Accounting & Finance FinTech and Financial Intelligence
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Programme Intended Learning Outcomes
On completion of the programme, students should be able to
1. apply quantitative methods to analyse financial data and build financial models;
2. explain the applications of artificial intelligence in financial data processing, text and financial analytics and algo-trading;
3. discuss and evaluate a wide range of ESG factors and financial risks, and integrate them in the investment strategies;
4. critically interpret financial performance, optimise investment portfolios and formulate quantitative investment strategies; and
5. use computational tools to perform financial analytics, implement algo-trading as well as solve finance and investment problems.
Module 1: AI and Financial Computing (42 hours)
Module 2: Financial Analysis and ESG Investing (33 hours)
Module 3: Financial Risk Analysis and Portfolio Optimisation (33 hours)
Module 4: Machine Learning for Financial Analytics (33 hours)
Module 5: Web Scraping and Text Analytics in Quantitative Finance (33 hours)
Module 6: Algo Trading and Quantitative Investment Strategies (42 hours)
|Application Code||2155-FN092A||Apply Online Now|
|Apply Online Now|
Modules & Class Details
Module 1: AI and Financial Computing
- Principles of finance
- Overview of AI in finance
- Introduction to Python programming
- Mathematical and computational methods for finance
Module 2: Financial Analysis and ESG Investing
- Introduction to financial analysis
- Evaluation of financial performance
- Introduction to ESG and the ESG market
- ESG factors, engagement and stewardship
- ESG analysis, valuation and integration
- ESG integrated portfolio construction and management
- Investment mandates, portfolio analytics and client reporting
- Integrated financial analysis and ESG investing
Module 3: Financial Risk Analysis and Portfolio Optimisation
- Overview of financial risk analysis
- Interest rate risks
- Market risks
- Credit risks
- Portfolio optimisation
Module 4: Machine Learning for Financial Analytics
- Introduction to machine learning and financial analytics
- Machine learning and algorithms
- Financial modelling and financial analytics
Module 5: Web Scraping and Text Analytics in Quantitative Finance
- Web scraping and data wrangling
- Text analytics and text mining
- Applications of web scraping and text analytics for quantitative finance
Module 6: Algo Trading and Quantitative Investment Strategies
- Introduction to algorithmic trading
- Technical analysis and algorithmic trading
- Performance evaluation and strategy optimization
- AI, algo trading and quantitative investment strategies
1. Mr. Hong Lin
Mr. Lin graduated from the University of California, Davis with a Bachelor of Science degree in Managerial Economics Development under Trade and Development of Agricultural Commodities, and the Hong Kong University of Science and Technology with a Master of Science degree in Business Analytics. Mr. Lin is passionately sharing his Fintech knowledge and contributing to the digital progress of Hong Kong’s banking and finance industry.
2. Mr. Stephen Chan
Mr. Stephen Chan has more than 20 years of experience as a professional accountant and business consultant. He holds his BSc degree in Science in Economics awarded by the University of London and the Professional Diploma in Accountancy awarded by the Hong Kong Polytechnic University. Also, he is a graduate of the Executive MBA from the City University of Hong Kong. He started his first auditing job at PricewaterhouseCoopers. Moreover, he has served the Hong Kong SAR Government, the Jockey Club, banks, airlines and various listed companies. In recent years, he has offered advisory services for various companies on compliance, corporate finance and taxation. He has also worked as a lecturer at various universities and tertiary institutions.
3. Mr. Ken Liu
Mr. 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. Mr. Liu earned a Master in Computer Science from USC and a Bachelor in Computer Science from University of Warwick.
4. Dr. Simon Yiu
Dr.Yiu has over 20 years' IT experience of quantitative algorithmic trading design (data-feed, strategy, back-test, porfolio monitoring and execution), infrastructure management (low latency trading and network, OS and application), implementation, project management to formulate and development business strategic and operation management.
5. Mr. Ferrix Lau
Mr Lau 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.
Students who complete all six modules with over 70% attendance and pass all individual assignments and group presentations will be awarded the Postgraduate Diploma in Financial Analytics and Algo Trading within the HKU system through HKU SPACE.
Fee & Entry Requirements
Applicants shall hold a bachelor’s degree in quantitative or computational areas (e.g., economics, finance, mathematics, statistics, science, computer science, IT or engineering) awarded by a recognized institution or equivalent.
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:
- an overall band of 6.0 or above with no subtests lower than 5.5 in the IELTS; or
- 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
- HKALE Use of English at Grade E or above; or
- HKDSE Examination English Language at Level 3 or above; or
- equivalent qualifications.
Applicants without the above qualifications but have substantial work experience will be considered on individual merit.
Applicants who do not have a background in quantitative or computational areas are required to take the Certificate for Module (Quantitative Methods in Finance) as the bridging course. They must complete and pass the module before the commencement of the programme.
HK$150 (Non-refundable)Course Fee
- Module fee: $11,000 (course fees are subject to change without prior notice)
2 installment-:1st- three modules: $33,000 and 2nd- three modules: $33,000
- The CEF Institution Code of HKU SPACE is 100
|AI and Financial Computing (Module from Postgraduate Diploma in Financial Analytics and Algo Trading)|
|COURSE CODE 33Z144216||FEES $11,000||ENQUIRY 2520-4612|
|Financial Analysis and ESG Investing(Module from Postgraduate Diploma in Financial Analytics and Algo Trading)|
|COURSE CODE 33Z144224||FEES $11,000||ENQUIRY 2520-4612|
|Machine Learning for Financial Analytics (Module from Postgraduate Diploma in Financial Analytics and Algo Trading)|
|COURSE CODE 33Z144232||FEES $11,000||ENQUIRY 2520-4612|
|Algo Trading and Quantitative Investment Strategies (Module from Postgraduate Diploma in Financial Analytics and Algo Trading)|
|COURSE CODE 33Z144240||FEES $11,000||ENQUIRY 2520-4612|
|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 Financial Analytics and Algo Trading
Online Application Apply Now
Application Form Application FormEnrolment Method
HKU SPACE provides 24-hour online application and payment service for students to apply to selected award-bearing programmes and to enrol in most open admission courses (courses enrolled on a first come, first served basis) via the Internet. Applicants may settle the payment by using either "PPS by Internet" (not available via mobile phones), VISA or Mastercard online. Online WeChat Pay, Online AliPay and Faster Payment System (FPS) are also available for continuing enrolment in the same programme, if online service is offered.
For first time enrolment
Complete the online application form
Applicant may click the icon on the top right-hand corner of the programme/course webpage to make online application, and then follow the instructions to fill in the online application form.
Some programmes/courses may admit by selection, and may require applicants to provide electronic copy of any required documents (e.g. proof of qualification) as indicated on the programme/course webpage. Only file format in doc, docx, jpg and pdf are supported.
Make Online Payment
Pay the application or programme/course fees by either using:
"PPS by Internet" - You will need a PPS account and a PPS Internet password. For information on how to open a PPS account and how to set up a PPS Internet password, please visit http://www.ppshk.com.
*Credit Card Online Payment - Course fees can be paid by VISA or Mastercard including the “HKU SPACE Mastercard”.
* HKU SPACE Mastercard cardholders who wish to enjoy 10-month interest free instalment scheme must pay their tuition fees in person at any of our HKU SPACE Enrolment Centres.
To know more about first-time online application/enrolment and payment, please refer to the user guide of Online Application / Enrolment and Payment:
For continuing enrolment in the same programme
Selected programmes offer online continuing enrolment service. Programme staff will inform students if they offer this service and offer further enrolment details.
Online Payment can be made via "PPS by Internet" (not available via mobile phones), VISA or Mastercard, Online WeChat Pay, Online AliPay and Faster Payment System (FPS)
In Person / Mail
For first time enrolment
For first come, first served short courses, complete the Application for Enrolment Form SF26 and bring or post the completed form(s), together with the appropriate application/course fee(s) and any required supporting documents to any of the HKU SPACE enrolment centres.
[Download Enrolment Form SF26]
Award-bearing and professional courses may require other information. Forms are usually available at the enrolment centres or on request from programme staff. Bring or post the completed form(s), together with the appropriate application/course fee(s) and any required supporting documents to any of the HKU SPACE enrolment centres.
For continuing enrolment in the same programme
The standard ‘Enrolment/Payment Slip’ is designed for students of award-bearing programmes or remaining programmes in a suite of programmes requiring continuing enrolment and it applies to most programmes.
Students should complete the “Enrolment/Payment Slip” which will be made available by relevant programme staff and return the slip to any HKU SPACE enrolment centre or post it to the relevant programme staff with appropriate fee payment.
Please refer to available Payment Methods for fee payment information. If you are in doubt about the procedures, please check the individual course details, or contact our programme staff or enrolment centres.
Please note the followings for programme/course enrollment:
- Applicants should not leave the online application idle for more than 10 minutes. Otherwise, applicants must restart the application process.
- Only Early Bird Discount is supported for Online Applicants (Application). To enjoy other types of discount, please visit one of our enrolment centres.
- During the online application process, asynchronous application and payment submission may occur. Successful payment may not guarantee successful application. In case of unsuccessful submission, our programme staff will contact you shortly.
- Applicants are reminded that they should only apply for the same programme/course once through counter or online application.
- For online enrolment, a payment confirmation page would be displayed after payment has been made successfully. In addition, a confirmation email would also be sent to your email account. You are advised to keep your payment confirmation for future enquiries.
- Fees paid are not refundable except as statutorily provided or under very exceptional circumstances (e.g. course cancellation due to insufficient enrolment).
- If admission is by selection, the official receipt is not a guarantee that your application has been accepted. We will inform you of the result as soon as possible after the closing date for application. Unsuccessful applicants will be given a refund of programme/course fee if already paid.
The School provides a platform for online services for a selected range of products it offers. While every effort is made to ensure timeliness and accuracy of information contained in this website, such information and materials are provided "as is" without express or implied warranty of any kind. In particular, no warranty or assurance regarding non-infringement, security, accuracy, fitness for a purpose or freedom from computer viruses is given in connection with such information and materials.
The School (and its respective employees and subsidiaries) is not liable for any loss or damage in connection with any online payments made by you by reason of (i) any failure, delay, interruption, suspension or restriction of the transmission of any information or message from any payment gateways of the relevant banks and/or third party merchants for processing credit/debit/smart card or other payment facilitation mechanism; (ii) any negligence, mistake, error in or omission from any information or message transmitted from the said payment gateways; (iii) any breakdown, malfunction or failure of those gateways in effecting online payment service or (iv) anything arisen out of or in connection with the said payment gateways, including but not limited to unauthorised access to or alternation of the transmission of data or any unlawful act not permitted by the law.
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.
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.
- 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.
About the Partners
Students under this programme are eligible to apply free membership for Hong Kong Internet and Ecommerce Association (HKIECA).
The association offers talks, workshops and/or seminars related to the Internet and Ecommerce as well as Big Data.
Link of HKIECA: www.hkieca.org
- More Programmes of
- FinTech and Financial Intelligence
- Relevant Programmes
- Certificate for Module (Quantitative Methods in Finance) Postgraduate Diploma in FinTech and Legal Regulations Postgraduate Diploma in Finance and Data Analytics Postgraduate Diploma in Investment Management and Financial Intelligence Postgraduate Diploma in Applied Financial Engineering