Download Technical skills trained - Department of Mathematics

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts

Derivative (finance) wikipedia , lookup

Financial crisis wikipedia , lookup

Systemically important financial institution wikipedia , lookup

Systemic risk wikipedia , lookup

Transcript
How does this Program equip students for a successful
career in financial engineering?
- technically skilled and financially streetwise
(development of an intuitive mind)
• Assessing risk – portfolio level or individual structured
products; statistical analysis, stress testing
• Empirical methods and statistical tools in financial
analysis
• Developing structured products from the ground up –
nature of risks, hedging strategy, pricing vehicles
(implementation of model calculations and
interpretation of results)
Technical skills trained
• Understanding the complexity in structured products:
•
•
•
•
Analytics of pricing models and their numerical
implementation
Fundamental concepts in financial economics
Analytic statistical and stochastic tools: Stochastic
Calculus, Financial Time Series,
Use of statistical packages
Mastery of a high level programming language (C++)
Courses in the MSc Program
Foundation courses
MAFS501
Stochastic Calculus
[Fall, 08]
Instructor: Professor B.Y. Jing of Mathematics Department
Meeting hours and Venue: Thurs 19:30pm - 20:50pm;
Sat: 9:00am - 10:20am; Room 4502
•
Brownian motions. Diffusion processes.
•
Ito’s calculus.
MAFS502 Advanced Probability and Statistics
[Summer, 08]
For those full-time students who have missed MAFS502 in the
summer session, you are advised to take either
MATH541
Advanced Probability and Statistics I (Prof B.Y. Jing)
or
MATH531
Advanced Numerical Methods
or
MATH551
Mathematical Methods in Science and Engineering I
Financial Mathematics
MATH571 Mathematical Models of Financial Derivatives [Fall, 08]
Instructor: Prof Y.K. Kwok of Mathematics Department
Meeting hours and Venue: Tues and Thurs 11:00am - 12:20pm;
Room 4502
•
Black-Scholes-Merton pricing framework
•
Dynamic hedging, replicating portfolio

Martingale theory of option pricing

Risk neutral measure
MAFS524 Software Development with C++ for Quantitative Finance [Fall, 08]
Instructor: Dr C.D. Shum
Meeting hours and Venue:
Sat 11:00am - 12:20pm;
Sat: 13:30pm - 14:50pm;
Room 2612A
•
Abstract data types
•
Object creation; Initialization
•
Toolkit for large scale component programming
MAFS601 Special Topics in Financial Mathematics
[Fall, 08]
“Fixed Income Derivatives and Structured Hybrid Products”
Instructors: "quants" in industry
Meeting hours: Saturday 15:30pm - 18:20pm
This topic course discusses the product nature, hedging, pricing and
risk management methodologies of the commonly traded fixed
income derivatives and structured hybrid products in the financial
markets. Products include exotic swaps, equity-linked products,
structured credit derivatives, and others. Illustrative case studies of
real financial products will be provided.
MATH572
Interest Rate Models
[Spring, 09]
MAFS521
Mathematical Models of Investment
[Spring, 09]
MAFS523
Advanced Credit Risk Models
[Spring, 09]
MAFS525
Computational Methods for Pricing Structured
Financial Products
[Summer, 09]
Statistics courses
MAFS511
Advanced Data Analysis with Statistical Programming
[Fall, 08]
Instructor: Professor Mike So of ISMT Dept
Meeting hours and Venue: Tues 19:30pm - 22:20pm; Room 4502
•
Reading and describing data
•
Categorical data and longitudinal data
•
Correlation and regression
•
Nonparametric comparisons
Implementation of statistical tools in SAS
MAFS522 Quantitative and Statistical Risk Analysis [Spring, 09]
MAFS512 Applied Multivariate Analysis
[Spring, 09]
MAFS513 Quantitative Analysis of Financial Time Series
[Spring, 09]
Upon completion of the program, students are expected to achieve
the following intellectual abilities
• A broad knowledge and understanding of the financial
products commonly traded in the markets and various
practical aspects of risk management.
• Use of mathematical and statistical tools to construct
quantitative models in derivative pricing, quantitative
trading strategies, risk management, and scenario
simulation, including appropriate solution methods and
interpretation of results.
To graduate from the MSc program, each student is required to
complete 30 credits of which
• 6 credits from the list of foundation courses
• 9 credits from the list of courses in statistics
• 9 credits from the list of courses in financial mathematics
• 6 credits as free elective* or independent project (MAFS 699)
• Free elective can be any mathematics course at 300-level or above,
or any course outside the department at 500-level course or above.
Maintain a graduation grade point average of B grade or above.