Science

Master of Science in Mathematical Finance and Risk Analysis

The Master of Science in Mathematical Finance and Risk Analysis is a postgraduate programme that prepares professionals for advanced practice in quantitative finance, risk management, and financial analytics. The programme combines finance theory with applied mathematics, statistics, computing, and computational methods.

Core areas include financial markets, discrete time finance, stochastic calculus, asset pricing, portfolio optimisation, statistical models, computational methods, machine learning in finance, risk management, and dissertation. Students engage with both theoretical and practical work through coursework, computational projects, and research.

The programme is offered by Strathmore University through the Institute of Mathematical Sciences. Strathmore is a private university offering the programme over four academic semesters plus a dissertation project.

Students develop competencies in quantitative finance, risk analytics, computational modelling, asset pricing, and machine learning applications in finance. The programme includes 16 course units, examinations, computational projects, and a supervised dissertation, preparing graduates for analytical roles in the finance industry and academic research.

Strathmore charges approximately KES 834,600 total for the programme, paid over six semesters (~KES 417,300/year). Entry requires a Bachelor's degree with at least Second Class Honours in mathematics, statistics, finance, economics, or related fields from a recognised institution.

Graduates pursue careers as quantitative analysts, risk managers, investment analysts, financial modellers, data scientists, and lecturers in mathematical finance across investment banks, insurance companies, regulatory bodies, government agencies, and universities.

Skills Required

Quantitative Finance and Modelling
Risk Analytics and Management
Stochastic Calculus and Continuous Time Finance
Asset Pricing and Portfolio Optimisation
Statistical Methods in Financial Markets
Computational Methods in Finance
Machine Learning Applications in Finance
Financial Markets and Instruments
Programming in MATLAB, Python, R, and C++
Academic Writing and Dissertation Research

Key Subjects

Financial Markets and Instruments
Discrete Time Finance Methods
Stochastic Calculus and Continuous Time Finance
Asset Pricing and Portfolio Optimisation
Statistical Models in Financial Markets
Computational Methods in Finance
Machine Learning with Applications in Finance
Risk Management and Analytics
Seminar Series in Finance
Dissertation Research

Certifications

GARP FRM Certification
CFA Charter

Specializations

Quantitative Finance

Focuses on quantitative finance, covering modelling, pricing, derivatives, analytics, and managing quantitative finance.

Risk Analytics

Examines risk analytics, covering assessment, modelling, management, compliance, and managing risk analytics.

Computational Finance

Covers computational finance, covering methods, programming, modelling, simulation, and managing computational finance.

Asset Pricing

Focuses on asset pricing, covering models, valuation, markets, portfolios, and managing asset pricing.

Machine Learning in Finance

Examines machine learning in finance, covering algorithms, models, applications, analytics, and managing ML in finance.

Investment Banking Analytics

Covers investment banking analytics, covering analysis, modelling, valuation, risk, and managing investment analytics.

Duration: 2 years
Public, up to: Ksh 295,800
Private, up to: Ksh 325,000
Job market: High

The programme

What you study, how long it takes, and how it is delivered.

Practicalities

Study mode: Full-time, Part-time
Attachment: 0 months
Average class: 15 students
Award: Masters

What you study

10 subjects

Financial Markets and Instruments
Discrete Time Finance Methods
Stochastic Calculus and Continuous Time Finance
Asset Pricing and Portfolio Optimisation
Statistical Models in Financial Markets
Computational Methods in Finance
Machine Learning with Applications in Finance
Risk Management and Analytics
Seminar Series in Finance
Dissertation Research

Modules

12 in the programme

Financial Markets and Instruments
Year 1Semester 13 creditsCore
Examines instruments, markets, trading, valuation, and understanding financial markets and instruments.
Discrete Time Finance Methods
Year 1Semester 13 creditsCore
Covers models, pricing, derivatives, arbitrage, and managing discrete time finance.
Statistical Models and Methods in Financial Markets
Year 1Semester 13 creditsCore
Examines statistics, models, markets, analysis, and managing statistical models in financial markets.
Computational Methods in Finance
Year 1Semester 13 creditsCore
Covers programming, modelling, simulation, algorithms, and managing computational finance using MATLAB, Python, R, and C++.
Stochastic Calculus and Continuous Time Finance
Year 1Semester 23 creditsCore
Examines calculus, processes, models, derivatives, and managing continuous time finance.
Asset Pricing and Portfolio Optimisation
Year 1Semester 23 creditsCore
Covers models, valuation, portfolios, optimisation, and managing asset pricing and portfolios.
Machine Learning with Applications in Finance
Year 1Semester 23 creditsCore
Examines algorithms, models, applications, analytics, and managing machine learning in finance.
Risk Management and Analytics
Year 1Semester 23 creditsCore
Covers assessment, modelling, management, compliance, and managing risk analytics.
Seminar Series in Finance
Year 2Semester 13 creditsCore
Examines current issues, research, practice, trends, and engaging with finance industry experts.
Financial Derivatives and Pricing
Year 2Semester 13 creditsCore
Covers derivatives, options, futures, swaps, pricing, and managing financial derivatives.
Quantitative Risk Management
Year 2Semester 13 creditsCore
Examines quantitative methods, risk models, VaR, stress testing, and managing quantitative risk.
Dissertation Research Project
Year 2Semester 29 creditsCore
Supervised dissertation on a mathematical finance and risk analysis topic, demonstrating mastery of quantitative methods and finance knowledge, assessed through written submission and oral defence.

Specialisations

Quantitative Finance
Focuses on quantitative finance, covering modelling, pricing, derivatives, analytics, and managing quantitative finance.
Risk Analytics
Examines risk analytics, covering assessment, modelling, management, compliance, and managing risk analytics.
Computational Finance
Covers computational finance, covering methods, programming, modelling, simulation, and managing computational finance.
Asset Pricing
Focuses on asset pricing, covering models, valuation, markets, portfolios, and managing asset pricing.
Machine Learning in Finance
Examines machine learning in finance, covering algorithms, models, applications, analytics, and managing ML in finance.
Investment Banking Analytics
Covers investment banking analytics, covering analysis, modelling, valuation, risk, and managing investment analytics.

A day as a student

A typical day during the MSc in Mathematical Finance and Risk Analysis programme combines lectures, computational labs, project work, seminars, and independent study. Sessions cover financial markets, stochastic calculus, asset pricing, computational methods, and machine learning. Financial markets sessions examine instruments, markets, trading, valuation, and understanding financial markets. Discrete time finance sessions cover models, pricing, derivatives, arbitrage, and managing discrete time finance. Stochastic calculus sessions cover calculus, processes, models, derivatives, and managing continuous time finance. Asset pricing sessions cover models, valuation, portfolios, optimisation, and managing asset pricing. Statistical models sessions cover statistics, models, markets, analysis, and managing statistical models. Computational methods sessions cover programming, modelling, simulation, algorithms, and managing computational finance. Machine learning sessions cover algorithms, models, applications, analytics, and managing ML in finance. Risk management sessions cover assessment, modelling, management, compliance, and managing risk. Seminar series provide opportunities for engaging with industry experts and debating current issues in finance. Computational labs provide hands-on experience with MATLAB, Python, R, and C++ for financial modelling. Project work provides hands-on experience with quantitative finance, risk analytics, and computational modelling. Guest lectures from experienced quantitative analysts, risk managers, and investment bankers provide practical insights. The programme culminates in a supervised dissertation on a mathematical finance and risk analysis topic.

The trade offs

In its favour

Unique programme combining mathematics, finance, and computing, filling a niche in Kenya's financial sector.
Programme uses industry-standard tools: MATLAB, Python, R, and C++.
Graduates are eligible for GARP FRM certification and CFA charter.
High demand for quantitative finance professionals in Kenya's growing financial sector.

Against it

Strathmore fees are high at approximately KES 417,300/year.
Only one university (Strathmore, private) confirmed offering this specific programme.
No public university confirmed offering this specific programme.
Programme requires strong mathematics background, limiting access for non-quantitative graduates.

What it costs

Tuition at both ends of the market, and how to pay for it.

What it costs, and where

Against 243 science courses

Public250k to 296k

250k at University of Nairobi296k at Kenyatta University

Private325k to 325k

325k at Strathmore University325k at Strathmore University

Annual tuition in Kenyan shillings, rounded. The upright tick is the median for this field, so a bar sitting entirely to its right is an expensive programme by the standards of its own subject.

The fine print

KU sci MSc ~296K/yr (joweri.com). UoN unverified. Strathmore 325K/yr (sims.strathmore.edu).

HELB postgraduate loans are available for Kenyan students. Strathmore University may offer scholarships for eligible students. GARP may offer bursaries for risk management education. Some financial institutions, banks, and regulatory bodies may sponsor staff for postgraduate study.

Funding options

HELB Postgraduate Loan
Strathmore Scholarship
GARP Bursary

Scholarships

3 recorded

HELB Postgraduate Loan
LoanKsh 200,000Kenyan
Kenyan students pursuing postgraduate studies at recognised universities.
Strathmore Scholarship
ScholarshipKsh 417,300Kenyan
Strathmore University offers scholarships for eligible postgraduate students.
GARP Bursary
ScholarshipKsh 150,000
GARP may offer bursaries for risk management education and professional development.

Getting in

The grades, the alternatives, and who accredits the award.

What you need

KCSE mean grade: N/A (Postgraduate)
Alternative entry: Strathmore University requires a Bachelor's degree with at least Second Class Honours in a relevant quantitative field. An interview may be required. Contact Strathmore for specific admission requirements.

How you are assessed

4 components

Coursework and Continuous Assessment
Coursework30% of the mark
Continuous assessment through coursework assignments, computational projects, seminar presentations, and class participation.
Written Examinations
Examination70% of the mark
Written examinations covering financial markets, stochastic calculus, asset pricing, and computational methods.
Computational Project Assessment
Project40% of the mark
Practical assessment through computational projects, financial modelling, programming, and demonstrating quantitative finance skills.
Dissertation
Research100% of the mark
Supervised dissertation on a mathematical finance and risk analysis topic, demonstrating mastery of quantitative methods and finance knowledge, assessed through written submission and oral defence.

Accreditation

The programme is accredited by the Commission for University Education (CUE). Strathmore University (private) offers MSc in Mathematical Finance and Risk Analytics through the Institute of Mathematical Sciences. The programme meets CUE standards for postgraduate training in mathematical finance and risk analytics. Graduates are eligible for GARP FRM certification and CFA charter.

Accredited by

Commission for University Education (CUE)
Academic accreditationRequired
Programme accredited by CUE. Strathmore University (private) offers MSc in Mathematical Finance and Risk Analytics through the Institute of Mathematical Sciences. The programme meets CUE standards for postgraduate training in mathematical finance and risk analytics. Graduates are eligible for GARP FRM certification and CFA charter.

Where it leads

The roles it opens, and what you leave with.

Where graduates go

6 roles

Quantitative Analyst
High demandKsh 150,000 to Ksh 600,000
Develops quantitative models, overseeing modelling, pricing, analytics, and managing quantitative finance.
Risk Manager
High demandKsh 120,000 to Ksh 500,000
Manages risk operations, overseeing assessment, modelling, management, and managing risk.
Investment Analyst
High demandKsh 100,000 to Ksh 450,000
Conducts investment analysis, overseeing analysis, valuation, modelling, and managing investments.
Financial Modeller
Moderate demandKsh 120,000 to Ksh 500,000
Develops financial models, overseeing modelling, simulation, valuation, and managing financial models.
Data Scientist (Finance)
High demandKsh 150,000 to Ksh 600,000
Applies data science in finance, overseeing analytics, ML, modelling, and managing financial data.
Mathematical Finance Lecturer
Moderate demandKsh 100,000 to Ksh 450,000
Teaches mathematical finance at university or college level, overseeing instruction, research, and academic supervision.

Graduate outcomes

Where these fields lead

8 careers

Tools you will learn

Python
SoftwarePrimary
Python for financial modelling and analytics, covering data, modelling, analysis, and managing financial data.
MATLAB
Software
MATLAB for computational finance, covering modelling, simulation, analysis, and managing computational finance.
R
Software
R for statistical analysis and modelling, covering data, statistics, analysis, and managing financial data.
C++
Software
C++ for high-performance financial computing, covering algorithms, modelling, simulation, and managing computational finance.

Industry links

Common misconceptions

Mathematical finance is just about accounting.
Mathematical finance covers comprehensive quantitative modelling, stochastic calculus, risk analytics, and computational methods beyond just accounting.
Risk analysis is just about insurance.
Risk analysis covers comprehensive assessment, modelling, management, compliance, and analytics beyond just insurance.
This programme is only for mathematicians.
Mathematical finance skills are valuable for economists, statisticians, computer scientists, and finance professionals beyond just mathematicians.
Computational finance is just about spreadsheets.
Computational finance covers comprehensive programming, modelling, simulation, and algorithms in MATLAB, Python, R, and C++ beyond just spreadsheets.
Machine learning in finance is just about chatbots.
Machine learning in finance covers comprehensive algorithms, models, analytics, prediction, and risk management beyond just chatbots.
Quantitative finance careers are limited in Kenya.
Kenya's growing financial sector, fintech ecosystem, and regulatory bodies create high demand for quantitative finance professionals.