Course Details in 2024/25 Session

Module Title	LM Mathematical Securitisation
School	Mathematics
Department	Mathematics
Module Code	06 39847
Module Lead	TBC
Level	Masters Level
Credits	10
Semester	Semester 2
Pre-requisites
Co-requisites
Restrictions	None
Contact Hours	Lecture-24 hours Guided independent study-76 hours Total: 100 hours
Exclusions
Description	This module is designed to provide students with a comprehensive understanding of the mathematical models and techniques used in the securitization of financial assets. The module focuses on the analysis, structuring, and risk management of asset-backed securities (ABS) and mortgage-backed securities (MBS) using mathematical tools and quantitative methods. The module begins by introducing students to the fundamental concepts of securitization, including the role of originators, special purpose vehicles (SPVs), and investors. Students will gain an understanding of the motivations and benefits of securitization, as well as the challenges and risks associated with these structured financial products. Students will explore various types of asset-backed securities, such as residential mortgage-backed securities (RMBS), commercial mortgage-backed securities (CMBS), and collateralized debt obligations (CDOs). They will examine the cash flow structures, credit enhancements, and tranching mechanisms employed in these securities, and understand their impact on risk and return characteristics. The module will cover mathematical models used in the valuation and pricing of asset-backed securities. Students will learn how to analyse cash flows, estimate prepayment and default probabilities, and incorporate these factors into valuation models. They will explore techniques such as Monte Carlo simulation, option pricing models, and credit risk models to assess the fair value and risk profile of securitized assets. Risk management and hedging strategies in securitization will be discussed, including interest rate risk, credit risk, and liquidity risk. Students will learn how to identify and manage these risks through the use of derivative instruments, hedging strategies, and risk metrics such as value-at-risk (VaR) and stress testing. The module will also address regulatory considerations and accounting standards related to securitization, including Basel III guidelines, risk retention rules, and fair value accounting. Students will gain insights into the impact of regulatory frameworks on securitization practices and the importance of transparency and risk disclosure. Throughout the module, case studies and real-world examples will be used to illustrate the application of mathematical models in securitization. Students will have the opportunity to work on practical exercises involving data analysis, cash flow modeling, and risk assessment using software tools such as Excel or specialized financial modeling platforms.
Learning Outcomes	By the end of the module students should be able to: By the end of the module, students will have developed a strong foundation in mathematical securitization techniques and their applications in the financial industry. They will be equipped with the knowledge and skills necessary to analyse, value, and manage securitized assets, making them well-prepared for careers in investment banking, structured finance, risk management, or financial consulting.
Assessment
Assessment Methods & Exceptions	Assessment: 80% examination, 20% coursework. Reassessment: Resit Examination
Other
Reading List