MSc Financial Engineering
Programme Content Part 2

Part 2 - Compulsory Modules:

  • C++ for Financial Engineering
  • Topics in Financial Engineering
  • Equity and Foreign Exchange Derivatives Modelling
  • Interest Rate Derivatives Modelling
  • Credit Derivatives Modelling
  • Essentials of Financial Engineering

Plus a choice of 40 credits from the optional modules below:

Part 2 - Optional Modules:

  • Advanced Methods for Financial Research
  • Bond Market Pricing and Trading Strategies
  • Financial Econometrics
  • Hedging
  • Liquidity Risk
  • Market Risk
  • Portfolio Management
  • Research Project
  • Volatility Analysis

A selection of modules from the Department of Mathematics is made available on an annual basis subject to satisfying any pre-requisites.

Part 2 - Compulsory Modules

C++ for Financial Engineering

Convenor: TBC
Credits:10

Aims:

This module teaches essential skills for C++ programming with emphasis on practical applications in financial engineering. The main objective is to provide intuitive understanding of quantitative finance and to prepare the students, through small assignments and projects, for real world requirements in the industry.

Intended learning outcomes:

Assessable outcomes

By the end of the module, it is expected that students will be able to:

    * Design and construct simple pricing applications in C++
    * Use classes and objects for pricing derivative securities
    * Apply templates and the inheritance property
    * Use Excel as interface for C++ programs

Additional outcomes

Students will learn about effective design of a program and how to make it user-friendly, compatible with other applications and easily extendable. Also, students will get accustomed with the application-specific programming techniques used in the industry.

Outline content:

(1) Fundamentals; Pointers, Function Overloading and Operator Overloading

(2) Classes and Objects

(3) Inheritance

(4) Template Programming

(5) Interactions with Excel

(6) Applications in Financial Engineering 

Topics in Financial Engineering

Convenor: Jacques Pezier
Credits: 10

Aims:

Designed for future quants and financial engineers to introduce them to the main types of problems they will be asked to solve and to make them aware of the range of issues they will have to consider.

Financial engineering is the art of designing and implementing innovative solutions to financial problems. This course explores a number of typical problems faced by both financial and non-financial institutions for which a range of solutions, often using derivative products, is possible.

In each case we examine the feasibility and relative advantages and disadvantages of alternative solutions, taking into account legal, accounting, tax and regulatory matters as well as risks and returns.

Intended learning outcomes:

Assessable outcomes

By the end of the module, it is expected that students will be able to:

  •  A working understanding of main types of derivative and hybrid instruments (equity swap, interest rate swaps, options, convertibles, CDSs, CDOs) 
  •  An awareness of the legal, tax, accounting and regulatory environment in which these instruments may be used
  • An understanding of the main types of financial problems face by firms in fund raising, creation of capital, merger and acquisition, long term investments, risk management and incentive schemes
  • A working knowledge of pricing and evaluation methods for derivative products

Additional outcomes

Students will be encourage to discuss the pros and cons of various financial engineering solutions and to explain which might be particularly interesting or difficult to implement in their own countries.

Outline content:

1. Facilitation of acquisition and disposal of shares, preparation for mergers - Equity swaps, CVRs and quantity options
2. Tax efficient structures and strategies - Long term investment products, tax efficient financing, executive incentive schemes
3. Creation of cheap Tier 1 and upper Tier 2 capital for banks - Convertibles and other hybrids
4. Market risk management - Index linked structured products, overlay strategies, dynamic control strategies
5. Credit risk management - credit risk protected loans, CDSs and securitization

Credits Derivatives Modelling

Convenor: Leonardo Nogueira
Credits: 10

Aims:

This module familiarizes the students with the necessary tools to model credit risk. It explores  the different approaches to credit risk analysis. The models are then applied to the valuation and hedging of the essential types of credit derivatives. In addition, typical trading strategies in the credit markets are analysed.

Intended learning outcomes:

Assessable outcomes

By the end of the module, it is expected that students will be able to:

  • Describe and analyse the main approaches in modelling credit risk
  • Apply the related mathematical tools
  • Identify the major credit derivatives
  • Present and appraise the pricing methodologies
  • Describe and analyse some popular trading strategies

Additional outcomes

This module creates awareness of the complex mathematical tools for credit risk, a fast growing business. Students will get a synthesis of the available modelling approaches and get acquainted with the relevant literature. The second part of the course will, besides presenting valuation methods, familiarize students with the credit derivatives market particularities.

Outline content:

The module has two parts:

Part (a) Tools for credit risk modelling

  1. Two main approaches to model credit risk:
    - Adapting the contingent claims analysis to credit risk valuation         
    - Modelling credit risk with the Cox process approach
  2. Analysis of stochastic intensity models
  3. Modelling dependence with Copulas

Part (b) Credit derivatives in practice

  1. Valuation and trading of Credit Default Swaps
  2. Valuation and trading of Basket Default Swaps and Collateralized Debt Obligations
  3. The standardized correlation markets: trading i-traxx and CDX tranches
  4. Valuation and trading of Credit Default swaptions

Equity and Foreign Exchange Derivatives Modelling

Convenor: Leonardo Nogueira
Credits:10

Aims:

This module introduces extensions to the Black-Scholes framework to accommodate the empirical evidence from equity and FX markets, namely stochastic volatility and jumps. It also reviews some exotic instruments and the techniques for their pricing and hedging.

Intended learning outcomes:

Assessable outcomes

By the end of the module, it is expected that students will be able to:

  • Outline the possible extensions to the Black-Scholes model
  • Price and hedge options in the presence of jumps and/or stochastic volatility
  • Describe what is meant by an incomplete market and how this affects the pricing and hedging of options
  • Outline simple exotic instruments and propose techniques to price them
  • Differentiate between dynamic replication and static replication of exotic options

Additional outcomes

This module focuses on the models that are popular in equity and FX derivative desks. It makes intensive use of stochastic calculus but always with some background from empirical evidence to motivate the choice of a model. Calibration issues and model risk are also considered.

Outline content:

The module has two parts:

Part I: Extending the Black-Scholes framework

  • Black-Scholes assumptions and empirical evidence from equity and FX markets
  • Implied volatility smile and smile-consistent models
  • Stochastic volatility models
  • Jump models

Part II: Pricing and Hedging of Exotic Instruments

  • Review of popular exotic options (including basket instruments)
  • Static replication versus dynamic replication
  • Techniques to price exotic options
  • Hedging in incomplete markets
  • Discussion on calibration and risks associated with the choice of a model

Interest Rates Derivatives Modelling 

Convenor: Leonardo Nogueira
Credits:10

Aims:

To convey the basic concepts and analytical methodology for interest rate modelling and the valuation of interest based products.

Intended learning outcomes:

Assessable outcomes

By the end of the module, it is expected that the student will be able to:

  • work with some of the state of the art interest rate models
  • price interest rate products and equity derivatives under a stochastic interest rate
  • digest literature on interest rate modelling at an the introductory level
  • work in a support function, such as product structuring, in a derivatives business
  • use this as a platform for further research

Additional outcomes

The module creates awareness of the mathematical prerequisites for working in this subject.

This is turn may help the student to decide to what extent, and in which direction, derivatives might be a suitable career choice.

Outline content:

  1. The martingale method for interest rate modelling
  2. The classical interest rate models of Vasicek, CIR, HL, HW
  3. The HJM modelling framework
  4. The contemporary Libor market model and the Swap market model
  5. Valuation of interest based derivatives using the above interest rate models
  6. Calibration of market models and HWE

Essentials of Financial Engineering

Convenor: Dr Marcel Prokopczuk
Credits:10

Aims:

To introduce the key principles and techniques of financial engineering in forex, interest rate and credit markets and illustrate the benefits of financial engineering with a number of applications.

Intended learning outcomes:

Assessable outcomes

By the end of the module, it is expected that the student will be able to:

  • Understand and analyse most types of structured products currently available in the global capital markets.
  • Solve a large variety of financial problems by designing and valuing one or more structured solutions.

Additional outcomes

The module aims to encourage independent business-orientated thinking.

Outline content:

  1. Motivation. Cash flow engineering and forward contracts
  2. Currency Forwards and Cross Currencies FX-Swaps: Quotation conventions, bid-ask spreads; credit risks; arbitrage possibilities
  3. Major Interest Rate (IR) swap structures.  Pricing and hedging IR swaps. Uses
  4. Credit Markets: CDS engineering, creidt indices and CDO's
  5. FX and IR options and swaptions.

Part 2 - Optional Modules

Advanced Methods for Financial Research

Convenor: William T Ziemba
Credits: 10

Aims:

This module will discuss a number of important research topics in finance. It will review current research in various areas, which will include but will not be limited to: the strategies and approaches of a number of great investors and speculators in various financial markets; futures and options; horseracing to stock and mutual fund selection; value investing and hedge fund investing. 

Outline Content:

Class 1: Risk aversion, stochastic dominance and stochastic optimization
Class 2: Analysis of Race track betting strategies and professional syndicates
Class 3: Great Investors and their Strategies
Class 4: How do we research in finance – from idea to publication
Class 5: A topic from the current world of finance.

Bond Market Pricing and Trading Strategies

Convenor: Andy Bevan
Credits: 20

Aims:

The main aims of the module are to identify the fundamental determinants of short- and long-term interest rates, learn how to monitor developments in interest rate markets and employ commonly used trading strategies. The course will be based around the work of a research department in an investment bank when formulating strategy for its proprietary trading desk and hedge fund customers. Each lecture will provide: (1) a concise outline of economic theory, (2) practical examples of events in markets from recent years, and (3) identification of trading strategies. Seminars will focus on market pricing conventions and worked examples.

Outline Content:

  1. Flow of Funds and the Economics of Interest Rates
  2. Monitoring Central Banks and the Determination of Short Rates
  3. Pricing and Trading of Short Rate Instruments
  4. Fundamentals of Bond Pricing, Duration and Convexity
  5. Fitting the Yield Curve and Theories of the Term Structure
  6. Trading of Bonds, Bond Forwards and Futures
  7. Pricing and Trading of Interest Rate Swaps
  8. Swap Spreads and Corporate Bond Spreads Through the Business Cycle
  9. Bond Options and Contingent Cash Flows
  10. Cross-Country Risk and Foreign Exchange

Commodity Derivatives

Convenor: Konstantina Kappou
Credits: 10

Aims:

This module aims to provide students with a detailed knowledge of the Commodity Derivatives Markets. It examines the aspects of pricing and trading physical derivatives and their complexity relative to financial derivatives, with emphasis on the Energy (Oil) and Shipping (Freight) sectors

Outline Content:

  • Introduction to Commodity Markets, History and Evolution
  • Precious Metals. Energy Products. Soft Commodities
  • Main Market Players and Foward Curve. Basis Risk
  • Commodity Derivatives. Exchanges and OTC transactions
  • The Oil Market and its Mechanisms.  OPEC and DOE. Crude Supply and Demand.  Inventories
  • Crude Products and Crack Spreads
  • Refineries and Margins
  • The Freight Market and its Mechanisms.  The Baltic Exchange and the Shipping Industry.  Forward Freight Agreements.
  • Pricing of Commodity Derivatives - Swaps, Options and Structured Trades
  • Trading Techniques and Numerical Examples

Financial Econometrics

Convenor: Alfonso Dufour
Credits: 20

Aims:

Building on the material introduced in Quantitative Methods for Finance, this module examines a number of additional techniques that are relevant for financial applications, and in particular for modelling and forecasting financial time series. An introduction to the method of maximum likelihood estimation will be given, and emphasis will be placed on modelling volatility and its prediction. Case studies from the academic finance literature are employed to demonstrate potential uses of each approach. Extensive use is also made of financial econometrics software to demonstrate how the techniques are applied in practice.

Outline Content:

Topic 1: Stylised characteristics of financial data

Topic 2: Univariate linear time series models

  • ARIMA (Box Jenkins) approaches- model identification, estimation and diagnostic testing
  • Forecasting using ARIMA models; forecast appraisal

Topic 3: Simultaneous equations models

  • Simultaneous equations bias
  • Identification
  • Estimation, triangular systems
  • Case study: the relationship between trading activity and the bid-ask spread

Topic 4: Vector autoregressive models

  • Motivation, formulation, estimation
  • Comparison with structural models
  • Causality, impulse response functions, variance decompositions

Topic 5: Co-integration revisited: the Johansen approach, hypothesis testing using Johansen

Topic 6: Volatility modelling using generalised autoregressive conditionally heteroscedastic model

  • The ARCH Family of models
  • Testing for ARCH effects
  • Estimation issues
  • Variants and extensions of the ARCH model
  • Multivariate GARCH

Topic 7: Simulations methods in econometrics and finance

  • Motivation
  • Pure simulation versus bootstrap
  • Variance reduction techniques

Topic 8: Guest speaker from an investment bank

Topic 9: urther econometric analysis using EViews

Hedging*

Convenor: Jacques Pézier
Credits: 20

Aims:

This course is designed for students seeking a career in ‘front office' risk management whether in banks, fund management or corporate treasury. Hedging is financial risk management in action; it is often cited as the raison d'etre of derivatives markets - trading and arbitrage playing the supporting roles of providing liquidity and keeping prices fair and thus facilitating hedging. Corporates can reduce uncertainty by hedging away financial risks that fall beyond their areas of competence; fund managers can design hedge strategies that provide risk/reward profiles tailored to their clients; but it is in banking, which core activity is financial risk management, that efficient hedging makes the difference between success and failure.

Outline Content:

Topic 1: Assessment of risk, risk attitude, risk adjusted performance measures
Topic 2: Risks in financial markets and hedging principles
Topic 3: Market Risk: Static Hedging
Topic 4: Market Risk: Dynamic delta hedging
Topic 5: Market Risk: Gamma and volatility hedging; portfolio insurance
Topic 6: Credit Risks: Credit derivatives and other forms of credit risk mitigation
Topic 7: Multifactor hedging: Forex and interest rate risks
Topic 8: Impact of hedging on regulatory and economic capital
Topic 9: Hedging programmes banks, investment firms and corporates

Liquidity Risk

Convenor: Alfonso Dufour
Credits: 10

Aims:

The evolution of algorithmic trading, the proliferation of alternative trading platforms for trading the same security and the development of new products and assets with limited liquidity have contributed to raising the awareness of academics and traders on the importance of understanding and properly managing liquidity and execution risks.

The objective of this course is to give students an introduction to liquidity and execution risks and an overview of the methods for managing these risks. The issues discussed in this course are important when developing trading strategies, valuing portfolios, liquidating large positions and transitioning assets to new investments.

Outline content:

  1. Introduction. Security trading industry.
    New market mechanisms, intercontinental exchanges and regulatory challenges: fragmentation and consolidation (NYSE-Euronext, NASDAQ-OMX, LSE-Borsa Italiana).
  2. MiFID and Reg-NMS.
    Recent regulatory trends and expected impacts on markets (Transparency, Fragmentation, Internalisation)
  3. Traders and their motivation to trade. Profit motivated traders. Utilitarian traders. Liquidity suppliers.
  4. Order book trading: The LSE rule book
  5. Transaction cost measurement
  6. Execution Risk and Optimal Trading Strategies.

Market Risk

Convenor: Emese Lazar
Credits: 20

Aims:

This module provides an understanding of the Value-at-Risk (VaR) framework for market risk assessment and control. The module has a significant practical component with computer-based workshops that are designed to support the lecture material.

Outline Content:

  • Market Risk Management
  • Understanding Volatility
  • Covariance Matrices
  • Market Risk Metrics
  • Market Risk Control
  • Value-at-Risk Models
  • Model Validation
  • Scenario Analysis

Portfolio Management

Convenor: Jacques Pézier
Credits: 20

Aims:

The module aims to build on the techniques for portfolio selection that will have been introduced in the Securities, Futures and Options module. The module will address both the theory and practice of portfolio management. The theoretical part will examine the issues involved in constructing an investment portfolio, evaluating the performance of that portfolio, and adjusting its composition through time to ensure that its performance remains optimal. It will also consider the use of derivatives in managing risk. The practical part will provide students with hands-on experience of constructing and managing an equity portfolio.


Research Project

Convenor: Charles Sutcliffe
Credits: 20

Aims:

The aim of the research project is to allow students to define and execute a piece of research in finance on a topic of their choice, with direction from an academic supervisor and with assistance from a doctoral student support supervisor.

Outline Content:

The self-directed nature of study for this model should encourage students to be resourceful in their search for relevant literature and data, and to manage the various stages involved effectively, leading to timely submission of the finished piece.

Principles of Financial Engineering

Convenor: Marcel Prokopczuk
Credits: 20

Aims:

The module will present an applied, innovative approach to Financial Engineering from a practical point of view. Cutting-edge issues from financial markets will be utilised in a systematic way to discuss and identify the principles of Financial Engineering. The treatment focuses on the mechanics of major applications in today's markets.

Volatility Analysis

Convenor: Carol Alexander
Credits: 20

Aims:

This module provides an in depth understanding of the different approaches to modelling financial market volatility in discrete and continuous time. The module will focus on GARCH statistical models and the local and stochastic volatility models that are now in standard use by leading industry practitioners, and which have been the subject of extensive academic research. It is has a high quantitative content and a significant practical component with computer-based workshops (face-to-face and distance) designed to support the material.

Outline Content:

  • Statistical models of Volatility and Correlation
  • Normal mixture models
  • Normal and normal mixture GARCH
  • Principal Component Analysis: Applications to building covariance matrices
  • Modelling Implied Volatilities and their dynamics
  • Local Volatility models
  • Stochastic Volatility Models