Course Details in 2024/25 Session

Module Title	LM Quantitative Funds Management
School	Mathematics
Department	Mathematics
Module Code	06 39848
Module Lead	TBC
Level	Masters Level
Credits	10
Semester	Semester 1
Pre-requisites
Co-requisites
Restrictions	None
Contact Hours	Lecture-24 hours Guided independent study-76 hours Total: 100 hours
Exclusions
Description	This module provides students with a deep understanding of asset pricing theories, quantitative methods, and their applications in managing investment portfolios effectively. This module equips students with the knowledge and skills required to analyse asset prices, evaluate investment opportunities, and make informed decisions in the realm of quantitative funds management. The module introduces students to the foundations of asset pricing, various asset pricing models, including the Capital Asset Pricing Model (CAPM), arbitrage pricing theory, and factor-based models like the Fama-French three(five)-factor model. They will learn how these models capture different aspects of risk and provide insights into asset pricing dynamics, quantitative methods for asset pricing and valuation. Students will learn how to estimate and interpret asset returns using statistical techniques, including time series analysis, regression analysis, and volatility modeling. They will explore empirical methods for estimating asset pricing factors and risk premia and gain practical experience in applying these methods to real-world datasets. The module also covers advanced topics in quantitative funds management, such as factor investing and smart beta strategies. Students will study different factor models, including value, size, momentum, and quality, and understand how these factors drive asset returns. They will learn how to construct factor-based portfolios, evaluate their performance, and analyze their risk exposures. Furthermore, the module addresses the challenges of managing quantitative funds in dynamic market conditions. Students will explore trading strategies, market microstructure, and the impact of transaction costs on portfolio performance. They will also learn about risk management techniques specific to quantitative funds, including value-at-risk (VaR) models, stress testing, and scenario analysis. Throughout the module, students will engage in practical exercises, case studies, and hands-on projects that involve analysing real-world financial data. They will utilize industry-standard software and tools for asset pricing, quantitative analysis, and portfolio management.
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 asset pricing theories, quantitative methods, and their application in quantitative funds management. They will be equipped with the skills to analyse asset prices, evaluate investment opportunities, and construct robust portfolios based on rigorous quantitative analysis.
Assessment
Assessment Methods & Exceptions	Assessment: 80% examination, 20% coursework. Reassessment: Resit examination
Other
Reading List