Computational Finance is a field of applied computer science, which tackles issues concerning practical interest as far as finance is concerned. It is also the study of algorithms and data that is used in finance as well as computer programs’ mathematics that result into financial systems and models. Master in Computational Finance is a degree program that exposes students to programming, mathematical and statistical tools that are applied in the contemporary world for analyzing and financial data modeling. The skills learned enable expert application of the above tools in measuring risks, structuring of optimal portfolios and modeling asset returns using various programming languages as well as Microsoft Excel.
The many probability representations of asset returns in application of statistical procedures in evaluation are applicable where the returns distributions are normal. The Masters degree exposes students to quality ways of coming up with effective portfolios and optimized methods. The syllabus entails various topics. Among them include computing assets returns, understanding bi-variate distributions, risk budgeting, portfolio theories and the single index model among other relevant topics.
The learned skills in the Master in Computational Finance are applicable in quant trading, algorithmic trading, high performance trading as well as high frequency trading. The required basis is the basic calculus and relevant programming knowledge. The course is marketable worldwide for all students.
The MS (AS & FC) degree program is conformed upon those candidates who have demonstrated high academic performance at BS level programs in the fields of Actuarial Science, Economics, Mathematics, Statistics, Computer Science, and Physics and interested to explore actuarial science, risk management, financial mathematics and computing sciences in insurance and finance. The field of computational finance along with actuarial science is/will be in demand nationally and internationally in banks, financial institutions, insurance companies. [+]