Students on the MPhil in Finance programme take 6 core courses. These are taught at Cambridge Judge Business School unless specified otherwise:
This course studies corporate investment and corporate financing policy. We analyse how firms make investment decisions and how these investments are being financed. We study how a firm’s cost of capital depends on its business and financial risk. We present the main theories of corporate capital structure and discuss their empirical implications.
The course gives an introduction to the valuation of options using the binomial model, and shows how option pricing can be used for the valuation of corporate liabilities and real options.
Topics covered:
- Capital budgeting with and without debt financing
- The Adjusted Present Value method (APV) and The after-tax Weighted Average Cost of Capital (WACC) method
- Corporate capital structure and corporate restructuring: theory and empirical evidence
- Options and option pricing
- The valuation of corporate liabilities and real options
This is a graduate-level course and some familiarity with basic concepts of finance as provided in the prerequisite reading is expected.
Asset Pricing examines how securities are priced. From a theoretical point of view we examine models of portfolio choice and how investors allocate their wealth across assets. From an empirical point of view, we discuss the empirical success of those models and the statistical techniques used to do so.
Topics covered include:
- Utility-based portfolio theory
- Introduction to cross-sectional asset pricing and CAPM
- Multifactor models and the conditional CAPM
- Generalised theory of moments: theory and applications
- Predicting stock returns, in and out of sample
- Present value relations and return decompositions
- Introduction to term structure models
- The asset pricing of foreign exchange markets
Asset Pricing I requires a strong prior background in microeconomics and statistics/econometrics.
Please work on the assigned summer pre-readings to be announced to the students holding an offer of a place.
Choice of one of the following 2 courses (however, if you wish to apply to continue to the Cambridge Judge PhD after your MPhil year, you’re required to take both Asset Pricing II and Corporate Finance II, taking one as a core course, and one as an elective):
This course follows on Corporate Finance I that is taught in the Michaelmas term. It introduces students who would like an academic career to fundamental empirical research in corporate finance.
Important to note: This course is heavily research-based. It is not suited and not recommended for you if you wish to enter a non-academic career. It has a very heavy reading load of original research papers that you’re required to be familiar with before you enter the class. There is no textbook for the course.
By the end of the course, you should be able to:
- appreciate the theoretical foundations of and empirical evidence on capital raising, internal capital market and control, and corporate governance
- assess critically the theoretical and empirical debates in the corporate finance literature
This course builds upon Asset Pricing I. Asset Pricing II examines how assets are priced in practice and how pricing models are implemented via basic trading strategies.
The course is delivered using lecture slides, Jupyter notebooks, and a free online platform for building and backtesting algorithmic strategies (Quantopian). Some knowledge of Python would be helpful (although not a prerequisite).
Topics covered include:
- Asset pricing: foundations and quantitative implementation
- Valuing risk
- Estimation techniques and model selection
- Hypothesis testing
- Small sample inference
- Modelling, estimating and forecasting volatility
- Introduction to machine learning
Choice of one of the following 2 courses:
Taught by the Faculty of Economics.
This course covers the standard economic models of individual decision-making with and without uncertainty, models of consumer behaviour and producer behaviour under perfect competition and the Arrow-Debreu general equilibrium model.
The course builds the foundations for, and then culminates in, a theory of markets and Adam Smith’s “invisible hand”.
You are introduced to the foundations necessary to conduct research in the 3 areas of marketing, operations & technology management, and finance, with a view to developing your own skills as researchers in these areas and in business in general. This course covers standard models of:
- individual choice under certainty and uncertainty
- production theory
- general equilibrium
- monopoly pricing, price discrimination
- information economics
- behavioural economics
The course gives you some fundamental knowledge of competitive markets, enabling you to leverage your course knowledge to do original research and write papers in your chosen field of research in a business school.
Choice of one of the following 2 courses:
This is the first in the sequence of Econometrics modules designed for Research MPhil students who intend to use econometric methods in their PhD research at Cambridge Judge Business School. It is taught in Michaelmas term.
This introductory module develops your capability in using linear regression and associated statistical techniques to examine causal relationships from primarily cross-sectional, observational data. By the end of the module you will be able to specify, estimate, test, interpret, and critically evaluate single equation regression models, with applications in subject areas of management, finance, and business economics.
The module is followed in Lent Term by Econometrics II, training you in methods and applications of Micro-econometrics. A further module on Time Series Econometrics is offered as an elective in Easter term.
Taught by the Faculty of Economics.
The module provides a graduate-level training in econometric methods. The emphasis of the course is on single equation models; empirical examples are provided both to motivate and to illustrate the methods. Topics include: least squares and the linear regression model; instrumental variables; maximum likelihood estimation and test procedures; binary choice and count data models; time series models; simple dynamic structures.
Visit the Faculty of Economics website to learn more about the Econometrics Methods module.
Choice of one of the following 3 courses:
To carry out empirical research that has the potential to make an original contribution to knowledge in management, finance, business economics and similar fields, it is necessary to exploit the richness and structure of longitudinal as well as cross-sectional, individual-level data. It is necessary to become competent in an array of micro-econometric techniques that help researchers to build into the design of their studies, a variety of complexities (in decision-making, for example) and also compensate for partial observability that is inherent in available data.
This module introduces you to research-level micro-econometric methods. It provides the background required to confidently choose techniques and methods suited to different types of data-sources and models. The focus is on how applied techniques relate to theory, on the insights that can be drawn from their application, and critical interpretation and appraisal of results.
You must have taken the Econometrics I course to take this course. A further module on Time Series Econometrics is offered as an elective in Easter term.
Taught by the Faculty of Economics.
The Time Series course shows how economic and financial time series can be modelled and analysed. Topics covered include ARMA models, state space models, trends and cycles, multivariate models and co-integration, nonlinear models and changing volatility.
You must have taken the Econometrics Methods course in Michaelmas term to take this course.
Visit the Faculty of Economics website to learn more about the Econometrics II: Time Series module.
Taught by the Faculty of Economics.
The Cross-section and Panel Data course covers a broad range of topics in microeconometrics. Topics covered are taken from random utility models in discrete choice, heterogeneity and endogeneity in binary choice models, program evaluation and treatment effects, fixed and random effects estimators for panel data, nonlinear and dynamic panel data models, machine learning, count data models, and an introduction to simulation methods (classical and Bayesian).
You must have taken the Econometrics Methods course in Michaelmas term to take this course.