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Students
Tuition Fee
GBP 29,950
Per year
Start Date
Medium of studying
On campus
Duration
24 months
Program Facts
Program Details
Degree
Masters
Major
Mathematics | Probability Theory | Statistics
Area of study
Mathematics and Statistics
Education type
On campus
Timing
Full time
Course Language
English
Tuition Fee
Average International Tuition Fee
GBP 29,950
Intakes
Program start dateApplication deadline
2023-09-192023-08-01
2024-01-092023-12-01
2024-09-01-
2025-09-01-
About Program

Program Overview


The Financial Mathematics MSc program at Queen Mary University of London equips students with the knowledge and skills to tackle complex financial problems. The program emphasizes a practical approach, combining theoretical knowledge with real-world applications through case studies, industry projects, and guest lectures. Graduates are prepared for careers in investment banking, quantitative finance, risk management, and other related fields. The program is taught by a team of experienced researchers and practitioners and offers a variety of elective modules to specialize in specific areas of interest.

Program Outline


Degree Overview:


Financial Mathematics MSc

The Financial Mathematics MSc program at Queen Mary University of London equips students with the knowledge and skills to tackle complex financial problems and thrive in the competitive financial services industry. The program provides a comprehensive foundation in financial mathematics, quantitative analysis, and programming, preparing graduates for a variety of careers in investment banking, quantitative finance, risk management, and other related fields. The program is designed for students with a strong background in mathematics, statistics, physics, economics, engineering, or computer science. It emphasizes a practical approach, combining theoretical knowledge with real-world applications through case studies, industry projects, and guest lectures from leading professionals.


Objectives:

  • Provide students with a solid understanding of the theoretical foundations of financial mathematics.
  • Develop students' quantitative analysis and programming skills.
  • Equip students with the ability to apply financial mathematics to solve real-world problems.
  • Prepare students for successful careers in the financial services industry.

Key Features:

  • Taught by a team of experienced researchers and practitioners.
  • Strong emphasis on practical applications.
  • Offers a variety of elective modules to specialize in specific areas of interest.
  • Excellent career support and industry connections.

Outline:


Structure:

The Financial Mathematics MSc program is a one-year full-time program consisting of taught modules, an industry project, and a dissertation.


Modules:

  • Shared Core Modules:
  • Financial Instruments and Markets
  • Foundations of Mathematical Modelling in Finance
  • Machine Learning with Python
  • Programming in C++ for Finance
  • Investment Management and Data Analytics Stream:
  • Advanced Machine Learning
  • Digital and Real Asset Analytics
  • Two additional elective modules
  • Quantitative Pricing, Development and Research Stream:
  • Advanced Derivatives Pricing and Risk Management
  • Advanced Computing in Finance
  • Two additional elective modules
  • Project:
  • An industry-focused project, allowing students to apply their knowledge and skills to real-world problems.
  • Dissertation:
  • A research-based dissertation on a chosen topic in financial mathematics.

Course Schedule:

The program typically follows a semester-based structure, with teaching taking place during the fall and spring semesters. The summer semester is dedicated to project work and dissertation research.


Foundations of Mathematical Modelling in Finance:

This module covers the fundamental mathematical concepts and techniques used in financial modelling, including stochastic calculus, probability theory, and numerical methods.


Machine Learning with Python:

This module introduces students to the principles and methods of machine learning, with a focus on using Python for data analysis and model building.


Programming in C++ for Finance:

This module teaches students how to program in C++, a high-performance programming language widely used in the financial services industry.


Advanced Machine Learning:

This module delves deeper into advanced machine learning techniques, including deep learning, reinforcement learning, and natural language processing.


Digital and Real Asset Analytics:

This module explores the use of data analytics in various asset classes, including digital assets, real estate, and commodities.


Advanced Derivatives Pricing and Risk Management:

This module covers advanced topics in derivatives pricing, risk management, and quantitative modeling for various types of derivatives.


Advanced Computing in Finance:

This module introduces students to advanced computing techniques used in finance, including high-performance computing, cloud computing, and parallel processing.


Elective Modules:

Students can choose from a variety of elective modules to specialize in specific areas of interest, such as:

  • Bayesian Statistics
  • Bond Market Strategies
  • Credit Ratings
  • Financial Data Analytics
  • Neural Networks and Deep Learning
  • Risk Management for Banking
  • Systematic Trading Strategies

Assessment:

The assessment methods for the Financial Mathematics MSc program vary depending on the module. Typically, assessments include a combination of:

  • Exams: Some modules may include written exams, which test students' understanding of key concepts and theories.
  • Coursework: Students may be required to complete various assignments, projects, and presentations throughout the program.
  • Project: The industry project is assessed based on the quality of the research, analysis, and presentation.
  • Dissertation: The dissertation is assessed based on the originality of the research, the quality of the analysis, and the clarity of the writing.

Teaching:


Teaching Methods:

The Financial Mathematics MSc program uses a variety of teaching methods, including:

  • Lectures: Lectures are used to introduce key concepts and theories.
  • Seminars: Seminars provide students with an opportunity to discuss course material, ask questions, and engage in critical thinking.
  • Guest Lectures: Industry professionals are invited to share their expertise and provide insights into the real-world applications of financial mathematics.

Faculty:

The program is taught by a team of experienced researchers and practitioners. The faculty members have a strong academic background and extensive experience in the financial services industry.


Unique Approach:

The program emphasizes a practical approach, combining theoretical knowledge with real-world applications. Students are encouraged to apply their knowledge to case studies, industry projects, and independent research.


Careers:


Potential Career Paths:

The Financial Mathematics MSc program prepares students for a variety of careers in the financial services industry, including:

  • Quantitative Analyst
  • Risk Management Analyst
  • Investment Analyst
  • Portfolio Manager
  • Trader
  • Data Scientist
  • Financial Consultant

Career Support:

The School of Mathematical Sciences provides students with a range of career support services, including:

  • Careers guidance and workshops
  • One-to-one career consultations
  • Employer presentations and networking events
  • Internship opportunities
  • Alumni network

Study Options:

The Financial Mathematics MSc program is offered as a full-time program.


Location:

The program is taught at the Queen Mary University of London campus in Mile End, London.


Program Length:

The program is one year in duration.


Program Start Date:

The program typically starts in September.


Application Deadline:

The application deadline for the program is typically in July.

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