computational finance programme

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Opportunities in
Quantitative Finance
A/P Ng Kah Hwa, PhD (Columbia)
Director, Quantitative Finance Programme
Director, Centre for Financial Engineering
12 March 2005
Slide 1
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
12 March 2005
Slide 2
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.
12 March 2005
Slide 3
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 mange the risk?
12 March 2005
Slide 4
Examples (continued)
Tools
• Linear Algebra and Calculus
• Advanced probability and statistics
• Time Series Analysis
• Simulation Methodologies
12 March 2005
Slide 5
Examples
Derivatives Trading
Pricing and Hedging of Complex Derivatives
Tools
• Advanced Stochastic Processes
• Numerical solutions to partial differential
equations
12 March 2005
Slide 6
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
12 March 2005
Slide 7
Career Opportunities
Jobs
• Financial Product Development and
pricing (Structured Deposits, Derivatives
etc.)
• Risk Management
• Investment decision making and fund
management
• Wealth Management
12 March 2005
Slide 8
Skills Required for Quantitative
Analysts/Risk Managers
• Basic Quantitative Skills
- Mathematics (Linear Algebra, Calculus)
- Probability
- Statistics
• Computer programming
- Excel, VBA, C/C++, SAS
• Knowledge of Derivatives and Fixed
Income
12 March 2005
Slide 9
Objective
 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.
12 March 2005
Slide 10
Introduction
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
Current programme committee:
• A/P Ng Kah Hwa (Programme Director)
• A/P Tan Hwee Huat (Deputy Director)
12 March 2005
Slide 11
The Honours-Track programme
 Students are only admitted to QF Major after two
semesters of studies in the Science Faculty.

Students admitted to QF major are placed in the
honours track leading to a B.Sc (Hons) degree upon
completing the course work requirement (given later).

A student may, however, for various reasons, opt to
exit earlier with a B.Sc upon completing the
corresponding course work requirement (given next
slide).
 Typically, a student will require 3 and 4 years to
complete the requirement for B.Sc and B.Sc (Hons)
respectively. A shorter timeframe is possible for some.
12 March 2005
Slide 12
Coursework Requirement
for B.Sc.




Satisfy University requirements for B.Sc.
Satisfy Faculty requirements for B.Sc.
Pass a total of 70 MCs at level 1000 to 3000 to satisfy the Major
requirements
Essential Modules include:
•
•
•
•
•
•
•
•
•
•
•
•
•
CS1101 Programming Methodology
CS1102 Data Structures and Algorithms
CF3101 Investment Instruments: Theory and Computation
FNA1002 Financial Accounting
FNA2004 Finance
MA2222 Basic Financial Mathematics
MA3245 Financial Mathematics I
MA1101R Linear Algebra I
MA1102R Calculus
MA1104 Advanced Calculus I
MA2213 Numerical Analysis I or CZ2105 Numerical Methods for Scientific
Computing I
MA2101 Linear Algebra II or MA2215 Linear Programming or ST2132
Mathematical Statistics
ST2131 Probability
12 March 2005
Slide 13
Coursework Requirement
for B.Sc. (continued)
Elective Modules include:
• CF3201 Basic Derivatives and Bonds
• CS3230 Design & Analysis of Algorithm
• FNA3101 Corporate Finance
• FNA3103 Financial Markets
• FNA3117 Bank Management
• FNA3118 Financial Risk Management
• MA3220 Ordinary Different Equations or MA3264
•
•
Modeling via Ordinary Differential Equations
MA3236 Nonlinear Programming
ST3131 Regression Analysis
12 March 2005
Slide 14
Additional Requirements
for B.Sc (Hons) (continued)
 Essential modules include:•
•
•
•
CF4100 Honors Project
CF4102 Financial Trading and Modeling
CF4103 Financial Time Series: Theory and Computation
MA4257 Financial Mathematics II
•
CZ4105 Numerical Methods for Partial Differential Equations or
MA4255 Numerical Partial Differential Equations
FE5103 Equity Products and Exotics
FNA4111 Research Methods in Finance
FNA4112 Seminars in Finance
MA4253 Mathematical Programming
MA4264 Game Theory
MA4265 Stochastic Analysis in Financial Mathematics
MA4267 Discrete Time Finance
ST4231 Computer Intensive Statistical Methods
ST4233 Linear Models
 Elective modules include:•
•
•
•
•
•
•
•
•
12 March 2005
Slide 15
Professional Certification
Professional Risk Manager (PRM) Certification
 Designed for those:• Seeking professional certification in risk
management
• Looking to develop their skills
• Looking for skills assessment of potential
employees
CFA Certification
CFA Cross-over with PRM
12 March 2005
Slide 16
Admission Requirements
 Students are only admitted to QF Major after two
semesters of studies in the Science Faculty.
 To be considered for admission, a student must :• achieve a CAP of at least 3.5;
• complete his/her first 2 semesters including the
group of four qualifying modules:
1)CS1101 (Programming Methodology)
2)MA1102R (Calculus)
3)MA1101R (Linear Algebra)
4)ST2131/MA2216 (Probability)
• the group average point (GAP) for the qualifying
modules must be at least 3.5.
12 March 2005
Slide 17
How to Apply
 At the end of semester 2, and after obtaining the examination
results, interested students should e-mail Ms Au Kasie at
[email protected] to request for an application form OR
 Collect the application form from the Department of
Mathematics General Office, S14-03-07.
 Send in the hard copy of the application form together with a
copy of your NUS academic results to Ms Au Kasie by the
application deadline.
 Students are encouraged to submit their application as early
as possible to facilitate the processing of their application.
 For more information, please go to
http://www.math.nus.edu.sg
12 March 2005
Slide 18
12 March 2005
Slide 19
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