committees and currently serves on the Board of Trustees of the Astronaut Scholarship Foundation. He received a BS in Aerospace Engineering and an MS in Space Science (University of London), an MS in Aerospace Engineering (Cornell University) and MS in Operations Research (Columbia University).
- “Applications of Data Science in Capital Markets Activities” – Kevin Benson. Mr. Benson heads the Data Strategy & Analytics (DSA) group at RBC Capital Markets. The DSA group is responsible for various data science solutions, including AI and machine learning models for capital markets. Earlier in his career, he worked in securitization and structured products for Morgan Stanley and JPMorgan. Kevinholds a DPhil in Theoretical Physics from the University of Oxford and an AB in Physics from Harvard University
- “Risk and Quantitative Analysis at BlackRock” – Yan Chen. Mr. Chen is a Managing Director of BlackRock’s Risk & Quantitative Analysis group. He is the head of BlackRock’s U.S. Unconstrained Investment risk, including the flagship Global Allocation and Strategic Income Funds. Dr. Chen joined BlackRock in2007, including his time with Barclays Global Investors (BGI), which merged with BlackRock in 2009. Prior to joining BGI, he also worked at Lehman Brothers and AIG. Chen received his Ph.D. degree in Statistics from Duke University in 1997 under Dr. Mike West.
Student Projects
For those industry-focused Quantitative Finance courses such as Algorithm Trading, the most important part of the learning is the student-led projects. Students are divided into small groups and work together to solve real-world problems supervised by faculty of significant financial industry experiences. Students learn the value of teamwork in a simulated commercial environment with real deadlines to meet. Students are required to write a research paper on their project with both underlying theory as well as practical implementation results. An evaluation panel including industry practitioners in relevant fields to evaluate student’s final projects. Here are a select student projects for the Algorithmic Trading Class:
- Deep Learning for Structural Break Prediction in Equities Pairs Trading
- Trading Dispersion and Correlation
- Extreme Gradient Profit
- Arbitrage Opportunities between ADRs and underlying securities
- Pairs Trading Strategies with DBSCAN and other Clustering Methods
- Momentum Trading with volatility-based portfolio weighting scheme
- A delta-neutral trading strategy that exploits differences between historical and implied volatilities.
- Trading Volatility Using Options: A Portfolio of Strategies for Capturing Volatility Premiums in Index Options
Events
October 2, 2023 - Quantitative Investment and Related Career Paths
Monday, October 2, 2023
1:30-2:30 pm
Gross 330
Nicholas Alonso, CFA
Director, Multi Asset Investments
Nick Alonso will discuss key themes and trends of Quantitative Investment. He will share his own experiences and career path in this fascinating field as well as provide advice to students who are interested in pursuing a career in quantitative finance.
Mr. Alonso is a Director within the Multi Asset Investments team. He is responsible for quantitative model research, development and enhancements for PanAgora’s Multi Asset strategies. He is also responsible for the development and management of the firm’s Defensive Equity strategies, including alternative-beta and factor-based strategies. Mr. Alonso joined PanAgora from Mellon Capital Management (formerly Franklin Portfolio) where he was a Quantitative Analyst primarily responsible for research and management of Market Neutral Equity portfolios. Mr. Alonso is a CFA Charterholder.
Education:
University of Chicago, M.B.A.
University of Florida, B.S. (Physics)
University of Florida, B.A. (Mathematics)
October 9, 2023 - Lunch & Learn with Optiver
Monday, October 9, 2023
11:30 am-1:00 pm Presentations (Lunch provided)
Gross 330
Speakers include: Andrew Claxton, Quantitative Trader; Gergely Chikan, Software Engineer, and Massimo Cutuli, Chief Risk Officer.
Optiver, a premium trading firm, will host a discussion on quantitative trading as well as career opportunities at Optiver. This is a great opportunity to learn more about quantitative trading business in general and Optiver as a firm in particular.
October 20, 2023 - AI and Our Economic Future
Monday, October 20, 2023
11:30-12:30 pm
Gross Hall, 107
Joseph H. Davis, Ph.D.
Global Chief Economist and Global Head of the Investment Strategy Group, Vanguard
Joseph H. Davis, Ph.D., is Vanguard’s global chief economist and global head of the Investment Strategy Group. He leads teams that are responsible for Vanguard’s research and thought leadership agendas as well as the development and oversight of the firm’s investment methodologies and models.
Joe chairs the firm’s Strategic Asset Allocation Committee, which governs multi-asset-class investment solutions, and he is a member of the senior portfolio management team of Vanguard Fixed Income Group.
Joe is a frequent keynote speaker, has published white papers in leading academic and practitioner journals, and currently serves on the editorial board of The Journal of Portfolio Management and the Journal of Fixed Income.
Joe earned his B.A. summa cum laude from Saint Joseph’s University, earned his M.A. and Ph.D. in economics at Duke University, and is a graduate of the Advanced Management Program at The Wharton School of the University of Pennsylvania.
November 8, 2023 - The ESG debate: will those three letters change the world?
Wednesday, November 8, 2023
3:00-4:00 pm
Gross Hall, 330
Jacques Longerstaey
Head of TIAA Financial Risk and Chief Risk Officer (CRO) of Nuveen Investments (retired)
In December 2022, Jacques Longerstaey retired from his position as head of TIAA Financial Risk and Chief Risk Officer (CRO) of Nuveen Investments. Prior to joining TIAA/Nuveen in 2019, he held CRO responsibilities at Wells Fargo, State Street Global Advisors, Putnam Investments and Goldman Sachs Asset Management
Early in his career, Mr Longerstaey held various positions at J.P Morgan and Co. (economist and fixed income researcher for the Benelux, head of the Bond Index Group, developer of the RiskMetrics value-at-risk methodology).
Mr. Longerstaey holds a degree in Economics from the University of Louvain in Belgium. He is a member of the Board of Trustees of GARP (Global Association of Risk Professionals) and Chairman of their Compensation Committee. He is also a member of the Board of Trustees of the Eldredge Public Library in Chatham, MA.
People
David Ye – Associate Research Professor, Ph.D in Math, Duke University, 1991. David has held executive positions in several large financial institutions in his 25 years in the industry, including Chief Risk Officer for Nomura Americas and State Street Global Markets. He is currently teaching the Math 585 course on Algorithmic Trading and IDS/Math 789 Fundamentals of Finance Business Model.
Hengzhong Liu – Executive in Residence, who has held senior and executive level roles at Bank of America, Citigroup and two other major US banks, where he managed decision science and quantitative risk teams in the retail as well as wholesale sectors. He received his PhD in Financial Economics from the Graduate Center of City University of New York. He currently teaches IDS 690/ MAT 590-02 – Case Studies in Quantitative Finance with a focus on Data Science Applications to Retail Banking.
Xavier Mela – Holds a M.S. in Probability from the University Paris VI and a Ph.D. in Mathematics from the University of North Carolina at Chapel Hill. He has over 15 years of teaching a variety of math courses at Duke and UNC and is currently teaching the core mathematical finance courses, Math 581/582. In addition, he also teaches mathematics for economics at the SKEMA business school.
Jason Xue – Jason has over 20 years of experience in the insurance industry and is currently Global Head of Insurance Risk at MetLife, one of the largest insurance companies in the world. He taught the course on Fundamentals of Life Insurance. Jason holds a M.S in Theoretical and Applied Mechanics from University of Illinois at Urbana-Champaign, and a MS in Computer Science from Texas A&M University. He taught a similar course at Columbia University.
Student Project: Quant Finance
Watch this presentation from the Quant Finance student team on their work.