Doctoral programme: MRes - two-year programme

This course provides students with a basic foundation in mathematics and statistics required to undertake further quantitative research methods courses. This course consists of two parts, statistics and mathematics. Topics covered include: matrix algebra; optimization; differential equations; random variables and probability distributions; moments of a random variable; probability distributions; joint, marginal and conditional distributions; functions and transformation of a random variable; hypothesis testing; univariate regression.

When starting new research, the first step is usually a literature review: scanning what is already known about a given topic and figuring out where the gaps are. However, novice researchers tend to be anything but systematic in their literature review: they have no method for scanning the literature, and they usually have little idea of what is relevant and what is not. The Systematic Review method opens a way to create research syntheses that add real value and novel insight – in a way that is potentially publishable in its own right.

Applied Microeconometrics I - This module will provide an introduction to the practice of applied microeconometrics. Students will learn the standard empirical methods in current use by applied researchers and be exposed to a handful of frontier approaches. The focus will be on implementation beyond simply estimating a parameter of interest: getting the standard errors right, validation and conducting appropriate robustness exercises, and adapting methods to fit new contexts.

Applied Microeconometrics II - This module will be an introduction to some of the most important themes for students wishing to conduct their own research in Empirical Corporate Finance. For other students, this module will help students gain a better understanding of research related to your own field. Topics covered include: regression refresher, causality and randomized experiments, instrumental variables, difference-in-difference, regression discontinuity, standard errors, event studies, discrete response models, matching methods, and non-parametric methods

Econometrics I - The module has the objective to provide the students with econometric tools necessary to conduct their empirical research and discuss fundamentals of econometric theory behind them. Students will learn how to conduct - and how to critique - empirical studies in finance, economics and related fields.

Macroeconomics - This course covers research issues that arise in the intersection of macroeconomics and finance. Topics include portfolio choice, general equilibrium models with heterogeneous agents and dynamic asset pricing models.

Microeconomics I - The module covers the main tools of microeconomic theory and focuses on preferences, consumer theory, choice under uncertainty, producer theory, and game theory. Time permitting, it introduces general equilibrium in competitive markets. The emphasis is on economic intuition as well as techniques. The fundamental concepts of microeconomic theory are discussed.

Microeconomics II - This module covers competitive equilibrium, markets with imperfect, competition and asymmetric information, general equilibrium, Social choice and mechanism design

Research Experience – This module is intended to give students practical experience of research preparation for their dissertation the following year.  They will undertake research tasks under the supervision of a faculty member on a topic chosen by the faculty member.  Students can select those projects that fit their research interests.

Empirical Corporate Finance - This module will provide an introduction to the practice of applied microeconometrics. Students will learn the standard empirical methods in current use by applied researchers and be exposed to a handful of frontier approaches. The focus will be on implementation beyond simply estimating a parameter of interest: getting the standard errors right, validation and conducting appropriate robustness exercises, and adapting methods to fit new contexts.

Econometrics II   - This module will be an introduction to some of the most important themes for students wishing to conduct their own research in Empirical Corporate Finance. For other students, this module will help students gain a better understanding of research related to your own field. Topics covered include: regression refresher, causality and randomized experiments, instrumental variables, difference-in-difference, regression discontinuity, standard errors, event studies, discrete response models, matching methods, and non-parametric methods. 

Econometrics I - The module has the objective to provide the students with econometric tools necessary to conduct their empirical research and discuss fundamentals of econometric theory behind them. Students will learn how to conduct - and how to critique - empirical studies in finance, economics and related fields.

Macroeconomics - This course covers research issues that arise in the intersection of macroeconomics and finance. Topics include portfolio choice, general equilibrium models with heterogeneous agents and dynamic asset pricing models.

Microeconomics I - The module covers the main tools of microeconomic theory and focuses on preferences, consumer theory, choice under uncertainty, producer theory, and game theory. Time permitting, it introduces general equilibrium in competitive markets. The emphasis is on economic intuition as well as techniques. The fundamental concepts of microeconomic theory are discussed.

Corporate Finance - This module is taught in two parts, starting with a historical background, and then considering the theory of investment decisions, capital structure, financial innovation, and corporate governance.

Asset Pricing Theory - The first part of this module deals with representative investors, portfolio choice and dynamic securities markets in discrete time before covering portfolio choice in continuous time and option pricing. The second part starts from the asset pricing implications of a general equilibrium Lucas-tree economy. Then, it discusses the main asset pricing puzzles implied by these economies. Finally, we will explore optimal portfolio choice, multiple trees economies and some of the latest attempts in the asset pricing literature to solve some of these puzzles.

Empirical Asset Pricing - The module is intended for students with a prior knowledge of asset pricing theory, capital markets and econometrics, and will concentrate on discrete-time methods and use a variety of econometric techniques. The module will cover these econometric tools in order to empirically address meaningful economic questions.

Research Experience - This module is intended to give students practical experience of research preparation for their dissertation the following year.  They will undertake research tasks under the supervision of a faculty member on a topic chosen by the faculty member.  Students can select those projects that fit their research interests.

Socialisation to Research - This module will introduce you to the craft of research. You will develop the skills and knowledge you need to effectively produce research questions and hypotheses, ensuring consistency between theory, research design, methods and measures, and developing a clear and compelling argument.

Qualitative Methods I - This module covers research methods required in qualitative research. You will develop skills in all aspects of the research process, including research design, data collection, data analysis, theory building, writing up as well as reviewing papers and responding to referees. The module is essential for those who wish to author qualitative research but will also be useful for quantitative researchers.

Quantitative Methods I - This module provides an overview of the primary quantitative methods employed in management research. It will enable you to develop the ability to interpret the results of your own research as well as to critically assess the findings presented in other studies. The emphasis will be on the practical application of different estimation models using STATA rather than on the econometrics and mathematical specification.

Organisational Behaviour - In this module you will be introduced to a selection of most seminal papers in organisational behaviour with a particular focus on classic and contemporary theories, ongoing controversies, and ground-breaking empirical studies. The emphasis is on providing a foundational overview of the field.

Organisation Theory - This module will expose you to the major theoretical perspectives and issues studied in organisation theory research. You will also be exposed to a set of approaches to understanding how and why organisations form, survive and grow.

Strategy - In this module you will develop the fundamentals of strategy including the theories of competitive advantage, industry analysis, understanding of resource based view/knowledge based view, and corporate strategy.

Innovation Management - This module will offer a thorough theoretical understanding of the key themes of innovation research, combined with practical insights into the challenges of innovation management in organisations. You will address topics ranging from technological change, creativity, the role of networks in innovation, and appropriability/value capture from innovation.

Entrepreneurship - This module introduces students to the major theoretical threads and debates in the field of entrepreneurship. Students will learn to make connections between theory and empirical research, practice critiquing and identifying insight in research, engage with fundamental debates in the field and formulate directions how the field may be further advanced.

Research Experience – This module is intended to give students practical experience of research preparation for their dissertation the following year.  They will undertake research tasks under the supervision of a faculty member on a topic chosen by the faculty member.  Students can select those projects that fit their research interests.

Socialisation to Research - This module will introduce you to the craft of research. You will develop the skills and knowledge you need to effectively produce research questions and hypotheses, ensuring consistency between theory, research design, methods and measures, and developing a clear and compelling argument.

Qualitative Methods I - This module covers research methods required in qualitative research. You will develop skills in all aspects of the research process, including research design, data collection, data analysis, theory building, writing up as well as reviewing papers and responding to referees. The module is essential for those who wish to author qualitative research but will also be useful for quantitative researchers.

Quantitative Methods I - This module provides an overview of the primary quantitative methods employed in management research. It will enable you to develop the ability to interpret the results of your own research as well as to critically assess the findings presented in other studies. The emphasis will be on the practical application of different estimation models using STATA rather than on the econometrics and mathematical specification.

Organisational Behaviour - In this module you will be introduced to a selection of most seminal papers in organisational behaviour with a particular focus on classic and contemporary theories, ongoing controversies, and ground-breaking empirical studies. The emphasis is on providing a foundational overview of the field.

Organisation Theory - This module will expose you to the major theoretical perspectives and issues studied in organisation theory research. You will also be exposed to a set of approaches to understanding how and why organisations form, survive and grow.

Strategy - In this module you will develop the fundamentals of strategy including the theories of competitive advantage, industry analysis, understanding of resource based view/knowledge based view, and corporate strategy.

Innovation Management - This module will offer a thorough theoretical understanding of the key themes of innovation research, combined with practical insights into the challenges of innovation management in organisations. You will address topics ranging from technological change, creativity, the role of networks in innovation, and appropriability/value capture from innovation.

Entrepreneurship - This module introduces students to the major theoretical threads and debates in the field of entrepreneurship. Students will learn to make connections between theory and empirical research, practice critiquing and identifying insight in research, engage with fundamental debates in the field and formulate directions how the field may be further advanced.

Research Experience – This module is intended to give students practical experience of research preparation for their dissertation the following year.  They will undertake research tasks under the supervision of a faculty member on a topic chosen by the faculty member.  Students can select those projects that fit their research interests.

Asset Pricing Theory - The first part of this module deals with representative investors, portfolio choice and dynamic securities markets in discrete time before covering portfolio choice in continuous time and option pricing. The second part starts from the asset pricing implications of a general equilibrium Lucas-tree economy. Then, it discusses the main asset pricing puzzles implied by these economies. Finally, we will explore optimal portfolio choice, multiple trees economies and some of the latest attempts in the asset pricing literature to solve some of these puzzles.

Corporate Finance - This module is taught in two parts, starting with a historical background, and then considering the theory of investment decisions, capital structure, financial innovation, and corporate governance.

Empirical Asset Pricing - The module is intended for students with a prior knowledge of asset pricing theory, capital markets and econometrics, and will concentrate on discrete-time methods and use a use a variety of econometric techniques. The module will cover these econometric tools in order to empirically address meaningful economic questions.

Machine Learning for Analytics, Marketing and Operations - This module covers some of the basic problems and algorithms for machine learning. It will cover supervised and unsupervised learning problems, and causal inference will also be one of the main themes of the module. Most of the applications will be in marketing, operations research and economics.

Topics in Empirical Banking - The main topics that we will discuss in the class relate to the foundations of intermediation. The course will be interactive with active participation being required from students.  The topics covered will include: Financial Fragility, depositor runs and deposit insurance. Contagion and network effects. Changing landscape of financial intermediation. Regulating banks. Interaction between banks and macroeconomics. Special attention will be given to the research methodologies and to the public policy implications, mainly macroprudential and monetary policy.

Topics in Environmental Resource Economics - In this PhD level course we explore key theoretical and empirical results in environmental and resource economics. The course will discuss both: classic papers as well as studies at the recent frontier of the field. While we will explore both theoretical and empirical work, there is a focus on applied empirical work. Students will be asked to replicate one recent empirical paper and explore modifications or extensions.

Topics in Health Economics - This is a PhD level course in Health Economics. It introduces the key topics studied by health economists and methods used in state-of-the-art research in these areas.  The course explores both theoretical and empirical contributions, including both classic papers and articles from research frontier.

Topics in Household Finance – This course will examine how the combination of large administrative datasets of household decisions, empirical techniques including machine learning, and insights from behavioural finance can be used to diagnose inefficient household decisions and evaluate policies to help these decisions to be made more efficiently. Two broad areas that will be focused on in particular are the allocation of savings, especially in equities, and the choice, refinancing, and default decisions of households in mortgages and real estate, which are, respectively, the largest liability and the biggest asset in household portfolios.