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QS Rank:

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416

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Stony Brook University

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New York

United States

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Program Rank

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18

Embarking on a journey through the Master of Science in Quantitative Finance program at Stony Brook University presents an unparalleled opportunity for students who aspire to excel in the vital intersection of finance and quantitative analysis. This program is meticulously crafted to equip students with a robust understanding of financial theories, advanced quantitative research methods, and the practical tools necessary to navigate the complexities of the financial world. As the global economy continues to evolve, the need for skilled professionals who can analyze financial data and derive actionable insights has never been more critical. Stony Brook University stands out as a beacon for aspiring finance professionals, offering a comprehensive curriculum that blends theoretical knowledge with real-world applications.


The curriculum of the Master of Science in Quantitative Finance program is both rigorous and dynamic. Students can expect to delve into a range of specialized courses, including Financial Derivatives, Risk Management, and Advanced Econometrics, among others. Each course is designed to challenge students to think critically and quantitatively, allowing them to tackle complex financial issues. Additionally, practical training is incorporated throughout the program, with opportunities to engage in hands-on projects and simulations that mirror current industry practices. This comprehensive approach ensures that graduates are not only knowledgeable but also adept at applying their knowledge in real-world scenarios.


One of the key strengths of this program is the esteemed faculty who are experts in their respective fields. The professors at Stony Brook University bring a wealth of experience and knowledge, having worked in both academia and the finance industry. Their diverse backgrounds enrich the learning experience, making it both relevant and insightful. Furthermore, faculty members actively encourage student participation in research projects, allowing students to work closely with them and gain valuable mentorship. This collaborative environment fosters a culture of inquiry and innovation, preparing students for successful careers in the financial sector.


Research opportunities are plentiful within the program, as Stony Brook University is home to state-of-the-art research facilities and resources. Students can engage in cutting-edge research initiatives, often collaborating with industry partners and contributing to significant projects. These research opportunities not only strengthen the academic foundation of students but also enhance their marketability to prospective employers. The university's commitment to fostering a research-centric learning environment ensures that students remain at the forefront of advancements in finance and quantitative analysis.


Moreover, the program boasts strong industry connections, which play a crucial role in enhancing students' career prospects. Stony Brook University maintains partnerships with leading financial institutions, providing students with unique internship possibilities during their studies. These internships are essential for gaining practical experience and establishing professional networks. Students have the chance to apply their quantitative skills in real-world settings, working alongside seasoned professionals and gaining insights into the workings of the finance industry. The combination of academic knowledge and practical experience positions graduates favorably in the job market, leading to a variety of career pathways.


The career outcomes for graduates of the Master of Science in Quantitative Finance program are promising, with a wide array of job roles available upon completion. Graduates typically pursue careers in quantitative analysis, risk management, data analysis, and financial consulting, among other sectors. Moreover, alumni from this program have a strong track record of securing positions at top financial firms, demonstrating the program's effectiveness in preparing students for successful careers. Testimonials from alumni highlight the transformative impact of the program, emphasizing how the knowledge and skills acquired have propelled them into rewarding careers in finance.


In conclusion, the Master of Science in Quantitative Finance at Stony Brook University is an exceptional choice for those seeking a comprehensive education in finance. The program's emphasis on research, practical learning, and collaboration with industry leaders sets it apart from other offerings. Students benefit from a robust curriculum, exceptional faculty expertise, ample research opportunities, and strong industry connections, all of which contribute to a well-rounded educational experience. For aspiring finance professionals, this program provides the knowledge and skills necessary to thrive in a competitive job market.


Why Study Quantitative Finance at Stony Brook University


  • A popular choice for international students: Stony Brook University boasts a diverse community that enriches the learning experience, making it an attractive destination for global students.
  • Learn from renowned experts: Students have the opportunity to learn from faculty members who are leaders in finance and quantitative analysis, providing invaluable insights and mentorship.
  • Advanced research facilities: The university offers high-end labs and resources that facilitate cutting-edge research, enabling students to engage in innovative projects.
  • Strong placement programs: The university's connections with leading firms ensure excellent job placement opportunities for graduates, often leading to immediate employment in the finance sector.

In terms of admission requirements, prospective students should be mindful of the deadlines and necessary documentation. Applicants are typically required to submit a completed application form along with a fee of $100. Additionally, international applicants must provide proof of English language proficiency, as demonstrated by standardized tests such as IELTS or TOEFL, with minimum scores of 6.5 and 80, respectively. Enrolling in this program is a significant step towards a successful career in quantitative finance, making it essential for candidates to prepare thoroughly and meet all application requirements.


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Total Tuition Fees

$45,000

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Duration

18 Months

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Median Salary

$1,10,000

Ranking

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#77

US World and News Report

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#416

QS World University Rankings

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Intake

Fall ( Sept - Nov )

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Spring ( Apr - June )

Class Profile

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Class Size

25

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Average Age

26

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Average Work Experience

2 Years

Diversity

California:

20%

Florida:

5%

New York:

40%

Texas:

10%

Illinois:

3%

Others:

22%

Career Outcomes

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Median Earnings After Graduation

$1,10,000 / year

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Graduation Rate

76%

Prospective Job Roles

Quantitative Researcher

Director of Financial Aid

China Finance Analyst

Financial Crime Investigator

Financial Advisor

Quantitative Analyst

Finance

Manager of Finance

Finance Director

Quantitative Risk Analyst

Quantity Surveyor

Financial Controller

Top recruiters

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Eligibility Criteria

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At least 3 / 4 undergraduate GPA is expected.

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At least 16 years of bachelor degree.

English Proficiency Tests

  • IELTS

    6.5

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  • TOEFL

    80

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Application Requirements

Here's everything you need to know to ensure a complete and competitive application—covering the key documents and criteria for a successful submission.

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Application Fee: 100

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    Transcript

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    Statement of Purpose

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    Resume

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    IELTS

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    Academic LOR

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    Professional LOR

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    Academic LOR

Application Deadlines

Standard DeadlineConsideration
FallJul 15, 2025Dec 15, 2024
SpringOct 15, 2024N/A

Fees and Funding

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Tuition Fees

$30,000 / year

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Overall Cost

$46,000 / year

FAQs

  • It is possible to be admitted as a Part-Time Student, however, there is no organized part-time program per se which will guarantee that all of the required classes are available in the evening. Thus, successful completion of the MS program will typically require some daytime classes.

  • AMS offers a BS, an MS and PhD degrees as well as Advanced Graduate Certificates in various fields. Various programs exist as tracks within the AMS Department and not as separate degree programs. Upon successful completion, you will be awarded a degree in Applied Mathematics and Statistics.

  • A strong background in Applied Mathematics and Statistics and the interdisciplinary nature of the AMS department gives students unusual advantages and flexibility; e.g. a student interested in portfolio management may work with a professor in Operations Research who specializes in Optimization. Another, who wishes to study methods for using market data to calibrate Options models might interact with a faculty member in Statistics. And a third, who wants to explore Parallel Computing in Monte Carlo techniques might work with a professor in Computational Applied Mathematics or Computer Science.

  • The training in Quantitative Finance focuses on the following aspects: The required courses cover standard topics in QF including investment science, portfolio optimizations, financial time series, pricing theory, interest rate models, high-frequency trading, risk management and so on. Students can follow different course sequences to master their knowledge in different areas of QF. Elective courses are split into five areas: A) Stochastic calculus, optimization and operations research B) Statistics and data analytics C) Computational methods and algorithms D) Advanced topics in risk management, high frequency trading E) Machine learning and big data QF Courses are taught by top academic professors and experienced financial practitioners. Students are exposed to various research and practical problems and can interact with both academic faculty and practitioners.

  • Quantitative Finance is an applied science dealing with the application of Mathematics and Computer Science in the finance sector. The discipline is also known as Financial Mathematics, Financial Engineering and Computational Finance, depending upon the problems or techniques emphasized.

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