PhD Programme

Course Structure

Initial Registration 
You will initially be registered for an MPhil. There is a compulsory taught part of the doctoral programme for both pathways, and you will be required to pass compulsory taught modules in the first year. Additionally, following the taught modules, you will be required to provide an upgrade proposal in order to be upgraded to the degree of PhD. You will be sent full details of the taught modules in the August before registration.

Business & Management pathway

You will study three compulsory modules in Term 1, before choosing two methods modules and two elective modules in Term 2. Module details can be found in the drop down section below.

Compulsory modules - Term 1:

  • Introduction to Quantitative Research Methods
  • Introduction to Qualitative Research Methods
  • Developing Management Research.

Methods modules - Term 2:

  • Applied Multiple Regression Analysis
  • Multivariate Statistics
  • Collecting and Analysing Data
  • Theorising and Publishing Qualitative Research.

Elective modules - Term 2:

  • Business in the Digital Age 
  • Recent Advances in Operational Research and Operations Management
  • Organisation and Strategy
  • Behavioural Research in Decision Making and Entrepreneurship. 



Your thesis
You will start working on your research topic from the very outset, but once you have upgraded your registration, this will become your main focus, leading to the completion of your thesis. The criterion for the award is that the thesis makes a significant contribution to knowledge.

 

Finance & Econometrics pathway

You will study six compulsory modules in Term 1, and six compulsory modules in Term 2. Module details can be found in the drop down section below.

Compulsory modules - Term 1:

  • Econometrics 1
  • Econometrics 2
  • Macroeconomics
  • Microeconomics 
  • Asset Pricing 1
  • Corporate Finance 1.

Compulsory modules - Term 2:

  • Qualitative Research Methods
  • Financial Econometrics
  • Asset Pricing 2
  • Corporate Finance 2
  • Advanced Topics in Finance 1
  • Advanced Topics in Finance 2.

Business & Management modules

Introduction to Quantitative Research Methods

Quantitative research methods involve applying statistical techniques to a data-set in order to describe, explain and test theories about the phenomenon being researched. The aim of the module is therefore to provide students with a thorough grounding in the main statistical techniques used in quantitative research. Key aspects of descriptive and inferential statistics will be covered, ranging from tabular and graphical methods used to summarise the characteristics of the data through to regression analysis to explain and test theories about the relationships between variables in the data-set. The module will also cover the key aspects of probability and sampling theory required to make the leap from descriptive to inferential statistics.

Introduction to Qualitative Research Methods

This module will provide you with an introduction to qualitative research. It makes links between practical, theoretical and philosophical ideas, as they are relevant for doing qualitative research. The practical choices we make as researchers always have theoretical and philosophical implications, and the more you are able to appreciate these, the better researcher you will become. The module will address key issues, debates and controversies relevant for the way we design, conduct and evaluate qualitative studies. We will 'try-out' qualitative methods - such as interviews, video analysis and observational work - and this tends to be fun.

Developing Management Research

The module comprises of eight teaching sessions relating to aspects of developing research projects in the field of management (broadly defined) and four sessions of student presentations where students are required to present a summary of their own research. Sessions will be delivered and facilitated by appropriate faculty members and students will be invited to reflect upon various aspects of theory and research on the basis of assigned pre-readings. Sessions will draw on faculty own research to illustrate theories, formulate research questions and do management research.

Applied Multiple Regression Analysis

This module aims to provide doctoral students with an understanding of, and skills in applying a range of multivariate regression analytic tools to address empirical research questions

The course focuses on multiple regression techniques useful to analyse observational and experimental data, including the measurement of policy (or organisation) changes. Application of the methods to answer empirical research questions will be carried out with specialised software (STATA).

Multivariate statistics

Multivariate Statistical techniques are important tools of analysis in all fields of management: Finance, Production, Accounting, Marketing, and Personnel Management. In addition, they play key roles in the fundamental disciplines of the social sciences: Economics, Psychology, Sociology, etc. This module is designed to provide students with a working knowledge of the basic concepts underlying the most important multivariate techniques, with an overview of actual applications in various fields, and with experience in actually using such techniques on real problems. The module will address both the underlying mathematics and problems of applications. This module aims to provide doctoral students with an understanding of, and skills in applying, a range of multivariate statistical tools.

Collecting and Analysing Data

The module will position you as qualitative researchers so that the learning will be directly relevant to your future research. This means that the responsibility to carry out the required activity and to solve the inevitable issues that will likely arise sit firmly with you. This will allow you to decide whether this approach - and possibly this career, is right for you. The module aims to address the practical, analytic and intellectual questions related to the collection of qualitative data. It will do so by providing you with hands-on experience on the use of some of the most common ways to conduct qualitative research.

Theorising and Publishing Qualitative Research

The module addresses the next steps, following 'collecting and analysing' qualitative; namely 'theorising' and then 'publishing' qualitative research.

  1. Students will be tasked with 'theorising' and 'writing up' data collected in the previous module or collected for your PhD.
  2. The module positions students as qualitative researchers, and will be directly relevant for their PhD studies as they critically analyse and reflect upon processes of theorising and publishing qualitative research.
Business in the Digital Age

The objective of the module is to familiarise the student with recent developments in research at the intersection between digital technology and business topics such as digital innovation, technology management, strategy, and data science. The module is intended to generate understanding of the theoretical, empirical, and methodological foundations of business research related to digital technology across different levels of analysis.

Recent Advances in Operational Research and Operations Management

The objective of this module is to make students aware of recent developments in Operational Research and Operations Management, and thoroughly engage them with a seminal paper related to their PhD research by asking them to critically reflect on the paper and present and communicate its content in a way accessible to other PhD students.

Organisation and Strategy

The objective of this module is to familiarise students with the principles of organisation theory, theories of work and main frameworks of strategy.

Behavioural Research in Decision Making and Entrepreneurship

The objective of this new module is to introduce current debates in decision theory about the role of rationality in decisions and whether heuristics help or hinder decision-making. The module will also provide students with a grounding in the field of entrepreneurship, examining topics such cognition, opportunity recognition, biology and economics.

Finance & Econometrics modules

Econometrics 1

Econometrics 1 aims to familiarise students with modern econometric techniques relating to the analysis of financial and macro time series. It covers some basic material: deriving standard least squares and maximum likelihood based estimators, and hypothesis testing. We then introduce the Generalised Methods of Moments (GMM), with applications to financial time series, the Kalman filter and the fixed effect and random effect approaches to panel data models.

Econometrics 2

Econometrics 2 aims to familiarise students with time series econometric techniques relating to the analysis of financial time series. It covers some basic material, ARIMA, and VAR analysis. The second half focuses on some basic ideas in simulation and briefly introduces Bayesian analysis, with a forecasting example using Bayesian VAR and a simple MCMC.

 

Macroeconomics

The module aims to provide students with an understanding of key topics in macroeconomics and the analytical and empirical skills to address these topics.

Microeconomics

The module aims to provide students with an understanding of key topics in microeconomics and the analytical and empirical skills to address these topics.

Asset Pricing 1

The objective of this module is to provide a rigorous, in-depth introduction to the theoretical foundations of Finance in the areas of Asset Pricing and Corporate Finance. The Asset Pricing part of the module focuses primarily on the investor's perspective and analyses individual's consumption and portfolio choice and their implications for equilibrium asset prices. In addition, contingent claims valuation techniques based on the absence of arbitrage are presented.

Qualitative Research Methods

The aim of this module is to enable students to understand the philosophy and paradigms which underlie research in Finance and the nature of different epistemologies. Students need to be properly conversant with both qualitative (and mixed-mode) as well as quantitative research methods and be aware of the spread of research paradigms and theoretical positions which exist in Finance. This module will also, therefore, introduce students to a range of qualitative research methods and techniques and explore the ethical underpinnings of our discipline.

Corporate Finance 1

The objective of this module is to provide a rigorous, in-depth introduction to the theoretical foundations of Finance in the area of Corporate Finance. It focuses on the following topics: theory of the firm and the agency problems, capital structure and asymmetric information, security design, financial intermediary, the interaction between finance and industrial organisation, corporate control and corporate governance.

Financial Econometrics

This course aims to familiarise students with modern econometric techniques relating to the analysis of financial time series. In particular this course covers conditional variances and correlations dynamics, nonlinear filtering and big data and high dimensionality with applications to financial time series.

Asset Pricing 2

This course is the second of the two courses that examines asset pricing. We will focus on the development of stylized facts and tools for the investigation of data. This course is an introduction to empirical research and quantitative analysis in the broadly defined area of asset pricing and macro-finance. The focus of the course is on applications of economic models and econometric methods in finance. Topics will include, returns predictability in the time-series and in the cross-section, foundations of macro finance, and applications of numerical methods for solving models.

Corporate Finance 2

The module is to prepare PhD in Finance students to do research in empirical corporate finance. The topics covered include natural experiments, difference in differences estimates, and regression discontinuity design. The module gives the students an opportunity to present their own work as well as other cutting-edge research to their peers, a skill which is essential for PhD researchers.

Advanced Topics in Finance 1

The aim of the module is to acquaint students with research in international finance and market microstructure. The first half of the module focuses on international finance and risk management, both from a corporate finance and asset pricing perspective. The second half of the module covers main theoretical models in market microstructure, with focus on understanding links between price formation, liquidity, price discovery, and market design. We will also look at recent empirical applications of market microstructure tools to other fields in finance such as asset pricing and corporate finance.

Advanced Topics in Finance 2

The aim of the module Advanced Topics in Finance 2 is to provide students with the latest developments in Advanced Corporate Finance and Empirical Market Microstructure and to ensure a good and advanced understanding of methodologies which are currently used in these areas of Finance. The first part discusses frontier research in the field of market microstructure and covers empirical applications of market microstructure tools to other fields in finance such as asset pricing and corporate finance. The second half of the module provides a methodological framework to understand some recent contributions in the growing research area of dynamic corporate finance.

Module details More Less

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