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Goal As Modern Financial Institutions Face Various Risks from a Wide Range Goal As modern financial institutions face various risks from a wide range of financial and non-financial Classification Abbreviation : MR-Major Requisite, ME-Major Elective sources, measuring and managing these risks has become a vital part of their daily and strategic LEC decision-making process. Due to the interconnectedness of the international financial system, we now YR CLS COURSE TITLE CR (LAB) witness that the consequences of financial risks can affect not just individual institutions, but all of MR INTRODUCTION TO QUANTITATIVE RISK MANAGEMENT 3 3 society. Quantitative Risk Management (QRM) is a multidisciplinary program designed to give 1 students opportunities to study advanced quantitative methods and models used in the modern MR INTRODUCTION TO STATISTICS 3 3(1) financial world. After completion of the program, successful students will be able to start careers in MR FUNDAMENTALS OF ECONOMIC ANALYSIS 3 3 various positions in financial risk management. QRM has a vision to nurture interdisciplinary global ME STATISTICAL METHODS 3 3 talents for financial risk management by creating synergistic effects which transcend traditional MR CALCULUS 3 3 academic disciplines such as economics, statistics, actuarial science, and other relevant fields. 2 ME LINEAR ALGEBRA 3 3 ME COMPUTER DATA ANALYSIS 3 3 Curri culum Bei ng an interdisci plinary program, QRM is based on a wide range of academic disciplines, such as ME PRINCIPLES OF ECONOMICS 3 3 economics, applied statistics, mathematical finance, and actuarial science. It offers a rich, yet ME QUANTITATIVE METHODS OF FINANCIAL ENGINEERING 3 3 mathematically rigorous, curriculum that enables students to understand, measure, and manage the MR PRINCIPLES OF FINANCIAL ENGINEERING 3 3 risks underlying diverse financial models and the economy. In particular, students will learn the ME PRINCIPLES OF MICROECONOMICS 3 3 system of the financial market, the risks underpinning the market, and how to measure, monitor, ME PRINCIPLES OF MACROECONOMICS 3 3 and manage those risks. MR MATHEMATICAL STATISTICS 1 3 3 Subjects taught include: macro and micro economics, statistical models for financial markets and ME MATHEMATICAL STATISTICS 2 3 3 products, fixed income securities and related risks, equity models, financial derivatives and structured 3 products, credit and operational risks, financial engineering, life and non-life insurance loss models, ME FINANCIAL ECONOMICS 3 3 asset-liability management, regulation, and other risk analytics. ME REGRESSION ANALYSIS 3 3 ME MONEY AND BANKING 3 3 Career ME ECONOMETRICS 3 3 Our program provides students with a strong foundation in quantitative risk management. After ME LAW AND ECONOMICS 3 3 completing the program successfully, QRM graduates will be well prepared for careers as qualified ME STATISTICAL MODELS FOR GENERAL INSURANCE 3 3 professionals within financial institutions such as banks, securities firms, insurance companies, asset management firms, ratings agencies, and consulting firms, as well as other private organization that ME STATISTICAL RISK MANAGEMENT 3 3 require advanced skills in risk management. Public sector jobs, such as those in regulatory ME FINANCIAL RISK ANALYSIS 3 3 authorities, are an alternative career choice. QRM graduates can also pursue higher education, or ME DATA MINING 3 3 4 work for government and private research institutes and universities. ME INTERNATIONAL FINANCE 3 3 ME STOCHASTIC PROCESS 3 3 Faculty ME ACTURIAL MATHEMATICS ) 3 3 Qualified faculty members of Yonsei University from diverse disciplines will teach the courses ME MAJOR QUALIFYING PROJECT (MQP) 6 offered at QRM. The faculty members have expertise in multitude fields such as economics, statistics, mathematics, and quantitative analysis for financial risk management. All faculty members have years of proven records in teaching and research in the field of QRM, and some of them are nationally acclaimed academics in their fields. • Major: 42 credit-hours required from the course list of QRM major. The following seven courses (21 credits) are required: 1) Introduction to Quantitative Risk Management 2) Introduction to Statistics - Students may take "Social Science Research Methods" instead of Introduction to Statistics. Various theories of financial engineering will be introduced as they relate to futures, options, 3) Fundamentals of Economic Analysis swaps, and other derivatives. Numerical techniques will be introduced in the pricing of 4) Social Justice: Theory, Policy, and Law derivatives. Computer programming will be used in determining the price of derivatives in order 5) Calculus to enhance understanding of the topic. 6) Mathematical Statistics 1 STATISTICAL MODELS FOR GENERAL INSURANCE Topics include models for loss severity such as parametric models, effects of policy 7) Principles of Financial Engineering modifications, and tail behaviour. Further topics such as models for loss frequency: (a, b, 0), (a, b, 1); mixed Poisson models; compound Poisson models; aggregate claims models: moments and • Double Major: 36 credit-hours required. Double majors must also take the seven courses required moment generating function will be introduced. Classical ruin theory will also be discussed if for QRM major. time permits. CALCULUS • Minor: 18 credit-hours required. Introduction to Quantitative Risk Management, Calculus, Calculus is a branch of mathematics of which primary purpose is the study of Introduction to Statistics, Fundamentals of Economic Analysis, Mathematical Statistics 1, Principles motion and change. It is an indispensable tool of thought in many disciplines including science, of Financial Engineering. finance, and engineering, as well as other mathematical applications. In this course, the concept of differentiation and integration are introduced in the univariate and multivariate (vector) •QRM majors can take a course taught in Korean and up to4courses(12credits)canbe settings. counted toward fulfilling the credit requirement for the major. LINEAR ALGEBRA Linear algebra forms the basis for much of modern mathematics-theoretical, applied, and computational. The purpose of this course is to provide a broad and solid foundation for the study of advanced mathematics. A secondary aim is to introduce the student to many of the INTRODUCTION TO QUANTITATIVE RISK MANAGEMENT interesting applications of linear algebra. Various applications of linear algebra show how linear An introduction to financial risk and management using statistical and mathematical models will algebra is essential in solving problems involving differential equations, optimization, be discussed. Brief quantitative methods for measuring and modeling financial risks and losses in approximation, and combinatorics. real-world events will also be introduced. Quantitative methods covered in the course will COMPUTER DATA ANALYSIS include theories from statistics, economics, and mathematics. Based on various kinds of quantitative data, useful computer programs will be taught for INTRODUCTION TO STATISTICS efficient data processing and its analysis. Statistical analysis and numerical analysis, and This course is an introduction to the use and limitations of mathematical and statistical optimization will be practiced using VBA, Matlab, R, or other suitable softwares. techniques in risk management. Several statistical techniques are covered and examined for MATHEMATICAL STATISTICS 1 application in quantitative decision making. The main purpose of the course is to provide useful The goal of this course is to provideacomprehensiveintroduction to the mathematical study of information and insights to support the uses of statistics in risk management. There are two statistics. Topics include probability, univariate distributions, multivariate distributions, functions of aspects to this course. The first aspect of this course is the teaching of statistical concepts by random variables, and limiting distributions. Emphasis will be on the theoretical development of introducing statistical techniques. Another aspect is to show how statistical techniques are each topic, including definitions, theorems, and proofs. actually used in practice. There are many examples of the practical use of statistical techniques. MATHEMATICAL STATISTICS 2 Relevant case studies will be presented as the course covers new topics. This course is designed for students who have a solid statistical background. Th e topics include FUNDAMENTALS OF ECONOMIC ANALYSIS various statistical estimations and tests based on various principles. Other topics covered are data This course seeks to address the following sets of related questions at an introductory level. reductions and some asymptotic theories. How are prices determined? When can we rely on market forces to work and when do they not REGRESSION ANALYSIS work? What happens when a market is not competitive? What does national income measure, Regression model is one of the most widely-used statistical tools in our real world. In and how can we improve it? What causes unemployment and price inflation? You should be in particular, linear regression model is important not only in the field of statistics but also in the a position to answer these important questions yourselves at the end of the course. all of data handling analyses. In this class we will explore basic theories - such as simple STATISTICAL METHODS regression models, multiple regression models, model diagnostics and variable selections. If time This course will introduce several statistical techniques useful for data
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