Introductory description

The module provides an introduction to financial analytics by applying various (analytical, statistical and mathematical) techniques to financial market and investment portfolios. As an important aspect of financial analytics we introduce various modelling and solving approaches for decision making problems arising in finance. We look at the analytics process from data management, modelling and computational tools perspectives. We will review various widely used approaches to portfolio analytics and introduce modelling approaches for portfolio analytics system design. The theoretical and practical aspects of various approaches will be motivated through underlying financial decision making problems using the financial market data and complexities of financial decision making problems will be addressed.

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

The main topics to be covered in Financial Analytics may include fixed income securities, bond and stock valuation, asset allocation, portfolio optimisation, risk management, asset and liability management, cash-flow matching, derivatives and option pricing.

Learning outcomes

By the end of the module, students should be able to:

• Demonstrate a comprehensive understanding of various analytics concepts commonly used in finance
• Demonstrate an understanding of theoretical and practical aspects of modelling and solving financial problems
• Critically evaluate the strengths and weaknesses of different approaches
• Analyse and evaluate case studies and model and solve the underlying problems effectively

Indicative reading list

• Edward E. Williams, Quantitative Financial Analytics: The Path to Investment Profits, 2017

• Mark J. Bennett and Dirk L. Hugen, Financial Analytics with R: Building a Laptop Laboratory for Data Science, 2016

• Marcello Minenna, A Guide to Quantitative Finance: Tools and Techniques for Understanding and Implementing Financial Analytics, 2006

• Yves Hilpisch, Derivatives Analytics with Python: Data Analysis, Models, Simulation, Calibration and Hedging, The Wiley Finance Series, 2015

• Wolfgang Marty, Fixed Income Analytics: Bonds in High and Low Interest Rate Environments, 2020

• S. A. Zenios, Practical Financial Optimization: Decision Making for Financial Engineers, John Wiley & Sons, 2008

• G. Cornuejols and R. Tutuncu, Optimization Methods in Finance, Cambridge University Press, 2018

• W. T. Ziemba and R. G. Vickson, Stochastic Optimization Models in Finance, World Scientific, 2006

• F. Fabozzi, P. Kolm, D. Pachamanova, S. Focardi, Robust Portfolio Optimization and Management, John Wiley & Sons, 2007

• D. G. Luenberger, Investment Science, 2nd Edition, Oxford University Press, 2013

• F. Fabozzi, D. Pachamanova, Portfolio Contruction and Analytics, John Wiley & Sons, 2016.

Subject specific skills

Evaluate and apply analytics to financial decision making problems
Develop and demonstrate modelling skills to formally describe and model typical financial problems
Appraise, evaluate and then use a range of modelling and solution approaches for typical financial decision making problems

Transferable skills

Demonstrate problem solving skills and implementation of computational tools