RMSC Courses
Undergraduate Course List
Course Categories
- Courses For the Non-Major
Undergraduates who are not majored in statistics but interested in an introduction to the basic principles and techniques of probability and statistics should consider STAT1011 (Introduction to Statistics) and/or STAT1012 (Statistics for Life Sciences). Students who would like to minor in Risk Management Science are required to register RMS2001 (Introduction to Risk Management Science). For details, please refer to [links] for Major/Minor Study Schemes.
- Foundation Courses
The core courses STAT2001 and STAT2006 are calculus-based introductions to probability and statistics, respectively, and are designed for students planning to continue with more advanced theory and methods courses. STAT3008 covers topics of applied regression analysis and serves as an intermediate level of statistics course. In general, 2000- and 3000-level courses are set up mainly for foundation/intermediate level study. They are usually taken by juniors/sophomores.
- Advanced Courses
Several more advanced theory and methods courses take one or more of the foundation courses as prerequisites. Among these are STAT4001 (Data Mining and Statistical Learning), STAT4002 (Multivariate Techniques with Business Applications), STAT4003 (Statistical Inference), STAT4004 (Actuarial Science), STAT4005 (Time Series), STAT4006 (Categorical Data Analysis), STAT4008 (Survival Modelling), STAT4010 (Bayesian Learning) and STAT4012 (Statistical Principles of Deep Learning with Business Applications). For RMSC majors/minors, advanced courses including RMSC4001 (Simulation Methods for Risk Management Science and Finance), RMSC4002 (Financial Data Analytics with Machine Learning), RMSC4003 (Statistical Modelling in Financial Markets), RMSC4004 (Theory of Risk and Insurance, RMSC4005 (Stochastic Calculus for Finance and Risk) and RMSC4007 (Risk Management with Derivative Concepts) are usually offered.
| Course Code | Course Title | Unit |
| RMSC1101 | Elementary Concepts in Risk Management |
1
|
| RMSC2001 | Introduction to Risk Management |
3
|
| RMSC2101 | Introductory Topics in Risk Management |
1
|
| RMSC3001 | Principles of Credit Risk Management |
3
|
| RMSC3101 | Special Topics in Risk Management |
1
|
| RMSC4001 | Simulation Methods for Risk Management Science and Finance |
3
|
| RMSC4002 | Financial Data Analytics with Machine Learning |
3
|
| RMSC4003 | Statistical Modelling in Financial Markets |
3
|
| RMSC4004 | Theory of Risk and Insurance |
3
|
| RMSC4005 | Stochastic Calculus for Finance and Risk |
3
|
| RMSC4006 | Operational Risk Management |
3
|
| RMSC4007 | Risk Management with Derivatives Concepts |
3
|
| RMSC4102 | Research Project |
3
|
| RMSC4112 | Research Project in Risk Analytics |
3
|
| RMSC4202 | Practicum |
3
|
| RMSC4212 | Practicum in Risk Analytics |
3
|
*Note: If any discrepancy arises, the version on CUSIS should be treated as the official version.
RMSC1101 Elementary Concepts in Risk Management
1U This is an elementary course that introduces current issues and special topics in risk management. Students are required to present and discuss books and current articles in the related topics assigned by the instructor. Advisory: For majors only.
RMSC2001 Introduction to Risk Management
This course aims at providing a focused introduction to various concepts of risk and risk measures from a scientific perspective. The course will discuss the various roles that risk plays in insurance and financial applications. Current risk measures such as value at risk and shortfall risk will be introduced. These measures will be calculated for recent financial losses to illustrate their usefulness in risk management.
RMSC2101 Introductory Topics in Risk Management
1 U This is an elementary course aiming at introducing current issues and special topics in risk management. Students are required to read books and articles in the related topics assigned by the instructor. Advisory: For majors only.
RMSC3001 Principles of Credit Risk Management
This course introduces the general methodology for credit risk management – how should we handle the possibility our counterparty may not pay us what they owe? Answering this question depends on who the counterparty is and the nature of our contract with them. As such, in this course we explore credit risk models for retail customers, credit risk measures for portfolios, credit mitigation techniques for markets, credit derivatives used by traders and much else besides, all in the context of the latest Basel regulations and the lessons learned from Credit Crisis of 2007-8.
RMSC3101 Special Topics in Risk Management
1 U This is an intermediate course aiming at introducing current issues and special topics in risk management. Students are required to read books and articles in the related topics assigned by the instructor. Advisory: For majors only.
RMSC4001 Simulation Methods for Risk Management Science and Finance
This course starts with presenting standard topics in simulation including random variable generations, variance reduction methods and statistical analysis of simulation outputs. The course then reviews the applications of these methods to derivative security pricing. Topics addressed include: importance sampling, martingale control variables, stratification and the estimation of derivatives. Additional topics include the use of low discrepancy sequence (quasi-random numbers), pricing American options and scenario simulation for risk management.
RMSC4002 Financial Data Analytics with Machine Learning
This course covers modern data analysis techniques that are commonly used in finance and risk management. Topics include applications of multivariate techniques for data cleansing and modeling such as principal component analysis and canonical correlation analysis to asset management, Extreme Value theory, Value-at-Risks, GARCH modeling in estimating volatility, time series methods in term-structure analysis. Besides, the next few introductory topics in machine learning will also be covered, such as recommender system, logistic regression, k-means clustering, perceptrons, decision trees, artificial neural network, stochastic gradient descent, Naive Bayes Classifiers and Bayesian networks.
RMSC4003 Statistical Modelling in Financial Markets
This course is designed to introduce the current developments in risk management in the financial markets. Risk management ideas associated with three general important areas in finance will be discussed: asset management, derivative pricing and fixed income models. Emphasis will be placed on the statistical modelling aspects on some of the commonly used models in these areas.
RMSC4004 Theory of Risk and Insurance
This course covers the theory of risk and its applications to insurance. Topics include: classical and stochastic risk models, ruin theory, claims modelling and evaluations, risk premium pricing, loss distributions and creditability theory.
RMSC4005 Stochastic Calculus for Finance and Risk
This course starts with the introduction of the concepts of arbitrage and risk-neutral pricing. It then proceeds to discuss the stochastic calculus foundations for continuous-time finance models. Topics include: Brownian motion, stochastic integral, Itô’s formula, Girsanov’s change of measure, and the relationship between stochastic calculus and partial differential equations. Examples will be taken from equity options, including the Black-Scholes formula for foreign exchange and term-structure models.
RMSC4006 Operational Risk Management
This course introduces the general methodology for operational risk management. Special emphasis will be placed on the analytical and modeling techniques for operational risk. Contents include Basel regulations, loss models, extreme value theory, copula, operational value-at-risk and operational risk derivatives. Machine learning techniques for managing operational risk will also be explored. The use
of statistical packages R will be demonstrated.
of statistical packages R will be demonstrated.
RMSC4007 Risk Management with Derivatives Concepts
This course aims at understanding the application of derivatives theories for the practical risk management. It starts by reviewing basic concepts of pricing and hedging derivatives, like risk-neutral valuation, arbitrage strategies, hedging strategies, implied volatilities and the Greeks. The Value-at-Risk framework for derivatives positions is discussed. Student will also learn how to apply option theoretic approach to credit risk management. Specifically, the capital structure model will be applied to measure the default probability. The Moody’s KMV methodology and CreditRisk+ are introduced. Advisory: For Risk Management Science, Quantitative Finance and Risk Management Science, Statistics majors only.
RMSC4102 Research Project
The course is to provide an opportunity for students to apply their knowledge to solve real-world problem. Students will be required to complete a group project, give a final project presentation and submit a written report, on which their assessment will be based. Advisory: For majors only.
RMSC4112 Research Project in Risk Analytics
In this course, students are required to review selected readings in academic journal in Statistics and Risk Management. Students are required to form a group to complete a project, in which the latest techniques of Risk Analytics are applied to tackle a real-world problem. They are also required to submit an interim and final written report, on which their assessment will be based. Advisory: For majors only.
RMSC4202 Practicum
The course serves to provide a bridge between the classroom and the real business world. Students will be required to complete a group project assigned by a company or an organization on a part-time basis. A team of three to five students will undertake a project under the joint supervision of an instructor and a member of the company or organization. Students will be required to give a final project presentation and submit a written report, on which their assessment will be based. Advisory: For majors only.
RMSC4212 Practicum in Risk Analytics
Students will join practicum in a financial-technology themed or start-up themed company on a full-time or part-time basis. Students are required to complete assignments about risk analytics jointly issued by the course instructor and a member of the company. They are also required to submit an interim and final written report, on which their assessment will be based. Advisory: For majors only.
RMSC1101 Elementary Concepts in Risk Management
1U This is an elementary course that introduces current issues and special topics in risk management. Students are required to present and discuss books and current articles in the related topics assigned by the instructor. Advisory: For majors only.
RMSC2001 Introduction to Risk Management
This course aims at providing a focused introduction to various concepts of risk and risk measures from a scientific perspective. The course will discuss the various roles that risk plays in insurance and financial applications. Current risk measures such as value at risk and shortfall risk will be introduced. These measures will be calculated for recent financial losses to illustrate their usefulness in risk management.
RMSC2101 Introductory Topics in Risk Management
1 U This is an elementary course aiming at introducing current issues and special topics in risk management. Students are required to read books and articles in the related topics assigned by the instructor. Advisory: For majors only.
RMSC3001 Principles of Credit Risk Management
This course introduces the general methodology for credit risk management – how should we handle the possibility our counterparty may not pay us what they owe? Answering this question depends on who the counterparty is and the nature of our contract with them. As such, in this course we explore credit risk models for retail customers, credit risk measures for portfolios, credit mitigation techniques for markets, credit derivatives used by traders and much else besides, all in the context of the latest Basel regulations and the lessons learned from Credit Crisis of 2007-8.
RMSC3101 Special Topics in Risk Management
1 U This is an intermediate course aiming at introducing current issues and special topics in risk management. Students are required to read books and articles in the related topics assigned by the instructor. Advisory: For majors only.
RMSC4001 Simulation Methods for Risk Management Science and Finance
This course starts with presenting standard topics in simulation including random variable generations, variance reduction methods and statistical analysis of simulation outputs. The course then reviews the applications of these methods to derivative security pricing. Topics addressed include: importance sampling, martingale control variables, stratification and the estimation of derivatives. Additional topics include the use of low discrepancy sequence (quasi-random numbers), pricing American options and scenario simulation for risk management.
RMSC4002 Financial Data Analytics with Machine Learning
This course covers modern data analysis techniques that are commonly used in finance and risk management. Topics include applications of multivariate techniques for data cleansing and modeling such as principal component analysis and canonical correlation analysis to asset management, Extreme Value theory, Value-at-Risks, GARCH modeling in estimating volatility, time series methods in term-structure analysis. Besides, the next few introductory topics in machine learning will also be covered, such as recommender system, logistic regression, k-means clustering, perceptrons, decision trees, artificial neural network, stochastic gradient descent, Naive Bayes Classifiers and Bayesian networks.
RMSC4003 Statistical Modelling in Financial Markets
This course is designed to introduce the current developments in risk management in the financial markets. Risk management ideas associated with three general important areas in finance will be discussed: asset management, derivative pricing and fixed income models. Emphasis will be placed on the statistical modelling aspects on some of the commonly used models in these areas.
RMSC4004 Theory of Risk and Insurance
This course covers the theory of risk and its applications to insurance. Topics include: classical and stochastic risk models, ruin theory, claims modelling and evaluations, risk premium pricing, loss distributions and creditability theory.
RMSC4005 Stochastic Calculus for Finance and Risk
This course starts with the introduction of the concepts of arbitrage and risk-neutral pricing. It then proceeds to discuss the stochastic calculus foundations for continuous-time finance models. Topics include: Brownian motion, stochastic integral, Itô’s formula, Girsanov’s change of measure, and the relationship between stochastic calculus and partial differential equations. Examples will be taken from equity options, including the Black-Scholes formula for foreign exchange and term-structure models.
RMSC4006 Operational Risk Management
This course introduces the general methodology for operational risk management. Special emphasis
will be placed on the analytical and modeling techniques for operational risk. Contents include Basel
regulations, loss models, extreme value theory, copula, operational value-at-risk and operational risk
derivatives. Machine learning techniques for managing operational risk will also be explored. The use
of statistical packages R will be demonstrated.
will be placed on the analytical and modeling techniques for operational risk. Contents include Basel
regulations, loss models, extreme value theory, copula, operational value-at-risk and operational risk
derivatives. Machine learning techniques for managing operational risk will also be explored. The use
of statistical packages R will be demonstrated.
RMSC4007 Risk Management with Derivatives Concepts
This course aims at understanding the application of derivatives theories for the practical risk management. It starts by reviewing basic concepts of pricing and hedging derivatives, like risk-neutral valuation, arbitrage strategies, hedging strategies, implied volatilities and the Greeks. The Value-at-Risk framework for derivatives positions is discussed. Student will also learn how to apply option theoretic approach to credit risk management. Specifically, the capital structure model will be applied to measure the default probability. The Moody’s KMV methodology and CreditRisk+ are introduced. Advisory: For Risk Management Science, Quantitative Finance and Risk Management Science, Statistics majors only.
RMSC4102 Research Project
The course is to provide an opportunity for students to apply their knowledge to solve real-world problem. Students will be required to complete a group project, give a final project presentation and submit a written report, on which their assessment will be based. Advisory: For majors only.
RMSC4112 Research Project in Risk Analytics
In this course, students are required to review selected readings in academic journal in Statistics and Risk Management. Students are required to form a group to complete a project, in which the latest techniques of Risk Analytics are applied to tackle a real-world problem. They are also required to submit an interim and final written report, on which their assessment will be based. Advisory: For majors only.
RMSC4202 Practicum
The course serves to provide a bridge between the classroom and the real business world. Students will be required to complete a group project assigned by a company or an organization on a part-time basis. A team of three to five students will undertake a project under the joint supervision of an instructor and a member of the company or organization. Students will be required to give a final project presentation and submit a written report, on which their assessment will be based. Advisory: For majors only.
RMSC4212 Practicum in Risk Analytics
Students will join practicum in a financial-technology themed or start-up themed company on a full-time or part-time basis. Students are required to complete assignments about risk analytics jointly issued by the course instructor and a member of the company. They are also required to submit an interim and final written report, on which their assessment will be based. Advisory: For majors only.