Programmes Structure

This course focuses on the role of accounting in communicating information for managerial decision-making and external performance evaluation. We will examine how the financial statements, including the income statement, the balance sheet, and the statement of cash flows, provide periodic and generally accepted metrics of firm activity. The course emphasizes evaluating the financial consequences of corporate ventures.

This course introduces the designing and implementing of financial models in the computer, with Excel as the main tool. It covers four classes of models: Corporate Finance models, Portfolio models, Option-Pricing models and Bond models. It also covers simulation, some numerical methods, and VBA programming.

This course aims to provide students with the foundation to understand the key concepts and tools used in Finance that are necessary for managers to make sound financial decisions. Topics covered include discounted cash flow models, risk and return, capital budgeting, valuation of stocks, as well as an overview of payout policy and capital structure.

This course covers the basic concepts in statistics, data analytics, and programming and adopts a cookbook approach to coding. You will use Python to wrangle, visualize, analyze, and model data.

We offer students hands-on experience with some of the industry-leading financial tools. Bloomberg Market Concepts and Refinitiv Workspace certificates will be included in selected foundation courses taught during the first semester.

Equipped with these tools, students will develop skills and strengths that will give them a distinctive advantage in the competitive financial industry.

This course develops a conceptual framework for investment decisions and corporate transactions. The first part of the course centers on valuation & financing strategy, while the second half studies mergers, private equity, and restructurings of distressed and bankrupt firms. We will examine their role in both the private and public capital markets, how they perform from a shareholders’ perspective, and possible agency problems with management.

This course is about the theory and practice of investing in capital markets. Starting from theoretical frameworks, it will explore how to systematically value financial securities and construct portfolios. You will learn about topics such as historical risk and return in capital markets, asset pricing models, the efficiency of capital markets (and when it might fail), stock market anomalies and return prediction, and the basics of equity valuation.

This course is designed to provide students with data analysis tools and conceptual frameworks for analysing international financial markets and capital budgeting. The course covers the following topics: foreign exchange markets; models of exchange-rate determination; international investments; currency and interest rate risk management; international banking; international capital budgeting; political risk and corporate governance in Asia.

This course covers topics on fixed income securities and derivative securities. This course will explain how such securities are valued as well as how they can be used for speculation or for risk reduction. Topics include bond valuation, interest rates and interest rate risk management, mortgage and asset-backed securities, futures, options markets, options pricing, and option strategies.

This course introduces principals, concepts, and modern practices of financial risk management, and also addresses basic financial and statistical techniques that enhance risk management decisions. Topics include Value-at-Risk, historical simulations, stress-testing, backtesting, and credit derivatives. This course will be useful for students seeking professional positions at any part of the financial industry, especially fixed income and derivatives sales, trading, asset management, hedge funds, banking, and risk management.

This module aims to introduce popular machine learning (ML) algorithms and applications in investment from the perspective of a fund manager. It will cover ML as a key element in the investment process, from idea generation to asset allocation, trading execution, and performance evaluation. Numerous use cases with relevant data and code examples will be provided for hands-on exercises.

This course comprises the application of various active investment strategies with a concentration on developing an investment programme which includes alternative asset classes. Topics will include how to research, evaluate and select different alpha generating investments into a practical ready to use investment programme. Different manager styles will be discussed and will cover both quantitative and qualitative methods to assess the strengths and weaknesses of various investment managers and styles. Alternative asset classes studied will include hedge funds, real estate funds, infrastructure investments, private equity, private debt, managed futures and commodities. We will also discuss risk management and control issues in investment programmes. The course will explore the impact of regulatory changes and emerging market variables on the performance of investment programmes.

The objective of this course is to introduce students to the systems and technologies used by financial institutions and markets. It will also explore future trends, opportunities, and threats that these systems and technologies provide.

Finance is a key pillar of modern business organisations. This course examines why and how financial markets and transactions are regulated, with a focus on corporate fundraising and how the regulatory reforms following the 2008-9 Global Financial Crisis are changing the financial landscape. The course also introduces how technological developments (e.g. blockchains, cloud computing, artificial intelligence) are rapidly transforming finance, and highlights regulatory issues that need to be addressed to leverage the potential of Fintech.

In this course, we take the viewpoint of an analyst, investor, or manager interested in corporate reporting and financial analysis. The objective is to understand how to read, interpret, and analyze financial statements, which is a primary and influential exercise when valuing an enterprise or a security. The course also introduces valuation models based on accounting earnings and does not emphasize other non-earnings valuation models such as discounted cash flow model.

This module will be structured around the theme of household financial decision making. Specifically, Household Finance studies (1) how households make financial decisions relating to the functions of consumption, payment, risk management, borrowing and investing; (2) how institutions provide goods and services to satisfy these financial functions of households; and (3) how interventions by firms, governments and other parties affect the provision of financial services. This functional definition shows that household finance is clearly a substantial component of the financial sector. These different functions show that the scope of household finance spans multi disciplines, embracing not just finance and economics but also industrial organization (eg. automatic enrolment in workplace savings plan), law (eg. regulations of retail financial transactions), psychology (eg. decisions affected by framing and cognitive biases), and sociology (eg. decisions shaped by social networks).

This course is an advanced finance course that aims to provide integrated perspectives on the topic of sustainability in the domain field of finance. Specifically, the course will cover the value implications of sustainability practices adopted by firms and those demanded by investors and financial institutions. Regulators, non-profit organizations (NGOs) and other intermediaries are also part of the ecosystem. Various financial valuation and investment tools and methodologies are modified and adapted for use.

This course covers analytical tools and innovations in finance that solve practical problems. The objective is to connect theory with practice by building models, testing them with data, and using them for financial decision- making. The topics include (1) efficient market hypothesis, (2) behavioral finance, (3) event studies, (4) Monte Carlo simulation, (5) artificial intelligence, (6) natural language processing, (7) digital payments, (8) cryptography and cybersecurity, (9) blockchain, and (10) real option. The course adopts a cookbook approach to model, code, and solve problems in finance.

The course provides both a broad and intensive overview of mergers and acquisitions, buyouts and corporate restructuring. By the end of the course, students will understand the motivations, methods, benefits and pitfalls behind M&A economic activity, and as well, appreciate the role of the many parties involved in implementing and effecting these transactions. Although the lectures and cases will often focus on the financial aspects of these transactions (including deal design), students will also consider the various related legal, strategic, organizational and general management issues, as these in fact drive the financial analysis and ultimate fate of the transaction.

This course covers private equity investment types including venture capital, growth capital, and buyouts. It also includes corporate venturing and cross-border structuring. Topics will cover the entire private equity investment cycle from fund raising and structuring; deal screening, due diligence, and valuation; investment negotiations; post-investment value development; and eventual exits.