Depth. Quality. Experience world-class research and faculty insight studying alongside students from across our suite of degree programmes. Of your three electives, at least two will come from our extensive finance portfolio.
Offered in flexible formats on weekdays, evenings and block weeks, electives provide a deep dive into specialist subjects and invaluable cross-generational learning with MBA, MiF and experienced leadership programme students.
Expand your network, build a wealth of knowledge and develop the resources you need to succeed.
Our elective options are updated annually. Faculty and programme material are subject to change.
Accounting
Accounting risk, regulation of standards and corporate governance.
This course will provide a framework for identifying digital companies and assessing their potential values. It will highlight why digital companies are fundamentally different both operationally as well as financially. Students will analyse opportunities for digital companies as well as discuss the significant risks facing such companies. The course will illustrate the key financial reporting considerations of digital investing, and students will learn where to find key financial reporting disclosures for digital companies and how they vary between types of digital companies. Leading executives and analysts will provide their insights into where the digital space is going.
The course will cover the financial reporting implications of consolidations, joint ventures, leveraged buyouts and recapitalizations, spin-offs, carve-outs, and special purpose entities. The complexity of these issues has resulted in companies pushing the reporting envelope in order to achieve desired financial reporting objectives. We will focus on understanding the link between underlying economic events and the information in financial statements, and on how this link affects our assessment of the firm.
The focus will be on the valuation of securities that embed credit risk. This includes, but is not limited to, corporate bonds, credit default swaps, credit indices, asset backed securities, emerging hard currency bonds, and capital structure. By the end of the course the students should have a sound understanding of (i) the trading conventions of these securities, (ii) determinants of the returns of the these securities, (iii) the role of fundamental analysis and structural models in identifying mispriced credit securities, and (iv) how risk and transaction costs affect your ability to build a portfolio of credit instruments. In addition to understanding the drivers of returns, risk and trading costs of credit related securities, the students will via 'hands-on' exercises develop investment skills via experiential learning. This course is aimed at individuals looking for a career in active asset management.
The objective of this course is to expose business students to applications of machine learning tools in business and finance. The course covers some of the most commonly used machine learning algorithms ranging from ridge and lasso and deep neural network for regression and classification problem to clustering and principal component dimensionality reduction. The course will end with a look at more advanced techniques commonly employed for specific tasks in economics and finance. The approach of the course is profoundly practical. For each algorithm we provide the essential theoretical intuition, most of the focus is on the practical implementation of these learning techniques. We will be using Python. No knowledge of Python is required. Students will work on the Python implementation of the various machine learning techniques to real-world data and applications in the second part of each class.
The aim of the course is to give a balanced evaluation of the opportunities and pitfalls for businesses in the main emerging markets of Russia, Central and Eastern Europe, Latin America, South and East Asia, Middle East, and Africa. A detailed framework will be provided within which to evaluate the risks and gains from doing business in a wide variety of emerging markets, particularly the BRIC (Brazil, Russia, India and China) economies.
This course deals with the international financial environment in a globalised economy. It will provide tools for assessing the impact of economic policy shocks and financial disturbances on financial markets, exchange rates, and capital flows. The course is suitable for anyone seeking further understanding of the international macroeconomy, whose importance the recent crisis has revealed. It will be especially relevant for careers in investment analysis, asset management, hedge funds, capital markets, corporate finance, and the finance/treasury function of corporates. GCMC gives the global macroeconomic context for international financing decisions.
Digital networks shape our society and businesses by determining:o the information we access, o the people we interact with, o the products and services we access. But: o How do networks form, and what are their properties? o What is the impact of network homophily on how information diffuses and opinion forms? o How can we ``manipulate" digital connections to make our product or idea go viral? o How should we measure financial contagion, or more generally, systemic risk in an interconnected system? o How can we measure segregation in society and what is the effect of segregation on social mobility and inequality? This elective will equip you with the tools to better navigate in the real world where digital networks are more and more pervasive. Content and delivery: Made-to-measure teaching notes, scenario-based simulations & Class experiments.
Through in-depth cases and discussion of topical issues, discover the multitude of ways that corporate finance theory can be applied to practical problems, with all the complexities that the real world entails. Cover advanced topics in valuation and financing
In the past, the field of finance developed a successful paradigm based on the assumption that investors and managers are rational and that the market is efficient. Anecdotal evidence and research means we now know that this paradigm is insufficient to describe real financial markets. This course adds institutional, social, cognitive, and emotional biases into an analysis of financial market phenomena
Develop an in-depth understanding of credit risk and credit derivatives, with a focus on modelling and valuation. Understand the balance between developing a conceptual framework and market understanding and insight. Learn about topics including: historical default experience and recovery rates, applications of structural models and default-intensity models of credit risk and credit spread options
Become a sophisticated and informed user of derivative instruments such as futures, swaps and options. Develop a sound understanding of the real-world details of the products and the models used to analyse them, as well as their limitations
Understand this innovative and influential area of corporate finance and private equity activity globally. Assess best practices in the field with reference to case studies, practical examples and lessons learnt. The course draws from The course draws from the experience of senior investment professionals and distressed fund advisors.
Multiple new technologies are finding their way into financial services, including artificial intelligence, machine learning, distributed ledger technology, cryptography, digital identity, SaaS platforms, chatbots, robotic process automation, and augmented reality. This has triggered the opportunity to fundamentally morph the business model of practically every financial services vertical - including payments, deposits & retail banking, lending, capital raising, wealth management, insurance, financial infrastructure, and regulation.
Learn about the hedge fund industry, which has grown rapidly over the last decade and is gaining recognition as an alternative to the traditional mutual fund investment. Examine the reasons for this, the modus operandi of hedge funds, their legal, organisational and operational structures, their risk-return characteristics, their model of aligning the interests of investors and managers and the likelihood of their success in the future
The Project and Infrastructure Finance course focuses on the application of techniques and principles to structure, value and finance large-scale infrastructure and industrial projects. The course describes the many ways in which project finance techniques can be used to redistribute and mitigate the risks typically found in these complex projects. Students will work through a series of case studies to apply project finance techniques to real-life projects such as Public-Private Partnership (PPP) infrastructure concessions and commodity development opportunities
Students will learn Python coding and will apply the skills in a variety of financial problems, such as devising and evaluating trading strategies, portfolio construction, and risk assessment, among others. Students are expected to have basic level of coding experience in any other language and a good technical background (namely should be familiar with linear regression and basic linear algebra).
Gain the concepts and tools you need to understand real estate markets and manage real estate assets with a focus on value creation. Most of the course will focus on commercial real estate. Topics covered include valuation and investment analysis, financing, economic, legal, political and taxation issues and recent trends and challenges
There are some $90 trillion dollars of professionally managed assets globally. Where does the money come from? Where does it go? What factors shape how it is managed? Together we take a tour of the world of investment management. We look at the investment challenge through the eyes of the principal actors on the global money management stage - and the current trends shaping the industry in which they work. After 5 days you will be better prepared for a career in investment or one in which investors are your clients. Please note: this course is not a masterclass in how to invest; it is a unique look at how and why investors invest the way they do and the investment industry in which they operate. The block week runs dawn to dusk. It features a parade of practitioners. The level of assignments is not particularly difficult - but the pace and continuous participation required is demanding. Do not take this course unless you can devote the entire week to it
Value Investing course is intended to teach students the principle of value investing as developed by Graham and Dodd and as practiced by prominent buy-side investment professionals. Students would be taught fundamentals of long/short equity investing. This would be done through a combination of formal lectures, speaker sessions and in-class discussion on real world ideas. The emphasis would be on real world Investing decisions with a goal to provide students theory and practice of investing and help students develop business acumen and industry experience
The objectives of this programme are to recognise and navigate with confidence a broad range of conventional wealth management concepts, tools and structures.
This course covers the emerging field of business analytics (BA) or data mining and expands and develops the students' analytical tool kit in analyzing massive data sets. Using case studies and hands-on data sets, students will learn advanced data query techniques, data cleaning and organization, explore various machine learning techniques including supervised and unsupervised classification schemes, text classification, clustering techniques as well as predictive analytics. Students will gain hands-on experience with a variety of software tools, including Tableau and XLMiner.
This course provides an introduction to an industrial sector of worldwide importance, and one in which there are now many business challenges through market restructuring and the development of low carbon technologies.
This is a practical course developed to extend statistical capabilities and critical understanding in the analysis of time series data. The main emphasis will be upon analysing financial and commodity data, mostly high frequency. Although various advanced regression-based methods are reviewed, the course will not be mathematically demanding and students who were comfortable with the pre-programme, or first term, statistics course will be able to move on to this material without difficulty. Students should, however, have an interest in model-based analysis. The course material will be developed intuitively, rather than theoretically, through the exploration of many examples and practical workshops. The course will start with the fundamental basics of time series analysis and lead to a look at recent techniques for algorithmic forecasting and value-at-risk. Two of the later sessions will be led by Dr Peter Bolland, who was formerly head of electronic market making at Morgan Stanley.
In most modern companies, the Product Manager (PM) plays a central role in bringing products successfully to market and also to manage their on-going life-cycle. S/he is the glue that binds the various functions within the company - including Engineering, Sales, Design, Marketing and more. The overall goal for this course, Product Management, is to help students understand all the various skillsets that are needed for the PM role, and to develop a good sense for what it takes to be a successful product manager - typically in a high tech company. By course end students will have learned various product management and product development frameworks. Also, they will have built some hands-on skills in product design based on customer requirements and product prototyping. Plus they will have a deeper understanding of product roadmaps, product-mix planning, overall product lifecycle and product portfolio management, go-to-market strategies, and product-related eco-system development.
In order to be a successful manager, you must regularly reach agreements with others. When interests and values are aligned, such agreements are easy to reach. But as we have all experienced, conflicts arise all too often, making agreements seem difficult if not impossible. One key reason for this difficulty is that although people often face conflict, most know very little about the strategy and psychology behind effectively resolving it and coming to an agreement.
Family firms make up around 70% of businesses worldwide and account for a substantial proportion of GDP. Many of the world's leading corporations originated as family firms, and retain cultural distinctiveness as a result. In some parts of the world, such as South Asia and the Far East, family firms occupy the commanding heights of the economy. Yet they are neglected in the management literature, and often treated as if they were a relic of the past. However, as the current financial crisis is illustrating, with their long time scales, adaptive cultures, and vision-led leadership many are much better fitted to survive the downturn in good shape than many PLCs.
Explore the issues and practices of financing entrepreneurial businesses, including start-ups, emerging growth companies, management buy-outs and buy-ins.
MIRB explores whether and how the adoption of Responsible Business practices by companies, in association with the integration of ESG factors by investors, can be an effective way to address these global challenges. MIRB thus aims to fundamentally transform the way students think about the role of business and finance in society by empowering them to understand, develop and implement a model of broader stakeholder value maximisation in conjunction with positive societal impact. Despite highlighting the importance of creating value for society, the course also stresses the criticality of companies generating profits. Indeed, one of the punchlines is that an approach to business based on responsibility can be more profitable than one focused on shareholder value.
Get an overview of the process and challenges associated with starting an entirely new business, the skills required to prepare a persuasive business plan, approach prospective investors and launch your venture. Gain a clear understanding of how to assess an entrepreneurial opportunity, the resources needed to start a new business and the costs and challenges involved. Give an entrepreneurial bias to your career using this course as a springboard. A number of graduates who have taken the New Venture Development course and gone on to set up their own business or pursued careers in venture capital.
If you have fancied yourself as an entrepreneur or intend to work in the venture capital industry or in professional businesses supporting entrepreneurial firms this is the perfect entry level entrepreneurship course for you. You explore the many dimensions of entrepreneurship and new venture creation and growth, including: conceptualising, developing and managing successful new ventures. The emphasis in this course is on applying and synthesising concepts and techniques from the functional areas of accounting, finance, managerial economics, marketing, operations management, and organisation behaviour in the context of new venture development.
You must successfully complete an additional three electives if you undertake the additional term. They run in a range of formats, and as with electives during the programme, are taken with students from all programmes.
You can take a maximum of three electives during the programme; however, if you choose to undertake the additional fourth term, you will complete an additional three electives.
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