Optional Modules
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F500 : Empirical Finance
This course is an introduction to some major topics in empirical finance. It aims to endow the student with an understanding of the current issues, methods, and conclusions of empirical research on financial markets. The focus is primarily on equity markets. There will be an emphasis on empirical results and their interpretation. Econometrics required background.
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F520 : Behavioural Finance
The goal of the course is to better understand human attitudes towards uncertainty in general, and financial risk in particular. The method to get there is to go beyond a pure behaviouralist approach, point to the difficulty of deciphering the psychology behind behaviour, to eventually land squarely in the domain of neurobiology. The approach promises more comprehensive insights than from a purely behavioural study (which makes humans look like a bug-plagued organism), and it bypasses difficult issues of awareness and consciousness (what if people don’t know what they think or feel?). Among others, the results are: novel insights into the role of emotions; an appreciation that neurobiology provides foundations for machine learning (and how the newest in computational neuroscience may yet revolutionise machine learning); a deeper understanding as to whether and how “smart drugs” (popular among students and professionals) work.
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F530 : Venture Capital in the Innovation Economy
The course explores the political and economic context from which professional venture capital has evolved and evaluates the distribution and correlates of investment returns to venture capital. Lectures explore the historic role of technological innovation in driving economic development and the complementary contributions of the state and of financial speculation to mobilizing resources for investment in the development and deployment of innovative technologies.
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F540 : Topics in Applied Asset Management
This course will provide a detailed understanding of the main issues in applied portfolio design and related topics in practical asset management and risk management. We first consider how to overcome the problems with the use of mean variance methods, which are industry standard. A range of alternative modern approaches will then be discussed. We will examine the role of the predictability in both expected returns and volatility for position sizing, the use of leverage, managing risk through vol targeting, directional prediction, volatility timing, the use of quantile and expectile regression methods and finally the importance of recognising regimes of predictability. The practical focus will be on equity markets but we will also consider FX and futures markets while studying carry and momentum strategies to some degree.
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F550 : Applications of AI to Finance: alternative data, sentiment and NLP
The course aims to provide a good level of competence around the main applications of AI in finance; the course has a very strong focus on real world applications students may encounter when working in the investment management industry.
The course will train students to identify, manipulate and evaluate data-sets, including alternative data that are an increasingly important part of empirical work in finance. Students will also gain an understanding of NLP and its main applications in finance as well as develop an appreciation for the benefits and challenges of the latest generation of large language models (LLMs). The course will provide ample examples of how such techniques are applied in finance and will give students the possibility to practice using such techniques to address specific empirical problems both in the lectures and the class-work.
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E200 : Principles of Macroeconomics I
The purpose of this course is to introduce you to major questions and theories in neoclassical economics. The goal is to develop the “tools and tastes” necessary to understand the main models of economic growth and business cycle. First, it discusses the Solow-Swan model with exogenous technological progress and savings decision. We analyse the equilibrium of the model and the comparative dynamics around the steady state. Second, we study the microfoundation of consumption and then we study the business cycles phenomena and set up a simple model, which can generate some business cycle facts. Finally we look deeper into investment theory.
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S101 : Public Economics
This course covers the foundations for optimal taxation based largely on the seminal work of Ramsey (1927) and Mirrlees (1971). The goal of the course is to familiarize students with basic empirical methods and theoretical models in applied microeconomics, with a focus on connecting theory to data to inform economic policy. Topics include efficiency costs and incidence of taxation, inequality, optimal income and commodity taxation.
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S140 : Behavioural Economics
This course offers an introduction to the behavioural approach to economics. Among the topic covered are behavioural game theory, intertemporal decision making, neuroeconomics, cognitive biases, decision-making heuristics and addiction. The course includes both theoretical and empirical material, but a recurring theme is the importance of experimental findings both in the laboratory and in the field.
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S150 : Economics of Networks
The course introduces students to the economics of networks. This area of research has emerged in the last two decades and it has introduced a set of tools for economists to incorporate network structure in the analysis of individual behaviour and economic outcomes. Topics covered include the formation of networks, the provision of local public goods, coordination, learning, trading, and financial networks. A central focus of the course is the interplay between theory and experiments.
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S201 : Applied Macroeconomics
The aim of this course is twofold: First, it will introduce students to structural VARs, and related the concept of structural to identification more broadly. In addition, the students will obtain the computational tools to analyse structural VARs themselves using mathematical softwares (primarily Matlab). Second, the course will go through applied macroeconomic theory and analyse the effects on monetary and fiscal policy, and how the policy effectiveness are altered when the economy is in a liquidity trap.
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S301 : Applied Econometrics
This course has two components (i) empirical strategies for obtaining causal estimates, including randomized experiments, difference-in-difference, regression discontinuity, selection correction and instrumental variables and (ii) panel data estimation including fixed and random effects and dynamic panel data models. The focus is on empirical rather than purely theoretical issues.