Module Catalogues, Xi'an Jiaotong-Liverpool University   
 
Module Code: MTH319
Module Title: Financial Engineering
Module Level: Level 3
Module Credits: 5.00
Academic Year: 2019/20
Semester: SEM1
Originating Department: Mathematical Sciences
Pre-requisites: N/A
   
Aims
This course gives a solid foundation towards the advanced numerical methods and other modeling techniques widely used in finance. It aims at reviewing the major financial models and modeling techniques used in practical applications, understanding their applicability and limitations, and at building an integrated framework allowing students to conduct comprehensive theoretical analyses and practical implementations.


The module is designed to complement the theoretical knowledge developed in the financial mathematics programme with practical applications.


The module not only contributes to the development of programming and computational skills of students but also improves the understanding of the financial mathematics theory via hands on practice with one of the most commonly used software.
Learning outcomes 
A Implement advanced modeling techniques in finance

B Conduct comprehensive theoretical analyses and practical applications in financial engineering

C Analyze and implement numerical schemas for financial derivatives

D Understand, analyze and implement derivatives pricing models by using financial models/numerical methods

E Analyze and apply financial models/numerical methods for portfolio optimization/allocation and performance attribution

Method of teaching and learning 
To give sufficient hands on experience the module is based on a mixture of lectures, tutorials and computer labs sessions. Computer labs equipped with a programming language will be utilized every week.


Furthermore, assignments and continuous work provides sufficient practice and timely feedback.

Syllabus 
Topic: Foundations

1. Mathematical foundations and pricing measures


Topic: Lattice and finite-difference methods in financial modeling

2. Discretization of time and state space

3. Lattice and tree implementations

4. Finite-difference schemes and applications


Topic: Monte Carlo method in Financial Engineering

5. Stochastic and local volatility models and Monte Carlo implementations

6. Pricing options with early exercise by Monte Carlo simulation

7. Sensitivities of Monte-Carlo prices and importance sampling


Topic: Stochastic modelling for interest rates and derivatives valuation

8. Interest rate structures and products

9. Heath-Jarrow-Merton (HJM) framework

10. Short rate models and derivative valuations


Topic: Theory and practice in active portfolio management

11. Asset allocation models (e.g., factor model, Treynor-Black model vs Black-Litterman model)

12. Portfolio performance measurement and evaluation


Topic: Intro to FinTech

13. Advances in financial machine learning and applications
Delivery Hours  
Lectures Seminars Tutorials Lab/Prcaticals Fieldwork / Placement Other(Private study) Total
Hours/Semester 26    13  13    98  150 

Assessment

Sequence Method % of Final Mark
1 Coursework 15.00
2 Coursework 15.00
3 Final Exam 70.00

Module Catalogue generated from SITS CUT-OFF: 8/24/2019 3:39:55 PM