Programme Content Part 2

Part 2 - Compulsory Modules

C++ for Financial Engineering

Convenor: TBC    Credits:10

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. 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 and use Excel as an interface for C++ programs. 

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: Dr Jacques Pezier    Credits: 10

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. 

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

Equity and Foreign Exchange Derivatives Modelling

Convenor: Dr Leonardo Nogueira    Credits: 10

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. 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; and differentiate between dynamic replication and static replication of exotic options.

Outline content: 1) 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. 2) 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: Dr Leonardo Nogueira    Credits:10

Conveys the basic concepts and analytical methodology for interest rate modeling and the valuation of interestbased products. 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 the literature on interest rate modelling at an the introductory level; work in a support function, such as product structuring, in a derivatives business and use this as a platform for further research. 

Outline content: The martingale method for interest rate modelling; The classical interest rate models of Vasicek, CIR, HL, HW; The HJM modelling framework; The contemporary Libor market model and the Swap market model; Valuation of interest based derivatives using the above interest rate models; Calibration of market models and HWE. 

Credit Derivatives Modelling

Convenor: Dr Leonardo Nogueira    Credits: 10

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. 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; and describe and analyse some popular trading strategies. 

Outline content: 1) Tools for credit risk modelling: The two main approaches to model credit risk; Analysis of stochastic intensity models; Modelling dependence with Copulas. 2) Credit derivatives in practice: Valuation and trading of Credit Default Swaps; Valuation and trading of Basket Default Swaps and Collateralized Debt Obligations; The standardized correlation markets: trading i-traxx and CDX tranches; Valuation and trading of Credit Default swaptions.

Essentials of Financial Engineering

Convenor: Dr Marcel Prokopczuk    Credits: 10

The module provides an introduction to the basic techniques employed in Financial Engineering. Students will understand how these methods can be applied to design securities with desired payoff characteristics. They will be able to evaluate complex securities by means of reverse engineering and be aware of possible problems when these methods are applied in real world situations.

Outline content: Introduction to Financial Engineering, cash flow engineering, basic financial products, interest and forward rates, no-arbitrage and the law of one price; Pricing and hedging by replication, major interest rate (IR) swap structures, IR swaps, currency forwards and cross currencies FX-swaps, options; Structured products, introduction and evaluation; Dynamic strategies for hedging and principal protection; Credit markets: CDS engineering, credit indices and CDO’s.

    Part 2 - Optional Modules

    Choice of 40 credits from: 

    Bond Market Pricing and Trading Strategies

    Convenor: Dr Andy Bevan    Credits: 20

    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: Flow of Funds and the Economics of Interest Rates; Monitoring Central Banks and the Determination of Short Rates; Pricing and Trading of Short Rate Instruments; Fundamentals of Bond Pricing, Duration and Convexity; Fitting the Yield Curve and Theories of the Term Structure; Trading of Bonds, Bond Forwards and Futures; Pricing and Trading of Interest Rate Swaps; Default Risk and Corporate Bond Spreads; Corporate Bond Spreads Through the Business Cycle; Pricing and Trading of Credit Default Swaps

    Financial Econometrics

    Convenor: Dr Alfonso Dufour    Credits: 20

    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 methods of maximum likelihood estimation and Generalised Method of Moments will be given, and emphasis will be placed on modelling high-frequency data. 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: Stylised characteristics of financial data; Ordinary Least Squares (OLS); Relaxing the OLS assumptions; Simultaneous equations models; Vector autoregressive models; Cointegration; Maximum Likelihood estimation method; Panel data analysis; Simulations methods in econometrics and finance.

    Hedging 

    Convenor: Dr Jacques Pezier    Credits: 20

    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.

    This course examines the rationale for hedging and the methods for doing it efficiently in a variety of circumstances. We review the wide range of market risks (currency, interest rate, equity and commodity) and credit risks for which there is a growing derivatives market. Particular attention is given to the thorny issue of optimal dynamic hedging with transaction costs.

    A basic understanding of stochastic processes and risk analysis methods is indispensable to address these issues as well as a basic knowledge of financial instruments and trading mechanisms. Only students with good quantitative skills and a basic knowledge of derivative products should take this course

    Liquidity Risk 

    Convenor: Dr Alfonso Dufour   Credits: 10

    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: Introduction to the Security trading industry; MiFID and Reg-NMS; Traders and their motivation to trade; Order book trading: The LSE rule book; Transaction cost measurement; Execution Risk and Optimal Trading Strategies.

    Market Risk

    Convenor: Dr Emese Lazar    Credits: 20

    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: The characteristics of markets and market risk; Capital requirements & RAPM; Value at Risk models; Advanced VaR models; Applications to Equities; Applications to Foreign exchange; Applications to Interest rate products; Applications to Derivatives; Applications to Fund management, banking & non-financial firms.

    Portfolio Management

    Convenor: Dr Jacques Pezier    Credits: 20

    The module builds on the techniques for portfolio selection that were introduced at Part One. It addresses both the theory and practice of portfolio management. The theoretical part will examine the issues involved in constructing an investment portfolio, evaluating it’s performance, adjusting its composition through time to ensure that its performance remains optimal, and it will consider the use of derivatives in managing risk. The practical part will provide students with handson experience of constructing and managing an equity portfolio. 

    Outline content: Financial instruments and markets; Diversification; Passive asset allocation; Active portfolio management; Equity analysis; Bond analysis; Derivatives for fund management (forwards/futures/swaps/options); Hedging/ portfolio insurance; Investment strategies/ Performance measurement; Fund management in practice.

    Research Project

    Convenor: Professor Charles Sutcliffe    Credits: 20

    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.

    Volatility Analysis

    Convenor: Professor Carol Alexander    Credits: 20

    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; Hedging.