Bachelor of Science (Financial Mathematics) with honours

Financial Mathematics

BSc. (Hons)


This program is developed with aim to provide knowledge on the application of mathematical methods such as probability theory, statistics, optimization, stochastic analysis and economic theory in financial problems which encompass investment, insurance, Islamic finance, risk analysis and so on. The curriculum of this program has been fully integrated to meet the eleven domains of learning outcomes of a program recommended by the Ministry of Higher Education (MOHE). In addition, to adapt with the development of the Industrial Revolution 4.0, several core courses of the program have been implemented with SAS modules that provide SAS certification to the graduates at the end of the program. This certification is an added value to graduates as it is recognized worldwide and has wide industry demand.


To ensure that students get real work experience, a 24-week Industrial Training course will be taken in the last semester in finance or other related industries. The knowledge that has been learned while on campus can be applied during this training, in addition to gaining new knowledge in the relevant sector.

Study resources
You have access to a range of professional mathematical and statistical software such as:

  • SAS
  • Maple
  • Mathematica
  • Minitab
  • R

Our experts use these packages in their teaching and research. 

Entry requirements

Home Student

STPM Graduates

General Entry Requirements:

    • Obtain Sijil Pelajaran Malaysia (SPM) with credits in Bahasa Malaysia / Malay language and pass the History subjects beginning in 2013. Credit in Bahasa Malaysia / Malay language paper in July can also be accounted;
    • Obtain at least CGPA 2.00 with grade C in three (3) subjects including General Studies; and
    • Obtain at least level 1 (Band 1) in Malaysia University English Test (MUET) according to the validity period on the date of application.

Specific Requirements:

    • Obtain at least grade C (CGPA 2.00) at STPM level in the following subjects:
      • Mathematics (M) / Mathematics (T).
    • Obtain at least level 2 (Band 2) in the Malaysian University English Test (MUET).

Matriculation / Foundation Programme Graduates

General Entry Requirements:

    • Obtain Sijil Pelajaran Malaysia (SPM) with credits in Bahasa Malaysia / Malay language and pass the History subjects beginning in 2013. Credit in Bahasa Malaysia / Malay language paper in July can also be accounted;
    • Pass Matriculation-KPM / Foundation Science in UM / Foundation in UiTM and obtain at least CGPA 2.00; and
    • Obtain at least level 1 (Band 1) in Malaysia University English Test (MUET) according to the validity period on the date of application.

Specific Requirements

    • Obtain at least grade C (2.00) at Matriculation/ Foundation level in following subject:
      • Mathematics
    • Obtain at least level 2 (Band 2) in the Malaysian University English Test (MUET).

Diploma Graduates

General Entry Requirements

    • Obtain Sijil Pelajaran Malaysia (SPM) with credits in Bahasa Malaysia / Malay language and pass the History subjects beginning in 2013. Credit in Bahasa Malaysia / Malay language paper in July can also be accounted;
    • Obtain a Diploma or other qualification recognize as equivalent by the Government of Malaysia and approved by the Public University Senate;


    • Pass Sijil Tinggi Persekolahan Malaysia (STPM) in 2018 or earlier and obtain at least grade C (NGMP 2.00) on three (3) subject included General Studies;


    • Pass the Matriculation / Foundation exam in 2018 or earlier and obtain at least CGPA 2.00;


    • Pass Sijil Tinggi Agama Malaysia (STAM) in 2017 or earlier and obtain at least Jayyid Stage;


    • Obtain at least level 1 (Band 1) in Malaysia University English Test (MUET) according to the validity period on the date of application.

Specific Requirements

    • For STPM/ Matriculation/ Foundation graduates in 2018 or earlier, obtain at least grade C (2.00) in any one (1) of the following subjects:
      • Mathematics/ Mathematics (T)/ Mathematics (M)/ Advanced Mathematics/ Engineering Mathematics.
    • Obtain at least level 2 (Band 2) in the Malaysian University English Test (MUET).

International Students

General Entry Requirements

  • Senior High School / Senior Secondary School / Other Certificates from the government schools (with the period of at least 11 to 12 years of study from primary to higher secondary); or
  • GCE ‘A’ Level examination obtained at one sitting; or
  • Any other certificate that is recognized by the Senate of the University as equivalent to the above; and 

English Language Requirements

  • Pass the Test of English Language as a Foreign Language (TOEFL) at least 550; or
  • Pass the International English Language Testing System (IELTS) at least 5.5; or
  • Pass the Malaysian University English Test (MUET) at least Band 3.

Our International Centre office will be happy to advise prospective students on entry requirements. See our International Centre website for further information for international students.

Course structure

Duration: 3.5 years full-time
Total Credit: 120 credits

University Core modules include 

BBB3013   Academic Writing Skills (3 credits)
BBB3102   English for Occupational Purposes (3 credits)
MPU3132  Appreciation of Ethic and Civilizations (2 credits)
MPU3142  Philosophy and Current Issues (2 credits)
MPU3223  Basic Entrepreneurship (3 credits)
MPU3312  Appreciation of Nature and Ocean Heritage (2 credits)
NCC3053   Malaysian Nationality (3 credits)
                    Co-Curriculum (2 credits)

Program Core modules include

This course discusses the topics of limit and continuity, multivariable functions, partial derivatives, total derivative and multiple integration. In addition, this course also discusses the cylinder coordinate, spherical coordinate and the change of variables in multiple integration.

This course is an introduction to techniques of solutions for differentiation equations that require a basis in calculus as well as algebra. Discussions on applications in real problems are also implemented. This course is necessary as the basis for the relevant advanced courses namely Applied Mathematical Methods and Partial Differential Equations.

The course discusses the concepts of vector space including row space and column space, linear transformation including covering matrix representation and similarity matrices, orthogonality up to the Gram-Schmidt orthogonalization process, eigenvalues, eigenvectors, eigenspace and numerical linear algebra.

This course discusses basic concepts for statistics including probability, random variables, probability distributions of random variables, sampling distribution theory, estimation and hypothesis test.

This course discusses linear models, nonparametric methods, multivariate distribution and some approaches in applied multivariate.

This course discusses the concepts of real number space, bounded set, similar set, finite set and countable set. Point set topology on real line includes the ideas of openness and closeness, compact set and connected set. This course also discusses the properties of convergence sequences of real numbers including the pointwise convergence and uniform convergence of functions. Discussion on several important properties such as limit function, continuity, continuity on compact and connected sets and uniform continuity end this course.

This course discusses an introduction to good programming style through examples, the modification of existing computer programming such as C++ codes to solve similar problems and the implementation of mathematical algorithms in a well-documented computer programming program. This course supports IR 4.0 by means of systematic thinking.

This course discusses the fundamental concepts of linear programming problems and the methods of solution. Topics also include simplex method, duality and its sensitivity analysis, transportation and network problems. The course also supports the industrial revolution through the application of SAS programming to solve optimisation problems.

This course discusses several mathematical techniques which are used in solving for unconstrained and constrained optimization problems. Unconstrained methods include Fibonacci search, Newton method, Secant method, gradient method and conjugate direction method. Meanwhile constrained methods include Lagrange condition and Karush-Kuhn-Tucker condition. Students also will solve optimization problems using software SAS.

The course introduces probability theory, mainly the one that are used in finance. It elaborates important topics; namely set and function, measure theory, random variables, probability distribution and conditional expectation which underly the area of financial mathematics. This knowledge of relevant probability theory is essential in understanding the development of stochastic calculus used in finance.  

This course provides an introductory analysis of investments from a quantitative viewpoint. It draws together many of the tools and techniques required by investment professionals, focuses mainly to the interest rate theory. Using these techniques, simple analyses of a number of securities including fixed interest bonds, equities, real estates and foreign currency are discussed.

This course discusses the concept of Markov chain in discrete and continuous times. This course begins with basic definitions and properties of the Markov chain including transition probability and continues with limiting distribution as the long-term behavior of Markov chain. The Poisson process is also highlighted. Some examples of real applications will also be discussed in this course.

The course discusses some basic concepts of calculus for the development of stochastic differential equations which is widely used in finance, other than application in engineering, physics and biology. Explanation on Brownian motion , the main continuous process used in stochastic calculus, is done before stochastic integral and related Ito process are described. Next, the application of Ito formula for Brownian motion and Ito process, also several other cases are illustrated. The course ended with the derivation of stochastic differential equation from ordinary differential equation and solution for few types of stochastic differential equations by using Ito formula.

This course discussed on the fundamentals of financial derivatives, covering the basic properties and the pricing fundamentals of futures, options and swaps. It also explores trading and hedging strategies involving financial derivatives. Finally, time permitting special topics such as exotic options are explored. The course provides the foundation of financial derivatives and lays the ground for a rigorous risk management course.

This course explains in depth the concepts of national income accounting, employment, inflation and unemployment; macroeconomic policies and macroeconomic models.

Students who have met the requirements for practical training shall be located at suitable industries for a period of 24 weeks, after 6 semesters of studies. Each student is required to do a comprehensive report equivalent to 12 credits under the supervision of a lecturer decided upon by the coordinator for practical training and the supervisor in charge at the industry concerned.

This course exposes the students with the basics in academic research, especially in writing the proposal of a scientific research project.

This course is a direct continuation of the MTK4998A course which allows students to implement scholarly projects that have been systematically recommended. Among the areas of research thrust are pure mathematics, applied mathematics, statistics, optimization, fuzzy set theory, financial mathematics, computer-assisted graphic design, numerical analysis methods and operational research. An appropriate series of talks will be given to the students and further discussions on the topic of the talk will be conducted with their respective supervisors next. All students are required to write, submit and present the final report of their respective academic projects in chronological order as determined by the Program.

Program Electives modules may include

This course discusses the introductory of forecasting, forecasting using regression analysis, forecasting using exponential smoothing, forecasting using Box-Jenkins method and modelling univariate GARCH.

The course gives the students exposure to various types of life insurance and annuities. By applying knowledge from the interest rate and probability theories, the values for net single premium and net premium for each type of life insurance and annuities are formulated. The formulas are then employed in solving the related practical insurance problems.

This course is a continuation of the optimization course. It discusses and provides a platform for students to apply linear and nonlinear optimization knowledge for solving problems in finance.

This course is designed to foster a basic understanding of risk management through a Value at Risk (VaR) approach. The main focus of this course is on the measurement and application of the VaR method. This understanding is important for students and financial practitioners to understand the latest revolution in financial risk management. Topics covered including financial risk measurement, VaR calculation, risk and correlation forecasting and stress testing. Each student will involve in VaR calculation project using real financial data. Students are assumed familiar with the concepts in probability including probability distributions, expectations and quantiles.

This course discusses several topics in financial econometrics such as the return predictability and the effect markets hypothesis, event study analysis, portfolio choice and testing the capital asset pricing model, multifactor pricing model, volatility and vector autregressive models.

This course emphasizes the need and importance of Islamic economics in the world economic system. The needs and interests are clarified by discussions on the principles, fundamental and methods of Islamic economics. Discussion on mathematical models for Islamic financial instruments ended the course.

This course explains the use of numerical methods in finance through programming aids. The main focus is option pricing through the Monte Carlo method and finite variance. This method is important for solving the problem of calculating the price of an option that has no analytical form. Topics discussed include financial theory, numerical methods and option pricing. Students are assumed to have an understanding of numerical analysis and the basis of option pricing.

This course presents numerical methods for solving mathematical problems. Both theoretical and computer implementation of the methods are discussed in this course. It covers solution of nonlinear equations, interpolation and approximation, numerical integration and differentiation and solution of ordinary differential equations.

This course discusses partial differential equations and its applications in physics. This course introduces partial differential equations of the first and second order and the solutions using the method of characteristics. This course also discusses main three partial differential equations in physics, namely the heat equation, the wave equation and the Laplace equation and their solutions using the method of separation of variables and integral transforms.

Fees and funding


The 2021/22 annual tuition fees for this programme are:

Home                               RM   1880
International full-time    MYR 8080

General additional costs

Find out more about accommodation and living costs, plus general additional costs that you may pay when studying at UMT. 


Government funding

You may be eligible for government finance to help pay for the costs of studying. See the Government’s student finance website.


Scholarships are available for excellence in academic and co-curricular activities, and are awarded on merit. For further information on the range of awards available and to make an application see our scholarships website.

Teaching and assessment

Teaching hour varies according to the number of courses taken by each individual student. On average, teaching amounts to approximately 18 hours of lectures and classes per week. Courses that involve programming or working with computer software packages usually include practical sessions.

The majority of courses are assessed throughout the semester which normally counts 60% for continuous assessment (assignment, test, etc.) and the remaining 40% for final exam.


Through your studies, you acquire many transferable skills including the ability to think critically, communicate effectively, lead and actively work in group in ethical manner, all of which are considered essential by graduate employers.

The main sectors that graduates can venture into are finance, insurance, banking and services. Among the careers that can be pursued are:

  • Strategic Risk Officer
  • Risk Modeller
  • Investment Analyst
  • Actuarial Manager
  • Quantitative Analyst
  • Technical Analyst
  • Data Analyst
  • Mathematics Educator
  • Researcher
  • Science Officer
  • Entrepreneurs

Please consult our career counsellor at the Centre of Entrepreneurship and Career office.

The programme has been
accredited by 


Dr. Ilyani Abdullah
Phone (office): +609-668 3476