Programme

Course Description

RMS 5001
Advanced Statistical Theory In Risk Management
This course discusses modern applications of advanced statistical methods in finance. Methods include times series methods, stochastic process approach, data mining, and Monte Carlo simulations.

RMS 5002 
Principles of Risk Management
This course provides students with fundamental concepts of risk and risk management. It further introduces risk management tools used in financial products. Topics include market risk, operational risk, integrated risk management and risk management Information Technology.

RMS 5003 
Risk Measures
Risk measurement and quantification are the fundamentals of risk management procedures. This course focuses on the methodologies of Value-at-Risk (VaR) such as historical simulation, parametric VaR, delta-gamma approximation and Monte-Carlo simulation. The uses of VaR in risk management are also addressed. Topics include portfolio risk management, asset allocation and measuring the performance of portfolio managers.

RMS 5004 
Seminar
Students need to present and discuss literatures assigned to them by the instructor on topics of current interest in financial risk management.

RMS 5101
Statistical Modeling 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 modeling aspects on some of the commonly used models in these areas.

RMS 5102
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.

RMS 6001
Interest Rate and Fixed Incomes Risk Management
Fixed income securities are highly sensitive to the fluctuation of interest rates. Thus interest rate modeling becomes crucial for pricing and managing fixed income securities. This course introduces various types of fixed income securities and interest rate models. It covers the celebrated Heath-Jarrow-Morton (HJM) model as well as some term-structure models including Ho-Lee, Hull-White and the CIR models.

RMS 6002 
Credit Risk Management
Credit risk is an important topic in the financial market in the way that over 70% of losses in the banking industry are caused by credit risk. This includes defaults of bank loans, corporate bonds and/or counter-parties. This course aims at providing students with some quantitative methods in credit risk management. Ideas of reduced-form models and structure models to credit risk are discussed. Software packages such as Creditmetrics^TM and KMV methodologies are introduced. Applications of credit derivatives are also addressed.

RMS 6003 
Operational Risk Management
Catastrophic losses are usually caused by a combination of market risk and credit risk along with failure of financial controls, which is a form of operational risk. This course introduces some tools in operational risk management. Topics include earnings volatility, casual networks actuarial models, capital allocation and regulatory requirements.

RMS 6004 
Special Topics in Risk Management
The course aims at discussing recent advances in risk management.

STA 5103
High-dimensional Data Analysis
This course emphasizes statistical methods for analyzing and interpreting high- dimensional data that are common in business management, marketing research, and other behavioral sciences. Selected topics include canonical correlations, classification, principal component, factor analysis, latent structure analysis, and discrete multivariate methods.

STA 6104
Financial Time Series
This course deals with the methodology and applications of business and financial time series. Topics include statistical tools useful in analyzing time series, models for stationary and non-stationary time series, seasonality, forecasting techniques, heteroskedasticity, ARCH and GARCH models, and multivariate time series.

STA 6105
Basic Actuarial Principles and Their Applications
This course develops the knowledge of basic actuarial principles applicable to a variety of financial security systems: life, health, and property & casualty insurance, annuities, and retirement systems. It includes the understanding of purpose of these systems, the design and development of financial security products, the concepts of anti-selection and risk classification factors.

STA 6107
Selected Topics on Data Science and Business Statistics
Recent topics on data science and business statistics are selected for discussion.

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