Science

Master of Science in Mathematical Finance

The Master of Science in Mathematical Finance is a postgraduate programme that trains graduates in financial mathematics, quantitative finance, risk management, and financial modelling. The programme prepares graduates for advanced careers in quantitative finance, risk analysis, financial engineering, and investment management.

Core areas include financial mathematics, stochastic calculus, derivative pricing, risk management, portfolio optimisation, financial modelling, quantitative analysis, computational finance, econometrics, and research methods. Students engage with theoretical foundations and practical quantitative finance applications.

The programme is offered by Moi University, Chuka University, and Jaramogi Oginga Odinga University of Science and Technology, with Strathmore University as a college. Strathmore offers MSc in Mathematical Finance through its Institute of Mathematical Sciences (SIMS). JOOUST has a Department of Applied Statistics, Financial Mathematics and Actuarial Science. Moi University offers related Master in Banking and Finance.

Students develop competencies in financial mathematics, derivative pricing, risk modelling, portfolio management, computational finance, and research. The programme includes coursework, computational projects, examinations, supervised research, and thesis.

The programme is delivered over two years with full-time and part-time study modes. Chuka University science-based postgraduate fees are KES 75,000 per semester. Strathmore University (private) postgraduate fees range from KES 100,000 to KES 190,000 per semester. Entry requires Bachelor's degree in mathematics, statistics, finance, or related fields with Upper Second or Lower with experience.

Graduates pursue careers as quantitative analysts, risk managers, financial engineers, investment analysts, and lecturers in banks, insurance companies, investment firms, financial regulators, and universities.

Skills Required

Financial Mathematics and Stochastic Calculus
Derivative Pricing and Financial Engineering
Risk Management and Quantitative Risk Analysis
Portfolio Optimisation and Asset Allocation
Financial Modelling and Computational Finance
Quantitative Analysis and Statistical Methods
Econometrics and Time Series Analysis
Monte Carlo Simulation and Numerical Methods
Financial Markets and Instruments
Mathematical Finance Research Methods

Key Subjects

Financial Mathematics
Stochastic Calculus
Derivative Pricing
Risk Management
Portfolio Optimisation
Financial Modelling
Quantitative Analysis
Computational Finance
Econometrics
Mathematical Finance Research Methods

Certifications

CFA Charter
FRM Certification

Specializations

Financial Mathematics

Focuses on financial mathematics, stochastic calculus, differential equations, martingale theory, Black-Scholes model, and understanding and applying mathematical finance theory.

Derivative Pricing

Examines derivative pricing, options, futures, swaps, exotic derivatives, pricing models, numerical pricing, and understanding and applying derivative pricing methods.

Risk Management

Covers risk management, market risk, credit risk, operational risk, Value at Risk, stress testing, and measuring, managing, and mitigating financial risk.

Portfolio Management

Focuses on portfolio theory, portfolio optimisation, asset allocation, Markowitz model, CAPM, factor models, and designing and managing investment portfolios.

Computational Finance

Examines computational finance, Monte Carlo simulation, finite difference methods, numerical methods, programming for finance, and applying computational methods in finance.

Quantitative Analysis

Covers quantitative analysis, statistical methods, econometrics, time series analysis, regression, forecasting, and applying quantitative methods in financial analysis.

Duration: 2 years
Public, up to: Ksh 187,200
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: 20 students
Award: Masters

What you study

10 subjects

Financial Mathematics
Stochastic Calculus
Derivative Pricing
Risk Management
Portfolio Optimisation
Financial Modelling
Quantitative Analysis
Computational Finance
Econometrics
Mathematical Finance Research Methods

Modules

12 in the programme

Financial Mathematics and Stochastic Calculus
Year 1Semester 13 creditsCore
Examines stochastic calculus, Brownian motion, Ito's lemma, stochastic differential equations, martingale theory, Girsanov theorem, and understanding and applying mathematical finance theory.
Derivative Pricing and Financial Engineering
Year 1Semester 13 creditsCore
Covers options, futures, forwards, swaps, Black-Scholes model, binomial models, exotic options, interest rate derivatives, and understanding and applying derivative pricing methods.
Risk Management and Quantitative Risk Analysis
Year 1Semester 13 creditsCore
Examines market risk, credit risk, operational risk, Value at Risk, expected shortfall, stress testing, Basel frameworks, and measuring, managing, and mitigating financial risk.
Portfolio Theory and Asset Allocation
Year 1Semester 23 creditsCore
Covers portfolio theory, Markowitz model, CAPM, APT, factor models, asset allocation, portfolio rebalancing, and designing and managing investment portfolios.
Computational Finance and Numerical Methods
Year 1Semester 23 creditsCore
Examines Monte Carlo simulation, finite difference methods, numerical methods, lattice methods, Python for finance, R for finance, and applying computational methods in finance.
Econometrics and Time Series Analysis
Year 1Semester 23 creditsCore
Covers time series analysis, ARIMA models, GARCH models, volatility modelling, regression, cointegration, forecasting, and applying econometric methods in finance.
Financial Markets and Instruments
Year 2Semester 13 creditsCore
Examines equity markets, bond markets, derivative markets, FX markets, money markets, OTC markets, market microstructure, and understanding financial markets and instruments.
Interest Rate Models and Fixed Income
Year 2Semester 13 creditsCore
Covers interest rate models, term structure, Vasicek model, Cox-Ingersoll-Ross model, Heath-Jarrow-Morton, LIBOR market model, and pricing fixed income derivatives.
Machine Learning for Finance
Year 2Semester 13 creditsCore
Examines machine learning for finance, supervised learning, unsupervised learning, neural networks, deep learning, NLP for finance, and applying machine learning in financial analysis.
Mathematical Finance Research Methods
Year 2Semester 13 creditsCore
Covers research methods for mathematical finance, numerical methods, empirical methods, data analysis, financial data, and conducting mathematical finance research, preparing students for their thesis.
Behavioural Finance and Market Microstructure
Year 2Semester 23 creditsCore
Examines behavioural finance, investor psychology, market efficiency, anomalies, market microstructure, trading mechanisms, and understanding behavioural aspects of financial markets.
Research Thesis
Year 2Semester 26 creditsCore
Original research thesis on a mathematical finance topic, demonstrating mastery of research methods and mathematical finance knowledge, assessed through written submission and oral defence.

Specialisations

Financial Mathematics
Focuses on financial mathematics, stochastic calculus, differential equations, martingale theory, Black-Scholes model, and understanding and applying mathematical finance theory.
Derivative Pricing
Examines derivative pricing, options, futures, swaps, exotic derivatives, pricing models, numerical pricing, and understanding and applying derivative pricing methods.
Risk Management
Covers risk management, market risk, credit risk, operational risk, Value at Risk, stress testing, and measuring, managing, and mitigating financial risk.
Portfolio Management
Focuses on portfolio theory, portfolio optimisation, asset allocation, Markowitz model, CAPM, factor models, and designing and managing investment portfolios.
Computational Finance
Examines computational finance, Monte Carlo simulation, finite difference methods, numerical methods, programming for finance, and applying computational methods in finance.
Quantitative Analysis
Covers quantitative analysis, statistical methods, econometrics, time series analysis, regression, forecasting, and applying quantitative methods in financial analysis.

A day as a student

A typical day during the MSc Mathematical Finance programme begins with morning lectures on financial mathematics, stochastic calculus, or risk management. Students engage in theoretical discussions on financial models, pricing theory, and quantitative methods. Financial mathematics sessions cover stochastic calculus, Brownian motion, Ito's lemma, stochastic differential equations, martingale theory, and understanding and applying mathematical finance theory. Derivative pricing sessions examine options, futures, forwards, swaps, Black-Scholes model, binomial models, exotic options, and understanding and applying derivative pricing methods. Risk management sessions cover market risk, credit risk, operational risk, Value at Risk, expected shortfall, stress testing, Basel frameworks, and measuring and managing financial risk. Portfolio management sessions examine portfolio theory, Markowitz model, CAPM, APT, factor models, asset allocation, and designing and managing investment portfolios. Computational finance sessions cover Monte Carlo simulation, finite difference methods, numerical methods, Python for finance, R for finance, and applying computational methods in finance. Econometrics sessions examine time series analysis, ARIMA models, GARCH models, volatility modelling, regression, cointegration, and applying econometric methods in finance. Quantitative analysis sessions cover statistical methods, hypothesis testing, estimation, Bayesian methods, machine learning for finance, and applying quantitative methods in financial analysis. Financial markets sessions examine equity markets, bond markets, derivative markets, FX markets, money markets, and understanding financial markets and instruments. Computational projects provide hands-on experience with derivative pricing, risk modelling, portfolio optimisation, and financial simulation. Programming sessions provide hands-on experience with Python, R, MATLAB, and financial computing. Research methodology sessions prepare students for their thesis, covering mathematical finance research methods, numerical methods, and data analysis. Guest lectures from CMA officials, CBK economists, ASK actuaries, investment bankers, and quantitative finance practitioners provide real-world insights. The two-year programme culminates in a research thesis.

The trade offs

In its favour

Kenya's growing financial sector, capital markets development, insurance industry, fintech growth, and regulatory needs create high demand for qualified quantitative finance professionals.
Strathmore offers MSc Mathematical Finance through its Institute of Mathematical Sciences (SIMS), providing specialised mathematical finance training.
Programme combines advanced mathematics with finance, providing highly specialised and marketable quantitative skills.
Career opportunities with banks, insurance companies, investment firms, CMA, CBK, IRA, fintech companies, and international financial institutions.

Against it

Programme requires strong mathematics background, which may exclude graduates without quantitative undergraduate training.
Programme involves rigorous mathematical content including stochastic calculus, differential equations, and numerical methods, which may be challenging for some students.
Strathmore fees at KES 150,000 per semester (~KES 300,000/year) are relatively expensive compared to public universities.
Specific fee structures for this exact programme could not be independently verified from all official websites.

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

Public150k to 187k

150k at Jaramogi Oginga Odinga University of Science and Technology187k at Moi 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

JOOUST 150K/yr (eafinder.com). Moi ~187K/yr. Strathmore 325K/yr (sims.strathmore.edu).

HELB postgraduate loans are available for Kenyan students. AIMS supports mathematical sciences education in Africa. Strathmore offers financial aid for eligible students. CFA Institute offers scholarships for CFA programme. GARP offers scholarships for FRM certification. The programme's mathematical finance focus attracts professional body and industry funding.

Funding options

HELB Postgraduate Loan
AIMS Scholarship
Strathmore Financial Aid

Scholarships

3 recorded

HELB Postgraduate Loan
LoanKsh 200,000Kenyan
Kenyan students pursuing postgraduate mathematical finance studies at recognised universities.
AIMS Scholarship
ScholarshipKsh 500,000
AIMS supports mathematical sciences education in Africa, providing scholarships for postgraduate study in mathematical sciences.
Strathmore Financial Aid
GrantKsh 300,000Kenyan
Strathmore University offers financial aid for eligible students demonstrating academic merit and financial need.

Getting in

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

What you need

KCSE mean grade: N/A (Postgraduate)
Alternative entry: The programme accepts graduates from mathematics, statistics, finance, economics, actuarial science, physics, engineering, and related quantitative fields. Strong mathematical background required. Two-year programme with full-time and part-time modes. Chuka requires Upper Second or Lower with 2 years experience. Chuka science-based fees KES 75,000/semester. Strathmore fees estimated at KES 150,000/semester.

How you are assessed

4 components

Coursework and Assignments
Coursework30% of the mark
Continuous assessment through coursework assignments, problem sets, mathematical proofs, computational exercises, and class participation.
Written Examinations
Examination40% of the mark
Written examinations covering financial mathematics, derivative pricing, risk management, and econometrics, conducted at end of each semester.
Computational Projects
Practical30% of the mark
Assessment of computational projects, derivative pricing implementations, risk models, portfolio optimisation, and programming assignments.
Research Thesis
Research100% of the mark
Original research thesis on a mathematical finance topic, demonstrating mastery of research methods and mathematical finance knowledge, assessed through written submission and oral defence.

Accreditation

The programme is accredited by the Commission for University Education (CUE). Strathmore University offers MSc in Mathematical Finance through its Institute of Mathematical Sciences (SIMS). JOOUST has a Department of Applied Statistics, Financial Mathematics and Actuarial Science. Moi University offers related Master in Banking and Finance. The programme meets CUE standards for postgraduate mathematical finance training. CMA regulates capital markets and CBK regulates banking in Kenya.

Accredited by

Commission for University Education (CUE)
Academic accreditationRequired
Programme accredited by CUE. Strathmore University offers MSc in Mathematical Finance through its Institute of Mathematical Sciences (SIMS). JOOUST has a Department of Applied Statistics, Financial Mathematics and Actuarial Science. The programme meets CUE standards for postgraduate mathematical finance training.
Capital Markets Authority (CMA)
Professional accreditation
CMA regulates capital markets in Kenya. Graduates pursuing careers in capital markets may benefit from CMA licensing and professional certification.

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 for financial institutions, overseeing derivative pricing, risk modelling, algorithmic trading, and supporting quantitative finance.
Risk Manager
High demandKsh 130,000 to Ksh 550,000
Manages financial risk, overseeing risk measurement, VaR, stress testing, Basel compliance, and ensuring effective risk management.
Financial Engineer
Moderate demandKsh 140,000 to Ksh 580,000
Designs financial products and models, overseeing derivative structuring, pricing models, hedging strategies, and supporting financial engineering.
Investment Analyst
High demandKsh 120,000 to Ksh 500,000
Analyses investments, overseeing portfolio analysis, asset valuation, performance attribution, and supporting investment decision-making.
Actuarial Analyst
High demandKsh 130,000 to Ksh 550,000
Applies mathematical finance in insurance, overseeing actuarial modelling, risk pricing, reserving, and supporting actuarial and insurance operations.
University Lecturer
High demandKsh 130,000 to Ksh 500,000
Teaches mathematical finance in universities, conducting research and training future quantitative finance professionals.

Graduate outcomes

Graduates pursue careers as quantitative analysts, risk managers, and financial engineers in banks, insurance companies, and investment firms.

Where these fields lead

8 careers

Tools you will learn

Python
SoftwarePrimary
Programming language for financial computing, derivative pricing, risk modelling, Monte Carlo simulation, and quantitative finance analysis with libraries like NumPy, SciPy, pandas.
R
SoftwarePrimary
Statistical computing software for econometric analysis, time series modelling, financial data analysis, and statistical modelling in mathematical finance.
MATLAB
Software
Numerical computing software for financial modelling, derivative pricing, numerical methods, and computational finance applications.
Excel VBA
Software
Spreadsheet and programming tool for financial modelling, pricing spreadsheets, risk dashboards, and financial analysis in banking and finance.

Industry links

Common misconceptions

Mathematical finance is just about accounting.
The programme involves stochastic calculus, derivative pricing, risk modelling, computational finance, econometrics, and research, covering advanced quantitative finance.
This programme is only for mathematics graduates.
The programme accepts graduates from mathematics, statistics, finance, economics, actuarial science, physics, engineering, and related quantitative fields.
There is limited demand for mathematical finance professionals in Kenya.
Kenya's growing financial sector, capital markets development, insurance industry, fintech growth, and regulatory needs create high demand for qualified quantitative finance professionals.
Mathematical finance is only relevant for investment banks.
Mathematical finance skills are relevant for banks, insurance companies, pension funds, asset managers, regulators, fintech companies, and consulting firms, not just investment banks.
A master's in mathematical finance is redundant after a bachelor's in mathematics.
The master's provides specialised financial mathematics skills, financial industry knowledge, and career progression to senior quantitative finance positions.
Mathematical finance is too theoretical with no practical application.
The programme combines theoretical foundations with computational projects, financial modelling, and practical applications in derivative pricing, risk management, and portfolio optimisation.