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.

This module covers: Linear Algebra, Basics of Functional Analysis (e.g. convergence, continuity, classical fixed-point theorems, Theorem of the Maximum), Differentiation and Optimization (e.g. Lagrangian, KKT Theorem, Envelope Theorem), Probability Theory (e.g. cdf, pdf, expectation, conditional expectation), and Dynamic Programming.

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.

Applied Microeconometrics - 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 - 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 I -  The course will focus on building a strong foundation in macroeconomic theory, particularly in analysing dynamic optimization problems. These techniques will be applied to a wide range of models to deepen students' understanding of topics like business cycles, long run growth, unemployment, and inequality. 

Macroeconomics II - 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.

Topics in Finance and Economics – This module constitutes a rotation set of 10 guest speakers from the Business School Finance Department who are not already teaching on the Doctoral programme. Each speaker will present a piece of their own research to introduce you to their field(s) of speciality. 

Econometrics - 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 I - The course will focus on building a strong foundation in macroeconomic theory, particularly in analysing dynamic optimization problems. These techniques will be applied to a wide range of models to deepen students' understanding of topics like business cycles, long run growth, unemployment, and inequality. 

Macroeconomics II - 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.

Topics in Finance and Economics - This module constitutes a rotation set of 10 guest speakers from the Business School Finance Department who are not already teaching on the Doctoral programme. Each speaker will present a piece of their own research to introduce you to their field(s) of speciality. 

Introduction to the Practice of 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 - 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.

Organisational 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.

Advanced Topics in Asset Pricing and Corporate Finance

Asset Pricing Theory

Consumer Behaviour

Corporate Finance

Corporate Sustainability

Cross Sectional Asset Pricing

Decision Making Under Uncertainty

Developing Theory and Theoretical Contribution 

Digital Markets, Organisations and Platforms

Empirical Asset Pricing

Entrepreneurship

Financial Economics of Climate and Sustainability

Industrial Organisation

Innovation Management

Machine Learning and Text Analysis for Social Science

Machine Learning for Analytics

Micro Development Economics

Optimisation

Organisational Behaviour

Organisational Learning, Behavioural Strategy, and Luck

Organisational Theory

Qualitative Methods I

Qualitative Methods II

Stochastic Processes 

Strategy

Sustainable Behaviour

Topics in Empirical Banking

Topics in Environmental and Resource Economics

Topics in Health Economics

Topics in Household Finance

Applied Microeconometrics  - 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.

Advanced Topics in Finance - This module builds on the first-year Topics in Finance and Economics module and is designed to inspire original research project ideas among second-year Finance students. Through a series of guest-led sessions, you will critically evaluate open questions across multiple areas of finance, explore approaches to addressing research questions and develop an original research project proposal grounded in the existing literature. The specific content will vary depending on the guest speaker.

Advanced Topics in Asset Pricing and Corporate Finance

Consumer Behaviour

Corporate Sustainability

Cross Sectional Asset Pricing

Decision Making Under Uncertainty

Developing Theory and Theoretical Contribution

Digital Markets, Organisations and Platforms

Entrepreneurship

Empirical Asset Pricing

Empirical Industrial Organisation

Financial Economics of Climate and Sustainability

Industrial Organisation

Innovation Management 

Machine Learning and Text Analysis for Social Science

Machine Learning for Analytics

Micro Development Economics

Optimisation

Organisational Behaviour

Organisational Learning, Behavioural Strategy, and Luck

Organisational Theory

Qualitative Methods I

Qualitative Methods II

Quantitative Methods I

Strategy

Stochastic Processes 

Sustainable Behaviour

Topics in Empirical Banking

Topics in Environmental and Resource Economics 

Topics in Health Economics

Topics in Household Finance

Advanced Topics in Asset Pricing and Corporate Finance

Applied Microeconometrics 1

Asset Pricing Theory

Consumer Behaviour

Corporate Finance

Corporate Sustainability

Cross Sectional Asset Pricing

Decision Making Under Uncertainty

Developing Theory and Theoretical Contribution

Digital Markets, Organisations and Platforms

Econometrics 1

Empirical Asset Pricing

Empirical Industrial Organisation

Financial Economics of Climate and Sustainability

Industrial Organisation

Machine Learning and Text Analysis for Social Science

Machine Learning for Analytics

Macroeconomics 1

Micro Development Economics

Microeconomics 1

Microeconomics 2

Optimisation

Organisational Learning, Behavioural Strategy, and Luck

Qualitative Methods 2

Stochastic Processes

Sustainable Behaviour

Topics in Empirical Banking

Topics in Environmental and Resource Economics

Topics in Finance and Economics

Topics in Health Economics

Topics in Household Finance

After your optional introductory modules, you will choose elective modules. In addition to the electives offered within the Business School as part of the MRes programme, you may elect to take a module from one of our partner institutions, subject to availability.

Advanced Topics in Asset Pricing and Corporate Finance

Applied Microeconometrics

Asset Pricing Theory

Behavioural Topics in Marketing

Causal Modelling for Business Analytics

Consumer Behaviour

Corporate Finance

Corporate Sustainability

Decision Making Under Uncertainty

Deep Learning and Generative AI

Developing Theory and Theoretical Contribution

Digital Marketing Analytics

Digital Markets, Organisations and Platforms

Dynamic Programming

Econometrics

Empirical Asset Pricing

Empirical Industrial Organisation

Entrepreneurship

Experimental Design and Analysis

Financial Economics of Climate and Sustainability

Foundations of Quantitative Marketing

Frontiers of Marketing Science

Industrial Organisation

Innovation Management

Machine Learning and Text Analysis for Social Science

Machine Learning for Analytics

Macroeconomics 1

Macroeconomics 2

Micro Development Economics

Microeconomics 1

Microeconomics 2

Optimisation

Optimisation & Decision Models

Organisational Behaviour

Organisational Learning, Behavioural Strategy, and Luck

Organisational Theory

Qualitative Methods 1

Qualitative Methods 2

Quantitative Methods

Stochastic Processes

Strategy

Sustainable Behaviour

Theory in Consumer Psychology

Topics in Empirical Banking

Topics in Finance and Economics

Topics in Health Economics

*These modules are available subject to capacity and timetabling constraints in other faculties and are differently weighted to the MRes Business electives

During the second year, you will work on your MRes project which is formally assessed through project submission and an oral examination, and counts towards the overall MRes mark. You will submit your proposed Research Project title and a brief outline in early October of your second year followed by a progress report in early March, outlining your progress to date with the thesis. During the Summer term, students will submit their MRes dissertation. This will be followed by an oral exam.

It is expected that you will undertake further training where you will delve deeper into your chosen field. Under the guidance of your supervisor, you will develop a training plan to identify which courses may be the most suitable for your training, whether at Imperial or externally. You will have the opportunity to give seminars on your research for constructive feedback and development.

When you begin the PhD you will choose a primary and secondary supervisor, based on your research interests. The supervisor-student relationship is the foundation for a successful doctoral thesis as your supervisor will help you develop your research question, identify research and teaching opportunities and support you through your studies and the academic job application process.

The Early Stage Assessment (ESA) takes place in year one of the PhD and is assessed by a panel of faculty. The ESA outlines the research question, the work you have done to date and the future research activities to be carried out to complete the project. It comprises a written paper and a presentation to which all Doctoral students and research department faculty are invited. The purpose of the ESA is not only to assess your personal progress but it also gives you the opportunity to discuss your work at its early stages and get feedback and ideas from faculty to improve your research.

Armed with feedback from the Early Stage Assessment, you will work intensely on your thesis, focusing on the collection and analysis of empirical data and developing theoretical frameworks. Under the guidance of your supervisors, the thesis gives you the opportunity to conduct a substantial piece of original research. 

Being part of the School’s inspirational research community is a crucial aspect of the doctoral experience – as is gaining familiarity with cutting-edge research from world-leading academics. Each department runs seminars where internal and external academics discuss their latest work. As well as providing insight into yet-to-be-published research, the seminars offer networking opportunities and visiting academics often lead special topic workshops for research students. The Doctoral programme also supports the participation of research students in international conferences where you can present your own research and participate in doctoral consortia.

The Late Stage Review takes place in year two of the PhD and follows the same principle as the Early Stage Assessment, in that its purpose is to assess your progress and provide you with feedback and advice on the direction and scope of your research.

You will also work on developing and polishing your Job Market Paper. You will have the opportunity to participate in workshops alongside support from your supervisors and faculty to help you be internationally competitive.