Accounting & Finance Investment Management
Big Data is important in investment management and AI is widely using in formulating investment decision. This programme offers the academic and practical knowledge in investment management as well as contemporary development in Big Data, AI and FinTech.
*The University has announced that from Monday January 17th 2022, everyone entering the campus are required to be fully vaccinated against Covid-19. HKU SPACE will follow the University policy ( https://covid19.hku.hk/announcements/all/2021/11/11105/ ). This policy is applicable in all HKU SPACE Learning Centres and Offices. The only exceptions will be for those individuals with medical certificates showing they are unable to take the vaccine. Others who are unvaccinated or not fully vaccinated will have to show proof of a negative weekly Covid-19 test (at their own expense) otherwise they will not be granted access.
Visitors (other than staff, students and part-time teachers) entering HKU SPACE Learning Centres and off-campus Offices will be required to use the LeaveHomeSafe app for access.
The programme aims to:
- impart financial and investment management knowledge and skills to students to enhance their financial decision making;
- facilitate students to understand and analyze contemporary issues as well as the latest development in the financial world;
- prepare students to sit for the CFA examinations based on the Candidate Body of Knowledge;
- equip students with the latest technologies on Big Data and Artificial Intelligence for financial industry;
- stimulate students to apply financial intelligence to perform investment management.
The Postgraduate Diploma in Investment Management and Financial Intelligence programme covers a wide range of knowledge in Economic and Statistical Analysis, Corporate Financial Management, Risk and Portfolio Management as well as Fintech, Big Data, Artificial Intelligence and Investing. As it has a rigorous syllabus and teaching members are all market practitioners, students will learn the concepts and theories to make investment decisions as well as the contemporary and practical cases of Financial Intelligence in the real world. Students will also learn how to apply the knowledge and techniques used by market professionals and refresh their investment knowledge using big data.
Graduates of this programme have satisfied the Institute of Financial Technologist of Asia (IFTA) requirements for qualification and will be admitted to the CFT programme for the exemption of Level 1.
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The fintech ecosystem explained by Business Insider
Programme Intended Learning Outcomes:
On completion of the programme, students should be able to:
- apply the relevant theories and concepts in statistical and economic analysis to solve contemporary investment management issues;
- interpret financial statements and analyze key decisions in the area of financing and investment;
- evaluate different methodologies on Big Data Analytics and Artificial Intelligence technologies for financial industry;
- make financial decision based on knowledge of financial intelligence such as Big Data, Fintech and Artificial Intelligence;
- evaluate the risk, pricing structure and strategies involved in the management of traditional and alternative assets;
- analyze investment requirements and construct optimal portfolio and perform portfolio management.
Students who complete all six modules will be awarded the Postgraduate Diploma in Investment Management and Financial Intelligence within the HKU system through HKU SPACE.
Students who complete three modules (module 1 or 2, module 3 or 4 and module 5 or 6) can apply to exit with the Postgraduate Certificate in Investment Management and Financial Intelligence within the HKU system through HKU SPACE.
|Application Code||2065-FN044A||Apply Online Now|
|Apply Online Now|
Module 1: Analytical Tools for Investment Management
This module combines Quantitative Methods and Macroeconomics, two basic subject areas that students must master to pursue more in-depth study of investment topics. Quantitative Methods will cover time value of money, discounted cash flow analysis, probability and statistical concepts, regression analysis and time series. Macroeconomics will cover measurement of GDP and inflation, aggregate demand and supply, Keynesian and Monetary policy and exchange rate determination.
Module 2: Financial Management
This module combines Corporate Finance and Financial Statement Analysis. Corporate Finance topics include capital budgeting and cost of capital, capital structure, dividend policy, warrants and convertibles, mergers and acquisition and corporate governance. Financial Statement Analysis teaches the analysis of financial statements from a user's perspective and includes detailed coverage of major items on the income statement, balance sheet and statement of cash flows. Current topics in accounting are also included.
Module 3: Big Data, Artificial Intelligence and Investing
This module aims to provide students with the knowledge in Big Data and Artificial Intelligence technologies and their applications in investment management. Students are expected to be familiar with different big data analyses and A.I. processes. The module provides an insight on how the current development in these two areas assist and influence investment decision and behaviour.
Module 4: Big Data and FinTech
This module aims to provide students with the knowledge in Big Data and FinTech. The latest development and trend of Big Data and FinTech will be discussed. Students are expected to be familiar with different big data analyses, tools and methodologies. This module provides an insight and challenges on how business world is using Big Data and FinTech to improve their business models.
Module 5: Equity, Debt and Alternative Investments
This module introduces the most commonly used methods of valuing equities including the discounted dividend valuation approach, free cash flow approach, residual income valuation and the use of price multiples. It also covers the analysis of various categories of fixed income instruments including bond investments with various embedded options, mortgage-backed securities, asset-backed securities and interest rate derivatives. Strategies for managing a fixed income portfolio will also be discussed. Alternative investments such as real estate investments, private equity, venture capital and hedge funds will also be taught in this module.
Module 6: Risk and Portfolio Management
This module examines the risk management and derivative market. The full range of derivative instruments such as futures, options and swaps will be discussed. This module also provides an in-depth study of portfolio management and asset pricing models. This module covers behavioural finance, strategies for managing personal versus institutional portfolios, ways of rebalancing the investment portfolio, equity indexing, performance measurement and selection of investment managers.
- Dr. Zenki Kwan, FRM, CAIA, CB, is the investment director of a listed company and a family office in Hong Kong, responsible for investment strategy and portfolio management across equities, fixed income, currency, funds and structured products. He has previously worked in J.P. Morgan, UBS, McKinsey and Samsung Securities. In addition to his doctoral degree, Dr. Kwan also holds Master of Finance and Master of Applied Business Research degrees as well as completed executive education programs at Harvard Law School and Oxford University Saïd Business School, respectively.
- Mr. Ken Liu, co-founder and CTO of Datatact Ltd, a startup focus on AI, Machine Learning and Big Data analytics. He is a hands on expert in his specialized area for over 10 years. Prior to Datatact, Ken worked at Citi, HSBC, Goldman Sachs, Deutsche Bank and Credit Suisse as Algo-Trading developer. Ken earned a Master in Computer Science from USC and a Bachelor in Computer Science from University of Warwick.
- Mr. Isaac Lo is currently an investment manager for a Chinese-based fund management firm in Hong Kong. He has more than 20 years of experience in the financial industry. He is also a CFA charterholder. Deep in his heart, he is a Big Data enthusiast. Currently, he is leading Big Data effort in his firm's Hong Kong office. He is a graduate of the Northwestern University's Master of Analytics program, one of the premier master’s program in Big Data. His past projects include improving DVD rental performance for the largest DVD rental kiosks company in the US, creating new credit card default model based on more than 2,000 factors.
2023 January Intake Class Schedule
Analytical Tools for
|Tue||17 Jan 2023|
Big Data, AI and Investing
|Sat||4 Feb 2023|
Equity, Debt and
|Wed, Sat||26 Apr 2023|
Detailed Timetable: 2023 January Class Schedule
2022 May Intake Class Schedule
|Big Data and Fintech||Sat||25 Jun 2022|
|Risk and Portfolio Management||Thur, Sat||4 Aug 2022|
Detailed Timetable: 2022 May Class Schedule
2022 September Intake Class Schedule
|Financial Management||Wed||21 Sep 2022|
Detailed Timetable: 2022 September Class Schedule
Remark: Tentative timetable is subject to change and module commencement is subject to sufficient enrollment numbers.
Applicants shall hold a bachelor’s degree awarded by a recognized institution.
If the degree or equivalent qualification is from an institution where the language of teaching and assessment is not English, applicants shall provide evidence of English proficiency, such as:
i. an overall band of 6.0 or above with no subtests lower than 5.5 in the IELTS; or
ii. a score of 550 or above in the paper-based TOEFL, or a score of 213 or above in the computer-based TOEFL, or a score of 80 or above in the internet-based TOEFL; or
iii. HKALE Use of English at Grade E or above; or
iv. HKDSE Examination English Language at Level 3 or above; or
v. equivalent qualifications.
Applicants with other qualifications will be considered on individual merit.
Remark: Applicants with relevant academic and/or professional qualifications may approach the Programme Team for application of exemption.
- Course Fee: $8000 per module (* course fees are subject to change without prior notice)
- The CEF Institution Code of HKU SPACE is 100
|Analytical Tools for Investment Management (Module from Postgraduate Diploma in Investment Management and Financial Intelligence)|
|COURSE CODE 33Z10768A||FEES $8,000||ENQUIRY 2867-8476|
|Financial Management (Module from Postgraduate Diploma in Investment Management and Financial Intelligence)|
|COURSE CODE 33Z107698||FEES $8,000||ENQUIRY 2867-8476|
|Big Data and FinTech (Module from Postgraduate Diploma in Investment Management and Financial Intelligence)|
|COURSE CODE 33Z10771A||FEES $8,000||ENQUIRY 2867-8476|
|Equity, Debt and Alternative Investments (Module from Postgraduate Diploma in Investment Management and Financial Intelligence)|
|COURSE CODE 33Z107728||FEES $8,000||ENQUIRY 2867-8476|
|Risk and Portfolio Management (Module from Postgraduate Diploma in Investment Management and Financial Intelligence)|
|COURSE CODE 33Z107736||FEES $8,000||ENQUIRY 2867-8476|
Continuing Education Fund
- The CEF Institution Code of HKU SPACE is 100
|Continuing Education Fund Reimbursable Course (selected modules only)
Some modules of this course have been included in the list of reimbursable courses under the Continuing Education Fund.
Postgraduate Diploma in Investment Management and Financial Intelligence
Online Application Apply Now
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Selected award-bearing programmes also provide online enrolment and payment service for its students.
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Course fees can be paid by cash or EPS at any HKU SPACE enrolment counters.
2. CHEQUE OR BANK DRAFT
Course fees can also be paid by crossed cheque or bank draft made payable to “HKU SPACE”. Please specify theprogramme title(s) for application and applicant’s name. You may either:
- bring the completed form(s), together with the appropriate course or application fees in the form of a cheque, and any required supporting documents to any of the HKU SPACE enrolment centres;
- or mail the above documents to any of the HKU SPACE enrolment centres, specifying “Course Application” on the envelope. HKU SPACE will not be responsible for any loss of payment sent by mail.
Applicants may also pay the course fee by VISA or MasterCard, including the “HKU SPACE MasterCard”, at anyHKU SPACE enrolment centres. Holders of the HKU SPACE MasterCard can enjoy a 10-month interest-freeinstalment period for courses with a tuition fee worth a minimum of HK$2,000; however, the course applicant must also be the cardholder himself/herself. For enquiries, please contact our staff at any enrolment centres.
4. ONLINE PAYMENT (FOR THE COURSE/PROGRAMME HAS ONLINE ENROLMENT ONLY)
The course fees of all open admission courses (course enrolled on first come, first served basis) and selected award-bearing programmes can be settled by using PPS via the Internet. Applicants may also pay the relevant course fees by VISA or MasterCard online. Please refer to the Online Services page on the School website.
For general and short courses, applicants may be required to pay the course fee in cash or by EPS, Visa or MasterCard if the course is to start shortly.
Fees paid are not refundable except under very exceptional circumstances (e.g. course cancellation due to insufficient enrolment), subject to the School’s discretion. In exceptional cases where a refund is approved, fees paid by cash, EPS, cheque or PPS (for online payment only) will normally be reimbursed by a cheque, and fees paid by credit card will normally be reimbursed to the payment cardholder’s credit card account.
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- For additional copies of receipts, please send a stamped, self-addressed envelope with a completed form and a crossed cheque for HK$30 per copy made payable to ‘HKU SPACE’. Such copies will only normally be issued at the end of a course.
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