Computational & Mathematical Finance

The computational and mathematical finance concentration combines financial theory with a solid grounding in quantitative methods, as you model and analyze the complexity of financial decisions under uncertainty.

Where the Computational & Mathematical Finance Concentration Takes You

It’s a great path for those interested in careers in risk management, asset management, trading, investment banking, commercial banking, corporate finance consulting, and strategic planning.

What You Will Study

This concentration blends the best of Babson’s curriculum, with strong foundations in the business world, math, and the liberal arts and sciences. Advanced finance courses are designed to provide in-depth knowledge of financial markets and instruments, while advanced math and science courses emphasize mathematical derivations, rigorous analytical thinking, state-of-the-art software tools, and building statistical, machine learning, simulation, and optimization models.

Required Courses

This course is an introduction to simulation and optimization techniques that enable marketing, finance, and management professionals to make optimal decisions under uncertainty. You will acquire a foundational understanding of the theoretical background for these techniques, as well as experience implementing them with software tools that are widely used in the financial industry. Classes draw on examples such as asset allocation under different definitions of risk; index tracking; derivative pricing, hedging, and arbitrage.


As part of your coursework in the computational & mathematical finance concentration, you will take:

Today, businesses know that to remain competitive, they have to use advanced analytic tools in their decision-making process. In this course, you work with unstructured data and apply tools like random forests and artificial neural networks. You also get a chance to build out your coding skills, so you don’t just understand the data but you understand the technology you are using.

This course is designed to introduce key financial technology and its applications in financial services. You will develop a broad and solid understanding of the recent innovations in FinTech, and their benefits and limitations. You will also experience hands-on problem solving that will be useful in FinTech ventures.

Explore the entire list of technology entrepreneurship courses

Who You Will Learn From

At Babson, our faculty are experts, innovators, and forward thinkers in their chosen fields. Here are just some professors sharing their expertise and support with our students.

Richard Bliss, Professor, National Academic Director - Goldman Sachs 10,000 Small Businesses

Richard Bliss

Dr. Bliss has been involved in corporate and entrepreneurial finance since 1987, with industry experience that includes time at Touche Ross & Company in New York as a consultant, and senior financial positions at Van Camp Seafood Company and Safety One, Inc., a specialty chemicals start-up. He teaches at the undergraduate, MBA, and executive levels, specializing in the areas of Corporate Financial Strategy, Sustainability, Risk Management, and Entrepreneurial Finance. Most recently, Dr. Bliss is a member of the Babson team helping to develop and deliver the curriculum for the Goldman Sachs 10,000 Small Businesses Program, a US$500 million initiative designed to create jobs and spur economic activity through greater access to business education, mentors, networks and financial capital. With publications in the areas of corporate finance, entrepreneurship, and banking, Dr. Bliss has an active research agenda. His current research considers the impact of gender teamwork on mutual fund manager investment decisions.

Dessislava Pachamanova

Dessislava Pachamanova

Dr. Pachamanova is Professor and Zwerling Family Endowed Term Chair in the Mathematics, Analytics, Science and Technology Division. Her research and consulting span multiple fields, including robust optimization, risk management, simulation, predictive analytics and machine learning, natural language processing, and operations. Dr. Pachamanova has collaborated with quantitative strategy groups at a number of financial institutions. She has coauthored three books in computational finance and risk management and published dozens of articles in operations research, finance, accounting, engineering, marketing and management journals, including in top academic and practitioner outlets. Dr. Pachamanova teaches courses in analytics and computational finance in the undergraduate and the MBA programs, and cares deeply about creating a valuable learning experience for students. She co-designed Babson's computational finance and business analytics concentration curricula, co-chaired the design task force for a Masters program in Business Analytics, and co-developed the Business Analytics and Machine Learning MBA concentration.

Have Questions?

Faculty Contacts: Dessislava Pachamanova and Richard Bliss
Sponsoring Divisions: Mathematics, Analytics, Science, and Technology and Finance

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