Core modules establish the foundations while advanced modules cover topics such as energy and credit risk, financial risk management, robust methods and market microstructure. The core modules cover the mathematical foundations of probability, statistics and partial differential equations, stochastic calculus and martingale theory, portfolio theory, the Black-Scholes model and extensions, numerical methods (finite differences and Monte Carlo), interest rate modelling, stochastic optimisation, exotic derivatives and stochastic volatility.
MATLAB is used as a practical computing language. Attendance at the four core modules is compulsory. For each module there is an assignment for which feedback and an indicative mark is given to assist you in improving your future performance. Assessment for these compulsory modules consists of two two-hour written examinations held in September of the first year. Each of the advanced modules explores a key area in contemporary mathematical finance.
The programme of advanced modules is published in July each year, and you will be asked to register your choice of three modules. Attendance at these three assessed modules is compulsory. Advanced modules will be assessed by short -special project- reports, each submitted on a subject chosen by you that is covered in the module. You will complete a dissertation on a topic chosen in consultation with your supervisor and the Course Director.
The MSc aims to develop students' modelling, mathematical and computational skills in applications to finance. It covers the most important technical and quantitative aspects of finance in regular use in banks and other financial institutions, from basic material to current research. Material on related subjects is included to enable students to make intellectual links between different topics. There is a substantial transfer of technology from applied mathematics, pure mathematics, statistics, computing and corporate finance.
By choosing relevant advanced modules and dissertation topics, students can apply their studies directly and concurrently to their areas of expertise at work. Suitable work projects can be approved as dissertation topics, supervised jointly by a member of the faculty and a qualified work colleague.
The course, like the full-time MSc in Mathematical and Computational Finance, is run by the Mathematical and Computational Finance Group, at the Mathematical Institute, University of Oxford.
· Knowledge and Understanding
· Cognitive / Intellectual Skills
· Transferable / Key Skills
· Discipline-specific Practical Skills
· Formulation of suitable mathematical models for new problems
· Identification and implementation of accurate and stable computational methods
· Calibration of models to market data
· Assessment of the validity and limitations of models
· Lectures, including some by guest experts
· Practical sessions
· Guided reading
· Course assignments
· Dissertation
Most students will complete the 28 month (7 term) course in the following time frame:
· January Year 1 to September Year 1:
o January to June inclusive: Students attend 4 compulsory core modules, each of 5 days duration, for which attendance in Oxford is required, and complete related assignments at home afterwards
o September: examinations, for which attendance for 1 day in Oxford is required. Module 5, an advanced moduleusually starts the day after the day of examinations, so students who elect to take that module are spared unnecessary travel.
· September Year 1 to June Year 2
o Students select 3 out of 4 advanced modules, each of 4 days' duration, for which attendance in Oxford is required, and complete related assignments at home afterwards
· July Year 2 to April Year 3:
o Students work on their dissertations at home
University of Oxford, United Kingdom
Core modules establish the foundations while advanced modules cover topics such as energy and credit risk, financial risk management, robust methods and market microstructure. The core modules cover the mathematical foundations of probability, statistics and partial differential equations, stochastic calculus and martingale theory, portfolio theory, the Black-Scholes model and extensions, numerical methods (finite differences and Monte Carlo), interest rate modelling, stochastic optimisation, exotic derivatives and stochastic volatility.
MATLAB is used as a practical computing language. Attendance at the four core modules is compulsory. For each module there is an assignment for which feedback and an indicative mark is given to assist you in improving your future performance. Assessment for these compulsory modules consists of two two-hour written examinations held in September of the first year. Each of the advanced modules explores a key area in contemporary mathematical finance.
The programme of advanced modules is published in July each year, and you will be asked to register your choice of three modules. Attendance at these three assessed modules is compulsory. Advanced modules will be assessed by short -special project- reports, each submitted on a subject chosen by you that is covered in the module. You will complete a dissertation on a topic chosen in consultation with your supervisor and the Course Director.
The MSc aims to develop students' modelling, mathematical and computational skills in applications to finance. It covers the most important technical and quantitative aspects of finance in regular use in banks and other financial institutions, from basic material to current research. Material on related subjects is included to enable students to make intellectual links between different topics. There is a substantial transfer of technology from applied mathematics, pure mathematics, statistics, computing and corporate finance.
By choosing relevant advanced modules and dissertation topics, students can apply their studies directly and concurrently to their areas of expertise at work. Suitable work projects can be approved as dissertation topics, supervised jointly by a member of the faculty and a qualified work colleague.
The course, like the full-time MSc in Mathematical and Computational Finance, is run by the Mathematical and Computational Finance Group, at the Mathematical Institute, University of Oxford.
· Knowledge and Understanding
· Cognitive / Intellectual Skills
· Transferable / Key Skills
· Discipline-specific Practical Skills
· Formulation of suitable mathematical models for new problems
· Identification and implementation of accurate and stable computational methods
· Calibration of models to market data
· Assessment of the validity and limitations of models
· Lectures, including some by guest experts
· Practical sessions
· Guided reading
· Course assignments
· Dissertation
Most students will complete the 28 month (7 term) course in the following time frame:
· January Year 1 to September Year 1:
o January to June inclusive: Students attend 4 compulsory core modules, each of 5 days duration, for which attendance in Oxford is required, and complete related assignments at home afterwards
o September: examinations, for which attendance for 1 day in Oxford is required. Module 5, an advanced moduleusually starts the day after the day of examinations, so students who elect to take that module are spared unnecessary travel.
· September Year 1 to June Year 2
o Students select 3 out of 4 advanced modules, each of 4 days' duration, for which attendance in Oxford is required, and complete related assignments at home afterwards
· July Year 2 to April Year 3:
o Students work on their dissertations at home
University of Oxford, United Kingdom
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