The Bachelor of Science (Financial Mathematics) with Honours program is a program developed 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 etc. The curriculum for this program is designed to cover the eleven domains of program learning outcome recommended by the MOHE and to be taken during the study period of 7 semesters or three and a half years. In addition, due to the development of the industrial revolution (IR) 4.0, SAS modules are integrated in several core courses of the program that provide SAS certification to graduates at the end of the program. This certification is an added value to graduates as it is recognized worldwide and has high industry demands. To ensure students acquire real working experience, a 24-week Industrial Training course is carried out on the last semester (semester 7) in finance or other related industries. The knowledge learned while on campus can then be applied during this training, other than gaining new knowledge in the relevant sector.
This programme is offered for students to achieve the following objectives:
This course covers the basic concept of corruption, including the value of integrity, anti-corruption, forms of corruption, abuse of power in daily activities and organizations as well as waysto prevent corruption. Cases related to corruption are discussed. Teaching and learning methods are implemented in the form of ‘experiential learning’ through individual and group activities. At the end of this course, students are able to understand the practice of integrity, the concept of corruption, anti-corruption, abuse of power as well as the prevention of corruption in society and organizations.
This course gives students an exposure to the basic concepts of entrepreneurship. Students will do learning activities that lead to building an entrepreneurial mindset as an initial preparation for a future career. This course provides an exposure to students on knowledge in entrepreneurship. It also gives students the opportunity to apply the knowledge obtained from their respective fields. In addition, the course aims to apply the entrepreneurial mind sets into their life after graduation.
This course covers the basic concept of corruption, including the value of integrity, anti-corruption, forms of corruption, abuse of power in daily activities and organizations as well as waysto prevent corruption. Cases related to corruption are discussed. Teaching and learning methods are implemented in the form of ‘experiential learning’ through individual and group activities. At the end of this course, students are able to understand the practice of integrity, the concept of corruption, anti-corruption, abuse of power as well as the prevention of corruption in society and organizations.
This course gives students an exposure to the basic concepts of entrepreneurship. Students will do learning activities that lead to building an entrepreneurial mindset as an initial preparation for a future career. This course provides an exposure to students on knowledge in entrepreneurship. It also gives students the opportunity to apply the knowledge obtained from their respective fields. In addition, the course aims to apply the entrepreneurial mind sets into their life after graduation.
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.
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 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.
General Entry Requirements:
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Specific Requirements:
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General Entry Requirements.
General Entry Requirements:
AND
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Specific Requirements
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General Entry Requirements
English Language Requirements
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.
Local | International | Additional Costs |
RM 7,210 | USD 7,150 | 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.
