The purpose of this module is to give a standard introduction of the field of corporate finance at the postgraduate level. The first part of this module looks at the classical areas of Modigliani-Miller irrelevance, Taxes and capital structure, Trade-off theory and Pecking order theory of capital structure. The second part looks at the more modern areas, which are essentially based on contract theory. Here we look at agency based models and asymmetric information based models of corporate finance. The final part looks at empirical evidence - some time will be allocated to the area of financial constraints - and if time permits, some special topics in corporate finance such as corporate restructuring (mergers, takeovers, workouts, buyouts etc). This is not an introductory Module.

Module Aims

The module aims primarily to introduce students to the roles of agency costs and information asymmetries in corporate financial decision making.

Learning Outcomes

On successful completion of the module, students will be able to:
1. understand, demonstrate knowledge of, and solve problems related to capital structure

2. understand, demonstrate knowledge of, and solve problems related to agency costs and information cost of financing

3. understand, demonstrate knowledge of and solve problems related to financial constraints and various topics covered in the lectures

Skills for Your Professional Life (Transferable Skills)

The module will teach students communication skills and problem solving skills; in particular how to structure and break down a large problems into smaller manageable bits.

This module focuses on the pricing of financial derivatives and their use for hedging financial risks. We start with the basics of two most important derivatives, futures and options. This is followed by an extensive analysis of the most widely used option pricing models, the Black-Scholes model and the binomial model and various numerical techniques for pricing financial derivatives. Futures and options are then utilised in the context of hedging financial risks. By relaxing the rigid assumptions underlying the Black-Scholes formula, alternative option pricing models are presented. Students will be provided with computer exercises that will illustrate the practical implementation of the models introduced in the module.

Module Aims

The aim of this module is to provide students with an understanding of the pricing of financial derivatives and their use in hedging financial risks.

Learning Aims and Outcomes

The aim of this module is to provide students with an understanding of the pricing of financial derivatives and their use for hedging financial risks.

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

1. Understand the main types of derivatives and how they can be used to hedge risks.
2. Devise trading strategies and arbitrage strategies with derivative securities.
3. Understand the main concepts and methodologies underlying financial option pricing.
4. Understand option pricing models with stochastic volatility and jumps.

Skills for your professional life (Transferable Skills)

Critical Thinking: By studying the way derivatives work and the theoretical foundations of some widely employed pricing models students will be able to understand the assumptions used by these models and critically analyse them. This will allow students to appreciate the usefulness/weakness of these models, and understand why sometimes they work/fail in practice. This type of knowledge is particularly useful in areas such as investment banking and asset management.
The module has two parts: theoretical and empirical parts. It will first review the fundamental theories of asset pricing including the expected utility, risk aversion, portfolio choice, asset pricing kernels, and risk-neutral valuation. The second part of the module will discuss some empirical asset pricing studies.

Module Aims

The aim of this module is to provide a formal introduction to asset pricing theories and to critically discuss empirical findings in asset pricing.

Learning Outcomes

On successful completion of the module, students will be able to:
* Explain and solve problems related to expected utility representations, asset allocation, and risk aversion
* Explain and solve problems related to state price representations, pricing kernels, and risk-neutral valuation
* Explain and solve problems related to the CAPM and the APT
* Critically discuss empirical studies in asset pricing

Skills for Your Professional Life (Transferable Skills)

The module will help you with the following transferable skills:
* Ability to interpret empirical statistical and econometric research results
* Ability to critically evaluate asset pricing models
* Literacy and numeracy skills
* Ability to develop your personal plan of setting targets and time management to undertake coursework and exam
The objective of this module is to immerse the student in the process of portfolio management. The module is specifically designed for students with an interest in becoming portfolio managers. The module covers the main concepts such as valuation, efficient diversification, managing risk exposures, portfolio management styles and performance measurement that are at the core of managing investment portfolios and pays special attention to the practicalities of implementation. The module content will therefore contain a balance between theoretical models and their practical applications.

Learning Aims and Outcomes

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

1. Value equity investments using a set of alternative methods
2. Perform basic bond valuation
3. Acquire a critical understanding of the centrality of efficient diversification in portfolio management
4. Understand equity and bond portfolio management strategies and styles
5. Manage portfolio risk
6. Perform basic macroeconomic analysis

Skills for your professional life (Transferable Skills)

The module is geared towards building up or enhancing the following transferable skills:
- Fluency in Excel in general, Excel's Solver function in particular, within the context of portfolio optimisation.
- Ability to use the Bloomberg Professional terminal to retrieve corporate data and perform analytics.
- Being able to write a valuation report on a stock using discounted free cash flows.
- Ability to prepare a professional report on portfolio management research undertaken within a group environment
- Being able to interpret financial data and problems in light of established theories
- Develop rigorous theoretical arguments based on mathematical and analytical reasoning


The aim of this module is to provide students with an understanding of international arbitrage relationships, models of exchange rate determination, and recent issues and debates in the international finance literature. By the end of this module, you should be able to describe the basic international parity relationships, outline some of the basic models of exchange rate determination, and have a good grasp of current issues in international financial markets, and be able to critically evaluate the empirical literature on international finance puzzles.

This module is quantitative in nature. Hence it requires some mathematical derivations and statistical analyses. Although some concepts will be discussed in class, you are expected to be familiar with basic and intermediate concepts in macroeconomics and statistics/econometrics. Familiarity with basic and intermediate notions in investments and portfolio management is also encouraged.


Module Aims

The aim of this module is to provide students with an understanding of the challenges and opportunities that global investments present for investors and portfolio managers.


Learning Outcomes

On successful completion of the module, students will be able to:

* Describe the basic international arbitrage relationships and understand why deviations from these may occur.

* Analyse some of the basic models of exchange rate determination.

* Be able to discuss some of the recent issues in international finance

* Evaluate critically the core empirical literature related to the fundamental debates on international finance puzzles.


Skills for Your Professional Life (Transferable Skills)

* Improve your analytical (research) and problem-solving skills by applying models to explain trends in the data and answer model questions.

* Improve your oral communication skills by communications in the classes

* Develop your critical thinking by critically evaluating existing models and their applicability to the real-life data.
The purpose of this module is to provide an introduction to core topics in financial econometrics that are useful in financial research. It is a relatively technical course that will suit students with some econometrics background who are comfortable with technical material. While practically oriented, it does involve some theoretical econometric material.

Module Aims

The main aims of the module are:

1. to enable students to acquire the skills and techniques necessary to understand and critically evaluate the research areas covered;

2. to enable students to develop and apply a subset of those skills and techniques in coursework.

Learning Outcomes

On successful completion of the module, students will be able to:

1. Understand and apply the following methods: OLS, hypothesis testing techniques, VARs, SUR, ARCH, GARCH and HAR, non-stationarity and cointegration, tests of the EMH, predictability of asset returns, long-horizon regressions, time variation in returns, point and density forecasting and forecast evaluation, and panel estimation.

2. Be familiar with econometric software (primarily EViews) and be able to implement financial applications.

Skills for Your Professional Life (Transferable Skills)

The course will deliver several skills that will be useful in your future professional life. These include:

1. Written Communication (through coursework)

2. Research Skills (a key objective in this module)

3. Critical Thinking

4. Digital and Technical Fluency (using econometric software)

5. Data and Analytics
Behavioural finance has since the 1980s emerged as a new paradigm within finance. On one hand it rejects crucial tenets of mainstream finance such as the Efficient Market Hypothesis (EMH) on the basis that agents are less than fully rational and that arbitrage fails to eliminate mispricing. Instead it identifies market anomalies or regularities that are at odds with the EMH. It uses ideas from cognitive psychology and aspects of imperfect arbitrage to explain these.


Module Aims

* To provide alternative advanced theoretical models in finance to those that are based on the efficient market hypothesis

* To understand how key cognitive biases and limits to arbitrage are introduced in advanced behavioural models of investment behaviour and asset prices

* To examine the application of advanced concepts in behavioural finance to real world issues such as mergers and acquisitions and investment strategies.


Learning Outcomes

On successful completion of the module, students will be able to:

* Understand the implications of psychological biases and of limits to arbitrage for financial markets and asset prices

* Understand the differences between behavioural and traditional explanations of anomalies in financial markets

* Be familiar with the literatures in both empirical and theoretical developments of behavioural finance

* Evaluate the theoretical and empirical evidence for behavioural models and hypotheses.


Skills for Your Professional Life (Transferable Skills)

The module will help you with the following transferable skills:

(a) Understanding of practical investment decisions including those relating to pension choices and investment styles such as value investing.

(b) Ability to interpret empirical statistical and econometric research results, including simulation results, within the context of behavioural models.
The recent financial crisis and credit crunch have demonstrated that risk management was too narrowly defined as it focused mainly on capital risk and not on liquidity risk, and that much of current financial engineering was based on inadequate and overly optimistic assumptions.

The module will start with an appraisal of Value at Risk (VAR) which is a summary measure of financial risk developed in the 1990s. Various VAR models will be described. The use of stress testing to compliment VAR, especially when portfolios include derivative products, will be discussed. The VAR approach has been extended to and beyond derivatives to encompass firm-wide financial risk management.

However the subprime debacle and the credit crunch have shown that existing approaches to risk management need to be reconsidered, and a discussion of the new Regulatory environment, post crisis given.

Module Aims

1. To study advanced models in risk management such as the VAR methodology.
2. To study techniques for the management of credit risk and the pricing of credit derivatives
3. To examine the role and failings of risk management in the recent sub-prime crisis and the subsequent credit crunch.

Module Outcome

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

1. Understand the uses and limitations of the VAR approach in the context of risk management.
2. Understand the uses and limitations of credit derivatives such as credit default swaps.
3. Evaluate the empirical evidence on the uses and limitations of extant risk management strategies in the light of the recent sub-prime and banking crises.
This module focuses on concepts and tools that are useful to asset managers who want to use fixed income securities for investing, market-making or speculating. First, fixed income markets and instruments are overviewed; then, basic concepts of bond portfolio management (e.g. price-yield relationship, discount factors, and price sensitivity measures) are introduced. The module is completed by exploring the quantitative tools used to value bonds and manage bond portfolios. Both theoretical intuitions and practical implications are emphasized.

This course is quantitative in nature and some mathematical derivations may be carried out. Although recalls of the main concepts will be made in class, you are expected to be familiar with basic mathematics, statistics and economics and some basic concepts of investment management.


Module Aims

* To study fixed income markets and instruments

* To study concepts of bond portfolio management

* To examine the quantitative tools used to value and manage bond portfolios


Learning Outcomes

On successful completion of the module, students will be able to:

* Understand the depth and breadth of fixed income markets and instruments

* Construct, value and manage portfolio of fixed income securities

* Compute and interpret the term structure of interest rates

* Set up investment strategies based on Treasury and Corporate fixed
income securities


Skills for Your Professional Life (Transferable Skills)

After completing this module, students have developed and improved the following employability-related skills:

* In-depth knowledge and understanding of the concepts and tools related to fixed income investment and trading activities

* Enhance your analytical and critical thinking by solving real-world problems, such as producing a credit analysis report, identifying mispricing and setting up a trading strategy, and interpreting the shape and movement of the yield curve

* Improve your commercial awareness by investigating the current trends in fixed income markets
The objective of this module is to provide theoretical knowledge and practical understanding of financial markets, trading strategies, risk and money management and trader analytics. The program offers a mix of classroom-based instruction, case study and practical trading exercises where students will trade on real-time simulated global markets through the use of industry strength informational and proprietary trading software on the EBS Trading Floor.

Using Bloomberg, X-Trader and other market trading and informational applications students will be able to experience the excitement of trading and applying theoretical knowledge to realtime prices and market scenarios.

As a window on the real trading world BE364 brings students into line with how practitioners are using financial markets and enables them to develop a firm understanding of the different roles in the financial sector.

Students should have knowledge of the different financial asset classes that are traded and their interrelationships

Students should have knowledge of various economic statistics that government Monetary Policy announce that directly influence markets

Students should have knowledge of different trading strategies and how to apply them

Students should understand trading risk, money management and different order types

Students should have knowledge of technical analysis techniques.
Big data is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. Given contemporary computing power and potential data collection, many firms, particularly those from the financial sector, wish to use big data. The challenges include capture, curation, storage search, sharing, transfer, data analytics and visualisation.

The primary purpose of this module is to provide the student with an understanding of data analytic approaches in finance. The first part of this module covers predictive analytics, risk modelling and corporate finance. The second part will concentrate on the application of data analytics in high frequency finance, fraud and personal finance.

The main aims of the module are:

1. to enable students to understand the applications of big data and data analytics in finance;
2. to enable students to critically evaluate the techniques above and provide a view on the future direction of innovation in the financial sector.

Objectives

This module enables students to be able:

1. to understand the use of high frequency data in finance and its limitations;
2. to undertake predictive estimations and tests of hypotheses using financial data;
3. to understand how big data can be used in areas of finance such as risk analysis and corporate finance.
4. to critically evaluate how big data and data analytics is changing the financial sector.
The aim of this module is to introduce students to the software package Matlab and to provide them with the necessary skills to utilise the software to analyse financial data. Students will be taught the usefulness of matrix algebra and how vectors and matrices can be manipulated in Matlab. Following this introduction, they will be taught how the software can be used in a number of financial applications including portfolio optimisation, testing for unit roots, cointegration and option pricing. A brief introduction to simulation will also be covered.

Module Aims

The main aims of the module are:

1) To develop and transmit knowledge about the Matlab software package and its usefulness in financial applications.
2) To give students knowledge of a number of key concepts in empirical finance and how Matlab can be used to analyse empirical data.
3) To provide students with a firm foundation for developing their own programmes in Matlab to tackle non-standard testing problems.

Learning Outcomes

After completing this module students will be able to:
1. Have an understanding of matrix algebra and how matrices and vectors can be manipulated in Matlab;

2. Import data and manipulate series in Matlab to calculate financial measures;

3. Construct an optimal or minimum variance portfolio and the efficient frontier;

4. Understand the concept of regression and perform regressions in Matlab;

5. Test for non-stationarity in financial data and examine the possibility of cointegration between one or more series;

6. Have a basic understanding of the Black-Scholes option pricing model and how option prices can be calculated using a Matlab toolbox;

7. Use loop commands in Matlab to perform multiple calculations and understand the relevance of these commands in performing Monte Carlo simulation exercises.

Skills for Your Professional Life (Transferable Skills)

By the end of this module students will be very familiar with the Matlab computer software, being able to perform basic command based operations and gaining knowledge of creating their own programmes to perform non-standard analysis. Such programming skills will be transferrable to other programming languages and are highly desirable for employers and very useful if further studies are pursued.

This module covers topics in mathematics that are required in finance modules at Master's level at Essex Business School. It focuses on basic algebra, compounding and discounting, calculus including optimization and dynamics. Little or no previous knowledge will be assumed. However the lectures will proceed at a quick pace, so you are expected to read the lectures notes in advance of the lectures.

This module is compulsory for finance degree students on the MSc Banking, MSc Banking and Finance, MSc Finance, MSc Finance and Investment, MSc Financial Engineering and Risk Management and MSc International Finance programmes and for the MSc Accounting and Finance and MSc Finance and Management programmes.


Module Aims

* To revise or teach basic mathematical skills

* To provide students with a basis of the mathematical techniques required in finance modules at Master's level at EBS


Learning Outcomes

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

* Solve basic algebraic problems

* Calculate present and future values

* Handle nonlinear functions

* Differentiate functions to find marginal values

* Identify the minimum and maximum points of functions

* Understand the basics of optimisation under uncertainty

* Understand differentiation and integration


Skills for Your Professional Life (Transferable Skills)

The mathematical techniques taught during the module will be useful not only during your Master's programme and future academic activities, but also in your professional life.

* Some of the methods taught will be directly applicable in professional financial roles

* More generally the mathematical skills you obtain in the course will help with problem solving tasks in professional life