Module Catalogues, Xi'an Jiaotong-Liverpool University

Module Code: MTH319
Module Title: Financial Engineering
Module Level: Level 3
Module Credits: 5.00
Semester: SEM1
Originating Department: Mathematical Sciences
Pre-requisites: CSE212 CSE212 OR CPT206 MTH202

 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 financeB Conduct comprehensive theoretical analyses and practical applications in financial engineeringC Analyze and implement numerical schemas for financial derivativesD Understand, analyze and implement derivatives pricing models by using financial models/numerical methodsE 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 measuresTopic: Lattice and finite-difference methods in financial modeling 2. Discretization of time and state space3. Lattice and tree implementations4. Finite-difference schemes and applicationsTopic: Monte Carlo method in Financial Engineering 5. Stochastic and local volatility models and Monte Carlo implementations6. Pricing options with early exercise by Monte Carlo simulation7. Sensitivities of Monte-Carlo prices and importance samplingTopic: Stochastic modelling for interest rates and derivatives valuation 8. Interest rate structures and products9. Heath-Jarrow-Merton (HJM) framework10. Short rate models and derivative valuationsTopic: Theory and practice in active portfolio management11. Asset allocation models (e.g., factor model, Treynor-Black model vs Black-Litterman model)12. Portfolio performance measurement and evaluationTopic: 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: 6/5/2020 9:17:16 PM