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Postgraduate Diploma in Applied Financial Engineering
應用金融工程深造文憑

CEF Reimbursable Course (selected modules only)

CEF Reimbursable Course (selected modules only)

Course Code
FN041A
Application Code
1975-FN041A
Postgraduate Diploma in Applied Financial Engineering
QF Level: 6 QR Registration No.: 17/000061/L6 QR Registration Validity Period: 13 Feb 2017 - on-going
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Continuing Education Fund Reimbursable Course
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.

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Credit
60
Study mode
Part-time
Start Date
To be advised
Next intake(s)
04-2022
Duration
1 year to 2 years
Language
English
Course Fee
Module fee: $4500 (* course fees are subject to change without prior notice)
2 installment-:1st- five modules: $22500 and 2nd- five modules: $22500

Deadline on 25 Feb 2022 (Fri)
Enquiries
2867 8476
2861 0278
finpgd@hkuspace.hku.hk
How to Apply
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Accept new applicants for the programme starting with the Statistical and Quantitative Methods in Finance module in March 2022!

Who would benefit from Postgradudate Diploma in Applied Financial Engineering:
1) one who already has basic knowledge of financial products;
2) one who has strong mathematics/statistics background;
3) one who does NOT want the pure theoretical nature of a Master degree;
4) one who wants to learn theories and real-life applications in the same course.

Check out our tutors' bio below!
One of the STRONGEST teaching teams in Applied Financial Engineering.

*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.

Financial engineering requires the application of mathematical methods and information technology to analyze financial problems quantitatively. Financial engineers are responsible for creating structured financial products, building mathematical risk models as well as developing algorithmic trading system which facilitate effective investment decision making, managing financial and investment risk with quantitative modeling and computing technology. This programme is designed for those who plan to pave their career path as a financial engineer or quantitative analyst. The programme is taught by financial and investment practitioners, who are all senior professionals from investment banks or finance industry.

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.

IFTA

Level 1

News about Applied Financial Engineering:

Are fintechs making an impact on treasury functions? by Euromoney

Strix Leviathan wants to build a better enterprise platform for crypto trading by TechCrunch

Wall Street's 'witches brew of hockey sticks and financial engineering' by Business Insider

A financial adviser explains 8 common biases that may be impacting your investment decisions by Business Insider

Here's why ad tech is incorporating financial trading technology by Business Insider

商智投顧 主攻機器人理財24小時不打烊《中時電子報》

提供個人化投資建議  《頭條日報》

創科小宇宙——AI工程師渴市 《頭條日報》

金融科技2.0 人才需具「ABCD」技能 《香港經濟日報》

醫療人工智能初創公司Infermedica發佈服務保險公司的新平臺 《華富財經》

The programme aims to train students to establish financial and trading systems in a logical and scientific way; to deliver the financial and economic knowledge to students and to equip them with financial quantitative analysis capability. It will enable students to manage actual trading operations proficiently and become professional investment traders. After completing the programme, students can enhance their ability to analyze financial and economic issues; to construct hedge fund trading strategies and to calculate the pricing of financial derivatives. Besides, students can set up risk management policies and deal with complex and volatile financial market environments based on the principles of financial engineering and the derivations of applied mathematics.

TUTOR

The programme is taught by practitioners of the finance industry, who are all senior professionals from investment banks or finance firms. They include:

  • Ms. Agnes Tse, CFA, is adept at analyzing the impacts of politics on global financial markets. With Master’s degrees in Business Administration and International Relations, her specializations are in monetary policies and currency markets, as well as geopolitics and energy markets. Currently the Head of Research of Action Forex, one of the top 10 global forex websites, Agnes previously worked as analyst for China Everbright Asset Management focusing on Greater China equity markets. She was later an advisor on the investment strategies of a mutual fund in Daiwa Asset Management. Agnes has been a guest speaker in universities in Hong Kong and Europe on topics of Hong Kong's political environment and the financial markets, and China's soft power.
  • Ms. Jenian Tai,CFA, FRM, is a Data Scientist at Luminant Analytics for Nassau Re – a reinsurance company based in Connecticut. She specializes in both fundamental and quantitative analyses as well as machine learning for practical application in financial institutions. Jenian was a senior fundamental research analyst with over 10 years’ experience in multiple billion-dollar international hedge funds and private equity, where she served as an expert in deep fundamental research, modelling, alpha strategy formulation and stock picking. Her exposure has spanned global financial market multi-strategy trading and investment as well as risk management. In addition to her hedge fund career, Jenian worked as a risk analyst at Societe Generale’s US derivative trading desk and as a data scientist at New York State Homes & Community Renewal. She had analyzed structured and unstructured data in enterprise environment. Jenian holds a Master of Science in Data Analytics from Columbia University.
  • 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, and completed executive education programs at Harvard Law School and Oxford University Saïd Business School, respectively.
  • Dr. Lai Man-Kit, CFA, is currently a professional trainer at Executive Training and Management Consultancy as well as a visiting scholar at HKUST.  Dr. Lai has extensive knowledge in teaching adult continuing education. He was also an Assistant Professor at City University from 1994-2000.
  • Mr. Ferrix Lau, HKACG, ACG, CFA, FRM, has over 10 years’ teaching experience in business, accounting and finance modules at tertiary level. He teaches Financial Analysis, Financial Risk Management, Quantitative Analysis, Financial Accounting, Cost and Management Accounting as well as Corporate Governance. Moreover, he is a co-author of a Statistics book, Quantitative Analysis for Professional Studies and Projects. Furthermore, he has strong interests in the areas of Statistical Analysis, Quantitative Finance and Machine Intelligence. Mr. Lau has earned a Bachelor's Degree in Social Science from The Chinese University of Hong Kong, major in Economics and minor in Computer Science. Besides, he holds a Master's Degree in Business Administration with Distinction from The University of Hong Kong, concentrating on the theme of Accounting Control and Financial Management.
  • 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. Alan Cheung, PRM, CQF, has solid experience in fintech in top tier investment banks, versed in architecting low latency, high frequency algorithmic trading systems. He is currently a Quantitative Strategist on the Equities Desk in Bank of America Merrill Lynch. Alan has a Masters in Mathematical & Computational Finance from the University of Oxford after graduating with First Class Honours in Mathematics with Statistics for Finance from Imperial College London.

On completion of the programme, students should be able to

  1. critically analyze the problems faced by the global financial markets and economic systems, in combination with the financial derivatives and hedging strategies to establish an appropriate investment strategy;
  2. systematically analyze the structure of derivatives and financial products; 
  3. apply financial models efficiently with various principles and theories in quantitative finance and financial engineering; 
  4. develop financial trading programmes in systematic and computerized methods and formulate trading tactics effectively with rational investment behaviours as well as proper risk management policies; 
  5. set up investment trading systems and portfolios applicable to the actual investment environments with the integration of analysis of financial information, investment tools and strategies, financial engineering models and investment disciplines.

 

Application Code 1975-FN041A -

Days / Time
  • Tue, Fri, Sat, -
Venue

All modules are 20 hours face-to-face lectures. Assessments will all be take home assignements or projects, unless indicated below. Student pursuing this programme must successfully complete the following 10 modules.

Module Details

Module 1 - Global Finance and Economics (Examination based)

This module adopts a pragmatic approach and links the textbook knowledge to the contemporary issues in the global economy and the financial markets. The aim is to equip students with the techniques and a sense to critically analyze the problems and events evolving in the global economic developments and the financial markets, so that they can make independent and responsible investment decisions. Since geopolitical developments have become increasingly important in the globalized world, the module would also involve discussions on the intertwinement of international relations and the international economy.

Module 2 - Statistical and Quantitative Methods in Finance

This module focuses on the understanding of nature and application of various quantitative methods and statistical instruments and their linkage to practical finance. By the end of this module, students are expected to apply the knowledge in their assignment, case study and in their own lives. Different tools of quantitative finance such as total return target, risk management and assessment, capital asset pricing model, multi-factor model, modern portfolio theory and portfolio management will be discussed.

Module 3 - Derivatives and Investment Strategy (Examination based)

This module provides students with a framework to understand the fundamental concepts of derivative products (forward and
futures, options, swaps, and basic structured products), to develop the necessary skills used in valuing derivative contracts, to
understand a wide variety of issues related to risk management and investment decisions using derivatives, and to provide a
comprehensive understanding about hedge fund operations.

Module 4 - Financial Time Series Analysis

This module provides students with a framework to understanding the time series modelling. Different regression models such as linear regression, logistic regression, polynomial regression and stepwise regression will discussed. This module examines different time series models such as seasonal decomposition and simple exponential smoothing (SES) as well.

Module 5 - Mathematical Modeling in Finance

This module will introduce different mathematical modeling in finance. Topics about financial derivatives pricing models and financial engineering and theories will be discussed. By completion of the module, students are ready to use the basic principles of financial engineering to deal with the complex market environment.

Module 6 - Fixed Income Securities and Interest Rate Models Analysis

This module provides an in-depth study of fixed income securities and interest rate models analysis. The relevant topics include
bond interest rate risk analysis, fixed income securities pricing, pricing of mortgage-backed bonds and asset-backed bonds and
mortgage pass-through securities, fixed income securities trading strategies, common interest rate models, and application of
interest rate models.

Module 7 - Techniques and Software in Applied Financial Engineering

This module introduces different techniques and software in Applied Financial Engineering. Topics about portfolio management systems and trading strategies will be covered. Students will learn how to use financial trading software such as R to conduct financial analysis. Moreover, the latest development and trend of trading technology innovation will be discussed.

Module 8 - Financial Risk Management and Optimization

This module introduces financial risk management from both qualitative and quantitative approaches. Topics about market risk, interest rate risk and credit risk will be covered. Based on the overview of financial engineering applications, how financial
instruments are used to minimize risks and managerial issues will be discussed. Risk measurement methods/tools and financial
modeling will be applied to tackle risks and uncertainty. Furthermore, concepts of portfolio management and optimization
are being covered.

Module 9 - Logics and Operations of Algorithmic Trading

This module introduces the current trend of AI and big data on trading. Students will understand the industry practice on Algo
trading. Algorithmic trading strategies and executives will be discussed. Student will learn to design and construct systemic trading platform.

Module 10 - Behavioural Finance (Examination Based)

This module examines the principles of behavioural finance and discusses their applications. Topics include the efficient market
hypothesis and its challenges, expected utility theory and its challenges, investor’s heuristics, cognitive biases and emotional
biases, and behavioural investment strategy.

 

Class Schedule (2021 March Intake)

Class Schedule (2021 August Intake)

Class Schedule (2022 March Intake)

Remark: Tentative timetable is subject to change and module commencement is subject to sufficient enrollment numbers.


 

Applicant shall:

A) 

i)          hold a bachelor’s degree awarded by a recognized institution, with 3 years’ relevant work experience; OR

ii)         possess a recognized qualification in financial industry such as CFA, FRM, etc. with 3 years’ relevant work experience;

and

B)  provide evidence of English proficiency (if the degree or equivalent qualification is from an institution where the language of teaching and assessment is not English) 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 professional qualifications and relevant work experience will be considered on individual merit.

Application Fee

HK$150 (Non-refundable)

Course Fee
  • Module fee: $4500 (* course fees are subject to change without prior notice)
    2 installment-:1st- five modules: $22500 and 2nd- five modules: $22500

  • The CEF Institution Code of HKU SPACE is 100
CEF Courses
Global Finance and Economics & Statistical and Quantitative Methods in Finance (Modules from Postgraduate Diploma in Applied Financial Engineering)
COURSE CODE 23Z10212-0 FEES $10,000 ENQUIRY 2867-8476
Techniques and Software in Applied Financial Engineering & Fixed Income Securities and Interest Rate Models Analysis (Modules from Postgraduate Diploma in Applied Financial Engineering)
COURSE CODE 23Z10213-9 FEES $10,000 ENQUIRY 2867-8476
Financial Time Series Analysis & Behavioural Finance (Modules from Postgraduate Diploma in Applied Financial Engineering)
COURSE CODE 23Z10214-7 FEES $10,000 ENQUIRY 2867-8476
Mathematical Modeling in Finance & Logics and Operations of Algorithmic Trading (Modules from Postgraduate Diploma in Applied Financial Engineering)
COURSE CODE 23Z10215-5 FEES $10,000 ENQUIRY 2867-8476
Derivatives and Investment Strategy & Financial Risk Management and Optimization (Modules from Postgraduate Diploma in Applied Financial Engineering)
COURSE CODE 23Z10216-3 FEES $10,000 ENQUIRY 2867-8476
Continuing Education Fund Reimbursable Course 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 Applied Financial Engineering

  • This course is recognised under the Qualifications Framework (QF Level [6])

Application Form Application Form

Enrolment Method
Payment Method
1. Cash, EPS, WeChat Pay Or Alipay

Course fees can be paid by cash, EPS, WeChat Pay or Alipay at any HKU SPACE Enrolment Centres.

2. Cheque Or Bank draft

Course fees can also be paid by crossed cheque or bank draft made payable to “HKU SPACE”. Please specify the programme title(s) for application and the 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.
3. VISA/Mastercard

Applicants may also pay the course fee by VISA or Mastercard, including the “HKU SPACE Mastercard”, at any HKU SPACE enrolment centres. Holders of the HKU SPACE Mastercard can enjoy a 10-month interest-free instalment 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

Online application / enrolment is offered for most open admission courses (course enrolled on first come, first served basis) and selected award-bearing programmes. Application fees and course fees of these programmes/courses can be settled by using "PPS by Internet" (not available via mobile phones), VISA or Mastercard. In addition to the aforesaid online payment channels, continuing students of award-bearing programmes, if their programmes offer online service, may also pay their course fees by Online WeChat Pay, Online Alipay and Faster Payment System (FPS). Please refer to Enrolment Methods - Online Enrolment  for details.

Notes

  • If the programme/course is starting within five working days, application by post is not recommended to avoid any delays. Applicants are advised to enrol in person at HKU SPACE Enrolement Centres and avoid making cheque payment under this circustance.
  • 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, WeChat Pay, Alipay, 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.
  • In addition to the published fees, there may be additional costs associated with individual programmes. Please refer to the relevant course brochures or direct any enquiries to the relevant programme team for details.
  • Fees and places on courses cannot be transferrable from one applicant to another. Once accepted onto a course, the student may not change to another course without approval from HKU SPACE. A processing fee of HK$120 will be levied on each approved transfer.
  • Receipts will be issued for fees paid but HKU SPACE will not be repsonsible for any loss of receipt sent by mail.
  • For payment certification, please submit a completed form, a sufficiently stamped and self-addressed envelope, and a crossed cheque for HK$30 per copy made payable to "HKU SPACE" to any of our enrolment centres. 
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