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Opportunities in Quantitative Finance in the Department of Mathematics Introduction and Background • In 1973 Black and Scholes developed the option pricing models based on advanced mathematics. • Today the financial practice has become very quantitative. • Sophisticated mathematical models are used to support investment decisions, to develop and price new financial products or to manage risk. What is Quantitative Finance? • Multidisciplinary programme that combines Mathematics, Finance and Computing with a practical orientation that is designed for high-caliber students who wish to become professionals in the finance industry. • Covers the following areas – Mathematical Theory and Tools – Statistical Methods – Computing Theory and Techniques – Financial Theory and Principles – Core Financial Product Knowledge • Plays an increasingly important role in the financial services industry and the economy. Examples Risk Management • Banks in the course of their business take on risk? • How do we measure the risk that the bank is exposed to? • How do we hedge and manage the risk? • Tools – Linear Algebra and Calculus – Advanced probability and statistics – Time Series Analysis – Simulation Methodologies Derivatives Trading • Pricing and Hedging of Complex Derivatives • Tools – Advanced Stochastic Processes – Numerical solutions to partial differential equations Career Opportunities • Potential Employers – Banks – Investment Companies – Securities Firms – Insurance Companies – Multinationals • Increase in demand for graduates with high level of quantitative and analytical skills • Jobs – Financial Product Development and pricing (Structured Deposits, Derivatives etc.) – Risk Management – Investment decision making and fund management – Wealth Management Skills Required of Quantitative Analysts/Risk Managers • Basic Quantitative Skills – Mathematics (Linear Algebra, Calculus) – Probability – Statistics • Computer programming – Excel, VBA, Matlab, SAS • Knowledge of Derivatives and Fixed Income Objective of Programme • To equip graduates for the finance industry with – Technical knowledge and skills in quantitative finance and risk management – Strong quantitative modeling skills – Analytical mind • This programme is uniquely positioned to meet the increasing demand for graduates with quantitative modeling and risk management skills. Key Features • Multi-disciplinary curriculum integrating mathematical methods and statistical tools, computing techniques with applications to finance. • Use of quantitative tools with state-of-the-art financial systems in the computing laboratory. • Projects with financial engineering applications. • Honours track programme with option to exit earlier and graduate with B.Sc. • Typically, it takes 3 and 4 years to complete the requirements for B.Sc. and B.Sc.(Hons), respectively. A shorter timeframe is possible for some. Curriculum Structure • Satisfy University requirements for B.Sc./B.Sc.(Hons) • Satisfy Faculty requirements for B.Sc./B.Sc.(Hons) • Pass at least 70 MCs/102 MCs to satisfy the major requirements for B.Sc./B.Sc.(Hons) • Obtain at least 120 MCs/160 MCs to graduate with B.Sc./B.Sc.(Hons) in Quantitative Finance • Maximum candidature for students reading B.Sc.(Hons) is 4 years Curriculum Structure • Core modules cover topics in – Calculus – Data structures and algorithms – Finance – Financial accounting – Financial time series – Financial trading and modeling – Financial mathematics – Investment instruments – Linear algebra – Linear programming – Mathematical statistics – Numerical analysis – Probability – Programming methodology Curriculum Structure • Elective modules cover topics in – Basic derivatives and bonds – Computer intensive statistical methods – Corporate finance – Design & analysis of algorithm – Discrete time finance – Equity products and exotics – Financial markets – Financial risk management – Game theory – Linear models – Mathematical programming – Nonlinear programming – Numerical partial differential equations – Ordinary different equations – Regression analysis – Stochastic analysis Admission Requirements • Enrolled in Faculty of Science • Studied for two semesters in NUS • Obtained an overall CAP of 3.50 or higher at the end of the two semesters • Passed the following four qualifying modules in the two semesters – CS1010/CS1010E (Programming Methodology) – MA1102R (Calculus) – MA1101R (Linear Algebra) – ST2131/MA2216 (Probability) • The group average point (GAP) for the qualifying modules must be at least 3.50 Application • Application deadline and form will be posted on the department’s web in due course. • Submit a hard copy of the application form with a copy of the NUS academic results to the general office by the application deadline. • For more information, visit http://www.math.nus.edu.sg