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Opportunities in Quantitative Finance in the Department of Mathematics

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.

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Opportunities in Quantitative Finance in the Department of Mathematics

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  1. Opportunities in QuantitativeFinancein the Department of Mathematics

  2. 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.

  3. 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.

  4. 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

  5. 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

  6. Skills Requiredof 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

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. Thank You

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