Quantitative Finance – (M.Sc.)

Contents

We review all our courses regularly to keep them up-to-date on issues of theory, practice and relevance. Therefore, there might be some late changes to the detailed content of the modules, and occasionally to module titles.

To satisfy the requirements of the degree programme students must complete:

nine core courses

and

five electives

or

one elective and a Business Research Project

Two Induction Weeks The Quantitative Finance course starts with two compulsory induction weeks, focused on:

• an introduction to careers in finance and the opportunity to speak to representatives from over 75 companies during a number of different industry specific fairs.
• a reminder course of advanced financial mathematics, statistics and basic computing which forms a prerequisite of the core modules in term 1

Four core modules (30 hours each)

Asset Pricing

This course introduces students to the basic concepts used for pricing and analysing financial securities, focusing on spot markets. The efficiency of financial markets is discussed together with the question of whether stock prices are predictable. The importance of the risk and its trade off with return will be analysed in depth. The course is academically rigorous in outlining theoretical models but also focuses on the practical applications and discusses empirical finding.

Numerical Methods 1: Foundations

This module introduces basic concepts used in numerical methods and integrates them with a programming language. This module is lab based and will cover Root finding and non-linear sets of equations; Solution of linear systems; Interpolation and extrapolation; Integration of functions; Partial differential equation; Generation of random number. This module uses Matlab as the programming language and does not require any prior knowledge of programming.

Derivatives

The course will develop an in depth understanding of forwards, futures and swaps and their application in risk management situation. The course covers stock index futures, commodity forward and futures, interest rate derivatives, portfolio insurance, credit derivatives and embedded derivatives for corporate applications.

Foundations of Econometrics

The course aims at introducing students to the technical issues in statistical analysis of financial data such as estimation of time series models, forecasting of financial and economic data, and the modelling of asset prices volatility. The course will be based on standard econometric packages like PC Give.

Four core modules (30 hours each)

Fixed Income Securities

This module will acquaint students with the main modelling used in fixed income securities as well as provide students with a good understanding of various fixed income security products. It will enable students to use models in this area for practical applications.

Numerical Methods 2: Applications in Finance

This module builds on Numerical Methods 1 and focuses on applications to finance. Students will learn how to generate stochastic processes; Monte Carlo Simulations; Trees; Pricing American options; Applications in risk management. This module again integrates the programming language Matlab and is lab based.

Risk Analysis

The aim of this module is to develop a solid background for evaluating, managing and researching financial risk. To this end students will learn to analyse and quantify risk according to current best practice in the markets, as implemented in the RiskMetrics and CreditMetrics methodologies.

Econometrics of Financial Markets

This module will cover recent advances in the field of financial econometrics, with particular emphasis on high frequency finance and data types, linear time series models and forecasting, GMM and maximum likelihood estimation methods in finance. Further, students will gain exposure to the most recent literature related to modelling return distributions and volatility, focussing on seasonal and realised volatility dynamics, volatility processes/conditional volatility models, correlation, dynamic correlations and multivariate risks.

Five electives (18 hours each)

OR

One elective and a Business Research Project

Electives

You may choose from a wide variety of electives. For example:

• Hedge Funds
• Exotic Options
• Equity Investment
• Technical Analysis and Trading Options
• Advanced Financial Engineering and Credit
• Trading & Hedging in the Forex market
• Behavioural Finance
• C/C++
• Visual Basic

Research Methods module

This compulsory module trains students to undertake independent research either in the context of a single organisation or by using third-party sources. It provides the necessary tools and skills to initiate, research and write up a business project and includes training in research methodology, availability of data sources, project writing, time-management and presentation skills. These skills will be invaluable to students in their future career whether or not they choose to complete a project.

Accreditation

An integral part of City University London, Sir John Cass Business School is among the global elite of business schools that hold the gold standard of 'triple-crown' accreditation from the Association to Advance Collegiate Schools of Business (AACSB), the Association of MBAs (AMBA) and the European Quality Improvement System (EQUIS). We are consistently ranked amongst the best business schools and programmes in the world which, coupled with an established 40-year reputation for excellence in research and business education, enables us to attract some of the best academics, students and businesses worldwide into our exclusive Cass network.