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​Apart from choosing both elective courses from MFFinTech electives list, students may take one of the two elective courses offered by the Faculty of Engineering, and/or one of the three electives offered by the Faculty of Law.  

Up to two electives may be chosen from other taught postgraduate curricula (including Master of Finance) offered by the Business School under the advice and approval of the Programme Directors concerned. Please refer to section at the end of this page for further details.


MFFinTech Elective Courses offered by Business School

The world of global finance, banking and financial services is changing rapidly with the emergence of start-up financial technologies, commonly referred to as FinTech that may disrupt the status quo.  Taught as a series of practical courses and guest lectures by industry entrepreneurs and professionals, the course covers the main pillars of the FinTech start-up ecosystem in Asia, including peer to peer lending platforms, internet finance, online finance, bitcoin, digital currencies, digital payments, big data, cybersecurity, cryptography, etc and their practical impact on global banking and finance.  This course will provide students with the latest empowering and practical knowledge on FinTech enabling them to understand some of the FinTech changes taking place currently in the financial services industry and, most importantly, the trends that will impact the industry in the future.  This is a very practical course with a heavy emphasis on guest lectures on the latest industry trends and best practices by industry experts and entrepreneurs rather than theoretical concepts. 

This course covers the main elements of natural language processing (NLP), text analytics, and text mining, providing students with a foundation in collecting, managing, and analyzing textual data with financial applications in mind such as FinTech. Examples of potential applications include understanding and responding to sentiment in financial newspapers and social media, using social media to improve performance in asset/investment management, due diligence, Fed watching, monitoring of company events, and detecting insider trading.  Although students write their own computer programmes in this course, they are not required to implement most algorithms from scratch. Instead, the focus of this course is on how to use existing state-of-the-art open-source software libraries and how to apply them in a financial context.  This course consists of three parts. In the first part, we work with real-world textual data sets to obtain proficiency in collecting, importing, organizing, and cleaning textual data from sources related to finance and FinTech.  Among others, we cover web scraping, textual corpora, text processing, tokenization, stemming, and stop word removal.  In the second part we delve into a more detailed analysis of NLP, text analytics, and machine learning with a particular focus on finance and FinTech.  For instance, we examine bag-of-words, word weighting schemes, document classification, document clustering, sentiment analysis, and topic models.  The third part consists of summarizing, displaying, and visualizing results obtained from NLP and text analytics for applications in finance and FinTech.

This course provides candidates with the legal background necessary to comply with the regulatory requirements in banking and finance.  It covers the legal aspects of corporate governance, the legal framework of banking and finance, and financial products, including derivatives. This course also provides candidates with background on market access in financial services, as China embarks on liberalisation of its financial markets as a member of the WTO. 

This course covers bank management techniques that include asset and liability management, liquidity and reserve management, credit analysis, loan pricing and off-balance-sheet banking, as well as regulatory issues of commercial banks.  It also discusses issues related to mortgage loan products and how real estate risks may affect the market value of mortgages. 

Hedge funds are one of the fastest growing sectors of asset management.  This course studies the styles of hedge funds and management strategies from an investment decision-making perspective.  Topics covered in this module include environment and micro-structure of capital market, investment strategies, quantitative tools, derivative products, investment performance evaluation and discussions of some hedge funds failures.  Special attention is given to various practical investment strategies and their risks, including equity selection techniques, market-neutral portfolio constructions, arbitrage strategies, emerging market investment, shortselling problems, etc. 

Behavioral finance uses insights from psychology to understand how biases, heuristics, framing and emotions influences the decisions of individual and professional investors, markets and managers.  It describes how and why these suboptimal decisions might deviate from those predicted by traditional financial or economic theory.  The course also shows why arbitrageurs such as hedge funds cannot correct but instead choose to ride on the misbehavior and mispricing. The course will explore the implications of investor psychology and limitation to arbitrage in the individual trading behaviors, aggregate stock market and the cross-section of average returns, and corporate finance.  How insights of behavioral finance complement the traditional finance paradigm will be examined, so that candidates will gain an understanding of how individuals and institutions actually make financial decisions (descriptive) and guidance on how to improve financial decision making (prescriptive) in themselves and others. 

A real option is a right—not an obligation—to take an action on an underlying real asset.  The action may involve, for example, abandoning, expanding, or contracting a project or even deferring the decision until a later time.  Real options analysis (ROA) is a tool that helps to quantify the value of a real option.  This course provides a synthesis of modern asset pricing and corporate finance via the framework of ROA.  The course compares and contrasts ROA with the traditional tools of valuation.  The benefits and limitations of ROA in terms of practical applications are also discussed.

This course provides students with the foundations and practical knowledge enabling them to launch and manage their own entrepreneurial venture including a hedge fund, private equity, venture capital or asset management firm. Taught as a combination of practical classes and guest lectures by industry professionals, the course covers the entire fund and business launch spectrum including fund structuring, investor capital raising, investor due diligence, regulatory, tax, governance, fund terms, private placement regulations, market trading rules, service provider selection, counterparty selection, employment matters, real estate, technology, operations, etc. The course also covers the investor landscape and investor lifecycle from early stage investors to institutional capital raising from global family offices, fund of funds, endowments, private banks and pension funds. We also cover the ongoing management and deal making of such funds from angel and venture capital early investments to private equity deals and exits. The course also discusses the global trends and industry institutional best practices, the customs and usage in the industry as well as some of the future trends, including FinTech and cybersecurity, and their impact on the industry. This is a very practical course with a heavy emphasis on the latest industry trends and best practices rather than theoretical concepts.

This course gives candidates an overview of Asian financial markets, their latest development and future trends so that candidates can better prepare themselves for building their career in finance in the region.  It consists of company visits, executive talks/seminars, training, networking and/or cultural activities.

This is a special course that deals with various current topics in finance.  Topics covered may vary from year to year, depending on the research interests of the instructor. 

This course aims to provide students with a practical approach to equity valuation and investing.  They will learn how to apply the key concepts, techniques and tools used by market practitioners in making real world investment decisions.  Topics include: identifying sources of value, core valuation techniques - discounted cash flow, multiples analysis of comparable companies, real options valuation, and other valuation methods commonly used by practitioners; an overview of the asset management industry; the fundamental assumptions and approaches to value investing; risk management in the investment process. 

This course aims to cover basic information and knowledge about project choice and financing, idea implementation, decision-making, and innovations in start-up businesses. The majority of such information and knowledge is delivered based on the case method (with supplementary lecture notes when appropriate).  It is noteworthy that we will take two roles interchangeably throughout this course: the entrepreneurs who seek funding and the venture capitalists who seek good projects.  Understanding the role of both important players in the entrepreneurial finance process helps us have an objective evaluation and unbiased assessment of potential ideas and projects.


MFFinTech Elective Courses offered by Faculty of Engineering

Machine learning is a fast growing field in computer science and deep learning is the cutting edge technology that enables machines to learn from large-scale and complex datasets. Ethical implications of deep learning and its applications will be covered first and the course will focus on how deep neural networks are applied to solve a wide range of problems in areas such as natural language processing, image processing, financial predictions, game playing and robotics. Topics covered include linear and logistic regression, artificial neural networks and how to train them, recurrent neural networks, convolutional neural networks, deep reinforcement learning and unsupervised feature learning. Popular deep learning software, such as TensorFlow, will also be introduced.

This course aims at introducing various analytics techniques to fight against financial fraud.  These analytics techniques include, descriptive analytics, predictive analytics, and social network learning.  Various data set will also be introduced, including labeled or unlabeled data sets, and social network data set.  Students learn the fraud patterns through applying the analytics techniques in financial frauds, such as, insurance fraud, credit card fraud, etc.

Key topics include: Handling of raw data sets for fraud detection; Applications of descriptive analytics, predictive analytics and social network analytics to construct fraud detection models; Financial Fraud Analytics challenges and issues when applied in business context.

Required to have basic knowledge about statistics concepts.


MFFinTech Elective Courses offered by Faculty of Law 

This course will explore privacy and data protection in an increasingly interconnected data economy. Reference will be made to the balance between privacy on the one hand and other rights as well as public and social interests on the other. The challenges posed by technological innovations and applications such as the internet, social media, mobile applications, cloud computing and Big Data will be highlighted. Specific topics to be addressed will include: (a) the concept of ‘privacy’ and the genesis and development of its political, philosophical and economic underpinnings; (b) existing common law and statutory protection: the equitable remedy for breach of confidence, defamation, copyright, the intentional infliction of emotional distress, the public interest, remedies; (c) the protection of ‘personal information’: Personal Data (Privacy) Ordinance, data protection principles, data access and correction rights, regulation of direct marketing, transborder data flow, Interception of Communications and Surveillance Ordinance, Electronic Health Record Sharing System Ordinance; (d) Privacy Commissioner for Personal Data: powers, functions, enforcement, exemptions, from data protection principles. The course will focus on the Hong Kong situation but reference will be made to relevant international human rights instruments and the global and regional trends and developments.

The overall aim of this is to help students understand how regulatory compliance and enforcement processes are being transformed by increased global competition and accelerating technological innovation in financial markets. Topics covered will include how the role of information technology in the delivery of modern financial services has evolved over time as well as how recent developments in information technology are transforming compliance processes inside firms and enforcement efforts of regulators. The impact of digital transformation of compliance in financial services on law firms, legal departments in companies, government attorneys, compliance managers, internal and external auditors, and system administrators will be considered A case study examining the impact of global competition and technology innovation on data protection/information privacy compliance efforts under Hong Kong, European Union and US law will be used to integrate theoretical and practical perspectives on the delivery of e-finance services.

Money laundering and terrorist financing are examples of financial crimes that can, among other things, undermine the integrity and stability of financial institutions and the economic system at large, deter foreign investment, and distort international capital flows. Money launderers and terrorist financiers are now deploying increasingly sophisticated methods and schemes to disguise and achieve their illicit purposes, and are particularly attracted to exploit those jurisdictions with weak or ineffective anti-money laundering (“AML”) and counter-terrorist financing (“CTF”) controls. Thus, developing a solid and comprehensive understanding of the concepts of money laundering and terrorist financing as well as keeping abreast of the respective regulatory frameworks are crucial to appreciating and managing such risks and challenges in the context of a financial services business. This course is designed to not only provide students with an overview of the legal and regulatory aspects of AML and CTF, but also to equip students with practical skills and best practices to detecting and managing these types of financial crime risks in a financial institution setting. To achieve these objectives, this course is made up of three main modules. The first module explores the concepts and typologies of money laundering and terrorist financing. These concepts will be contextualised against the international efforts that been deployed to combat these illicit activities. The Hong Kong AML and CTF framework, and the roles of the respective enforcement agencies, will also be discussed. The second module examines the key components of a sound AML and CTF compliance programme in a financial institution. The way how this programme should be embedded within the broader internal control, risk management, and governance framework will also be considered. The third module focuses on some thematic issues of an AML and CTF compliance programme, including customer due diligence, escalation and exit strategies, suspicious activities, suspicious transaction reporting, and dealing with customers and regulators. In this course, students will be learning through different activities. Besides the lecture component, students will be provided with an opportunity to deliver presentations and participate in in-class discussion on different case studies and court cases. Where appropriate, practitioners in the relevant field will be invited to share with students their experience and insights on how different AML and CTF issues come into play and handled in practice.

*The above course list is subject to change in future intakes. 


MAcct / MEcon / MFin / MGM / MSc(BA) / MSc(Mktg) Electives

You can take up to two electives from the Master of AccountingMaster of  Economics, Master of FinanceMaster of Global ManagementMaster of Science in Business Analytics or Master of Science in Marketing programme at HKU. Enrollment in electives from other programmes is subject to seat availability and approval by the Programme Directors concerned based on your profile, capabilities and performance in the MFFinTech programme.

Since enrollment in other taught postgraduate electives is not guaranteed, you should always choose two MFFinTech electives during the course enrollment in our programme. Course enrollment results of other programmes may only be confirmed after that course has started. If your enrollment is successful, you can drop the MFFinTech elective(s) and enroll in the other taught postgraduate elective(s).

It is your responsibility to make sure you obtain at least 75 credits to fulfill the graduation requirements and there is no overlapping of classes and exams in courses from different programmes.

*The list of available electives from other programmes may have prerequisite requirement(s) and is subject to change for future intakes.