MSc Quantitative Finance

1 Year On Campus Masters Program

University of Manchester

Program Overview

The MSc Quantitative Finance of the University of Manchester is a one-year, full-time highly specialized course designed for students interested in becoming specialists in advanced skills required in the banking industry. The course offers intense study of financial theory, quantitative methods, and computational techniques and equips graduates with the skills to deal with advanced financial problems. It is perfect for those seeking careers in investment banks, hedge funds, risk management, or financial technology.

Curriculum Structure:
The University of Manchester's MSc Quantitative Finance combines theoretical firm foundations with real-world application to prepare students with the knowledge to tackle real-world financial challenges. The curriculum seeks to provide comprehensive knowledge in quantitative finance utilizing the following modules:

Core Modules: From Financial Mathematics to Stochastic Processes, and Derivative Pricing, these modules establish a solid grounding in financial mathematics and its applications in the real world.

Quantitative Methods: Students will learn advanced statistical, econometric, and machine learning techniques, which are applied in financial markets directly. The goal is to equip students with the quantitative skills necessary to handle complex financial data.

Computational Finance: It deals with the study of programming methods through applying real-world approaches utilizing industry-focused software such as Matlab and Python. Students can analyze financial data and design financial models by applying these programming languages, thus gaining practical experiential knowledge in computational finance.

Dissertation: An integral component of the course, the dissertation allows students to develop a thorough understanding of a real-world financial problem, applying the knowledge and skills gained during the course to research and analyze current financial problems.

Accreditation:
The MSc Quantitative Finance qualification is accredited by professional bodies to confirm that it is industry standard and provides students with the skills that are most needed in the finance sector. Accreditation adds value to the qualification and enhances the employability value of graduates.

Campus Location:
The University of Manchester is located in the city center of Manchester, one of the UK's leading finance, business, and technology cities. The university provides students with access to up-to-date facilities, including finance labs and computer facilities, that contribute to the learning process by practice. Being located in a vibrant city means that students are also well connected to financial institutions, providing them with opportunities for networking and career progression.

 

Experiential Learning (Research, Projects, Internships etc.)

The MSc Quantitative Finance programme specifically focuses on the application of theoretical concepts to practical problems in real-world contexts, with various opportunities for students to develop hands-on experience:

Research Opportunities: Students can work with members of academic staff on cutting-edge research, with the aim of creating new financial models and theory. This can lead to publication and presentation opportunities at finance conferences.

Internships: The program is strongly affiliated with major financial institutions, and through these institutions, the students receive exposure to internships in leading firms such as Goldman Sachs, J.P. Morgan, and HSBC. The internships offer hands-on exposure, industry exposure, and exposure to develop real professional connections.

Group Projects: Students work on group projects throughout the course that are based on real financial problems. These projects improve teamwork, problem-solving, and communication skills, all of which are crucial for success in the finance industry.

Guest Lectures and Seminars: Regular guest lectures and seminars by industry experts and professionals give students a continuous update of the latest developments in finance and quantitative techniques.

 

Progression & Future Opportunities

The University of Manchester's Career Services provides excellent assistance to MSc Quantitative Finance students throughout and after studies, including:

Career Counselling: Qualified advisers assist students in determining career options best matched to their skills and interests, providing one-to-one advice on how to succeed in the very competitive finance industry.

CV and Interview Preparation: One-to-one and workshop sessions enable students to learn how to market themselves to the best effect in job applications, interviews, and networking.

Industry Networking: Students are able to attend career fairs, employer networking events, and on-campus recruitment interviews, where they can network with the representatives of top financial institutions.

Employability
MSc Quantitative Finance graduates are highly prized by top employers in the finance sector. The sophisticated computational and quantitative skills acquired by students make them ideal candidates for investment banking, asset management, hedge funds, and risk management positions. Graduates have gone on to work for top firms such as Barclays, BlackRock, and Goldman Sachs.

Academic Progression:
After the acquisition of the MSc Quantitative Finance, the students can also continue their career in academics by pursuing a PhD in Quantitative Finance, Financial Mathematics, or any other area related to their field. On the other hand, graduates may choose to take postgraduate courses such as an MBA with specialization in Financial Management or other fields related to the subject to advance their career.

Program Key Stats

£35,000
Sept Intake : 31st May


42 %
No
No

Eligibility Criteria


110
165
165
700
7.0
100
2:1
1300
29

Additional Information & Requirements

Career Options

  • Investment Banker
  • Risk Manager
  • Quantitative Analyst
  • Financial Engineer
  • Portfolio Manager
  • Asset Manager
  • Data Scientist
  • Financial Software Developer
  • Hedge Fund Analyst
  • Algorithmic Trader
  • Credit Risk Analyst
  • Financial Consultant
  • Derivatives Trader
  • Financial Researcher
  • Financial Data Analyst

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