Students must complete a minimum of 30 credits (15 courses) of coursework to graduate, including 10 credits of core courses (5 courses) and 20 credits of elective courses (10 courses) offered by MSc in Finance Program.
Students must complete a minimum of 30 credits (15 courses) of coursework to graduate, including 10 credits of core courses (5 courses) and 20 credits of elective courses (10 courses) offered by MSc in Finance Program.
Valuation of cash-flow streams (PV of cash flow streams, annuities, and perpetuities), valuation of bonds, valuation of stocks using dividend discount models, capital budgeting decisions (NPV, IRR, payback), capital structure, limits to the use of debt (trade-off models), estimation of the cost of debt and equity, WACC, and terminal value.
It develops the concepts and analytical skills needed to build and analyze investment portfolios and solve real-world problems. This course first introduces the background for investments, e.g., financial markets and investment instruments. Then it explores the risk and return characteristics that lead to diversification benefits, modern portfolio theory, asset pricing theory, and factor investing. The course also investigates how asset prices reflect information and the informational efficiency of financial markets.
This course covers the techniques of empirical investigation in finance. Students are introduced to recent empirical findings based on asset pricing and corporate finance models. The course includes a selection of the following econometrics topics: descriptive statistics, multivariate regression; Fama-MacBeth two-pass methodology; hypothesis testing; omitted variables and misspecification; instrumental variables for non-exogenous variables; introductory time series models; and generalized methods of moments (GMM) estimation. Students apply these techniques to study the predictability of asset returns, tests of market efficiency, and other asset pricing models. This course will highlight the effect on the economic interpretations and statistical tests from: time-varying risk and return, auto-correlated and cross-correlated financial data, issues of endogeneity and data-snooping, event study methodology, tests of linear factor models using portfolios vs individual assets. The data analyses are carried out in a programming language, which facilitates subsequent fintech courses.
Basic characteristics of derivatives instruments such as forwards, futures, options, and swaps. Topics include the pricing of futures and forward contracts, forward-spot basis risk, option strategies, put-call parity, and an introduction to the Black-Scholes model. The development and use of interest rates and currency swaps are also discussed.
Includes techniques in fixed-income portfolio management and the introduction of fixed-income derivatives. Topics include term-structure theories, yield-curve fitting techniques and yield-curve trading strategies, portfolio performance evaluation, floating rate securities, forward-rate agreements, bond and interest rate futures, and interest rate swaps.
Valuation of projects (advanced capital budgeting); estimating cost of capital; risk assessment of projects; decision tree analysis; real option valuation of projects; warrants and convertibles; leasing; dividend policy.
This course is tailored for individuals who are currently working in or are contemplating to work in a family business, either as a family member or a non-family executive. The material covered also gives greater understanding of the dynamics of family business for current or future private and investment bankers, family office professionals, accountants, lawyers and other service professionals working closely with families of wealth in the region.
The course covers the complete investment process including constructing investment objectives, outlining investment policies, choosing asset allocations, monitoring investments, and measuring performance. Practical issues relating to investment style, active management, and passive management are discussed. Advanced techniques in portfolio construction such as the Black-Litterman model and multi-factor models are covered.
This course puts together a collection of industry cases, projects and academic papers on Sustainable Investing, also known as ESG investing, which is an investment approach that integrates three additional factors — environment (E), social (S) and governance (G), into security analysis and portfolio allocation. Students learn that financial analysis with ESG integration provides the basis for more informed investment decisions.
The course is based on the open-source Python language that provides a wide variety of statistical and graphical techniques, and is well-suited for data manipulation, calculation, and graphical display. The remainder of the course covers a general introduction to Python, and then illustrates the use of specific tools such as matrix manipulation, optimization, random numbers and simulation, etc. with financial applications.
This is an introductory course to Financial Technology (FinTech) which includes Insurance Technology (InsurTech) and Regulation Technology (RegTech). The student will have an overall understanding of the underlying information technology being applied in various innovative business models to disrupt the finance and banking landscape globally. The critical business, social/ethical, legal and technology issues and the related risks faced by corporate executives when analyzing, designing, launching and managing FinTech projects to drive business innovations will be discussed in class. Live demos will be conducted to illustrate the proof-of-concept and their applications in real-world scenarios. Key industry developments and the impact on stakeholders will be examined.
This course covers the fundamental concept, design, and implementation of distributed ledgers and blockchains. The characteristics and properties, as well as misconceptions, of blockchains are discussed. In-depth study is conducted of Ethereum, Hyperledger, R3 Corda, Ripple, Quorum, and Stella, and their respective business and finance applications. Live demos and hands-on sessions are conducted to illustrate how DLT/Blockchain and smart contracts can disrupt the financial landscape and support innovative FinTech solutions.
Basic valuation approaches including dividend discount model, free cash flows model, and valuation by multiples; measures of company performance and value added; valuation in special situations such as emerging markets, closely held companies, mergers, and divestitures.
Topics include: (1) An overview of the venture capital and private equity markets in Asia; (2) Deal structuring; (3) Valuation techniques; (4) Due diligence and post-investment management; (5) Understanding the terms in term sheets; (6) Negotiating term sheets; (7) Going public, trade sale and other exit strategies. Real-world examples from throughout Asia will be used to illustrate these topics.
The course is designed to provide students with an overview of how supply equals demand in real-world financial markets. After taking this course, students would be able to appreciate the frictions existing in actual financial markets - bid-ask spreads, trade impact on price, brokerage commissions, quantity limitations, time delays, market manipulation, etc. - and be able to devise trading strategies that minimize these frictions.
Alternative investments are the fastest growing sector of the financial industry, and probably the least understood, including by several market professionals. Although the range of sophistication in people associated with alternative investments varies substantially, it is more and more common to use them in investment strategies, either as direct investments or through funds of funds or structured products. The purpose of this course is to give participants a good understanding and workable knowledge of the techniques that should be part of the tool kit of anyone investing in, analyzing and/or advising private and institutional clients on the inclusion of alternative investments - and more specifically hedge funds - in their portfolios. Furthermore, this course will enable the participants to absorb the analytical arguments in the technical publications - the in-house research notes of financial institutions and in practitioner-oriented journal - that deal with alternative investments and to apply them.
Focuses on the design, analysis, and implementation of financial strategies aimed at repositioning and revitalizing companies. Corporate value creation by restructuring a company or by undergoing a business combination.
The purpose of this course is to give participants a good understanding and workable knowledge of the techniques that should be part of the toolkit of anyone investing in, trading, hedging, analyzing and/or advising private and institutional clients on these three alternative asset classes. Furthermore, this course will enable the participants to absorb the analytical arguments in the technical publications – the in-house research notes of financial institutions and in practitioner oriented journals – that deal with commodities and their markets, and to apply them.
This course is a follow-up of the Venture Capital and Private Equity (VCPE) course, with a particular focus on early-stage venture companies. Students are able to experience and practice all of the content learned, particularly that related to VC endeavors in real-world VC settings. Students can “invest” alongside VC practitioners as well as be guided by investing, accounting, and legal professionals on various topics such as screening prospective investee companies in a live pitch session and drafting and compiling due diligence lists, term sheets, the required closing documentations, and valuation assessments with respective professionals, in addition to presenting early-read memos to industry professionals for deal approvals, among other topics.
Venture capital (VC), a type of private equity (PE) that provides financing to early-stage and emerging firms which are deemed to be too risky for traditional financing, is the financial engine that drives innovation worldwide. However, it is rather mysterious to many people in the field of finance, even to some experienced entrepreneurs and people in general finance, with regard to the internal dynamics of the VC industry. This course will lift that mysterious veil away and reveal its true color. The class will cover how the venture capital industry works, all the parties involved, and the dynamics therein. More specifically, the students will learn how VCs raise money, now they construct a fund portfolio, how they make investment decisions, how VC returns are calculated, and importantly what you need know and do to land a job in this mysterious sector of high finance. I will use real world examples from my personal experiences in some of the largest and most respected and successful VC firms in the world (Khosla Ventures, Softbank, Formation 8, etc) to drive home these points.
This course examines the nature of major types of financial institutions (e.g., banks, mutual funds, hedge funds, insurance companies) as well as the incentives of decision makers in these institutions. Course also covers the role of regulation in financial institutions and financial crises. By the end of this course, students will understand the role of financial institutions in the economy, the effects of informational problems and agency costs on behavior of agents in these institutions and will be able to critically evaluate the advantages and disadvantages of different regulatory reactions to financial crises.
Headline financial data are informative but not fully revealing, concealing hidden gems and traps. This course applies a wise-investor perspective to looking behind the scenes of financial statements. Building from the ground up, students learn how to spot abnormalities, develop pro-forma financials, build solid valuation models, and gain the knowledge and skills to pitch sound investment strategies. These foundations are supplemented by several real-world study cases illustrating accounting issues such as revenue recognition, valuation, and failed unicorns.
Overview of the major issues in green finance pertaining to markets and financial institutions from the standpoint of both investors and policymakers. One of the main references is a report by the Network for Greening the Financial System. Topics: taxonomies and green classification frameworks, green external review, climate transition metrics, disclosure requirements, green rating systems, the role of technology in green data collection and market transparency, green product adaptations, challenges specific to China and Asia, and preparation for ESG certifications.
This course focuses on how real estate financing is undertaken and the key considerations for the borrower and the lender. It focuses on the key steps in a transaction life-cycle and requires participants to prepare basic cash-flow models, approval memos, and negotiate term-sheets. The course also includes additional case studies on hedging and considerations of cross-border real estate financings.
With an introduction to the principles of wealth management and the financial planning process, this course progresses to cover various wealth management topics including consumption planning, investment planning and retirement planning. In particular, this course emphasizes on the provision of investment advisory services. It discusses client expectations and concerns including risk and other cognitive issues before applying the concepts and techniques to construct and manage investment portfolios for individual clients.
This is a course about financial modeling. The goal is to make financial models that provide useful answers to questions concerning the economy. Selected topics that lend themselves to financial modeling are covered, such as (but not limited to) loan amortization schedules, valuation and private equity, equity derivatives, mutual fund performance and style analysis, fixed income derivatives, and optimal portfolio selection.
This course introduces students to the concepts of big data and machine learning with a special focus on how these tools can be applied in a financial context. During the course students will learn Python and how it can be used to build and estimate some of the most commonly used machine learning models such as regression, clustering and classification. Students will also learn the basics of cloud computing and how the cloud can be employed to quickly estimate complex models with very large data sets.
* Concentrations:
IM: Investment Management
FA: Financial Analysis
The above elective courses are subject to change at the discretion of the MSc Programs Office.