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Accounting & Finance FinTech and Financial Analytics

New Course

Certificate for Module (Applied Econometrics and Financial Modelling)
證書( 單元 : 應用計量經濟學與金融建模)

CEF Reimbursable Course

CEF Reimbursable Course

Course Code
FN138A
Application Code
2370-FN138A

Credit
6
Study mode
Part-time
Start Date
28 Feb 2026 (Sat)
Next intake(s)
Apr 2026
Duration
30 hours
Language
English
Course Fee
Course Fee: $10,200 per programme (* course fees are subject to change without prior notice)
Deadline on 13 Feb 2026 (Fri)
Enquiries
2867 8331 / 2867 8424
2861 0278
Apply Now

Today and Upcoming Events

10
Dec 2025
(Wed)

How to Design a Strong-Stock Analytics Dashboard System (强勢股分析系統)? (10 Dec 2025)

To design a stock price analytics system, we need to do the following: Collect historical stock prices Transform the collected stock price record to an appropriate format for presentation Present the transformed stock price datasets in a useful layout to facilitate analytics and investors’ review.   In this talk (webinar), the speaker will showcase how to design a Strong Stock Analytics Dashboard with a BI approach. This would give you a fresh view of the practical use of data automation and data visualization techniques.   During this webinar, you will explore how a Strong Stock Analytics Dashboard will help you to: review the recent trend of HSI identify the strong stocks and weak stocks based on a specified definition of price momentum compare the ratio between the strong stocks and weak stocks according to your selected price momentum definition do sectoral analysis of the strong / weak stocks   This is an advanced application of data analytics techniques with common financial data.  You will find this webinar inspiring and will give you food for thought on how to make use of learnt data techniques for financial stock investment analysis.   Sample Screenshots below:   Related Programme Links: Certificate for Module (Technical Analysis and Data Analytics for Stock Investment) - HKU SPACE: FinTech and Financial Intelligence, Data Science courses https://hkuspace.hku.hk/prog/exe-cert-in-interpretation-and-visualization-of-business-big-data https://hkuspace.hku.hk/prog/cert-for-module-business-intelligence-and-data-automation

17
Dec 2025
(Wed)

Any correlation between Bitcoin, Ethereum and Gold? And now Stablecoin Explained (17 Dec 2025)

Bitcoin and Ethereum are the most dominant cryptocurrencies, both accumulative account for over 90% in term of market capitalization excluding stablecoin, out of more than two thousands currently in the market. They are both in a form of digital asset that trades via various DEX or centralizated regulated trading platforms. However there are quite many key differences among them though. Bitcoin (BTC) is designed as a monetary storage (some proclaim as alternative of Gold) and medium of transaction and as an alternative to fiat currency. Ethereum (ETH), otherwise, is intended for complex smart contracts or dApps which contribute and act as key infrastructure of the emerging Web3.0 future. In light of recent rapid further innovation (like staking protocol) and adoption, the price of BTC and ETH have been risen more than double in past 12 months and also exhibited a huge volatility. The speaker will give a brief introduction of above crypto with some attention drawn to the relationship and correlation among Bitcoin, Ethereum, Gold, XRP and S&P500 – as shown in below charts. The speaker will then also talk about the latest development and impacts of the recently passed GENIUS Act in U.S. and the Stablecoins Ordinance (Cap. 656) in HK. To say, Stablecoin per se. is NOT referring the price to be fixed or stable, it’s referring to link or collateralize by some tangible asse shifting from no intrinsic value issue. At 10 Oct 2025, one of most selloff in crypto, USDe has experienced flash crash to as low as 0.65 USDEUST, per shown below. Source: Bloomberg   Language: Cantonese (Supplemented with English)

Accept New Applications for Feb 26 intake! There will be practical classes in the computer laboratory. Economic issues, applied econometrics, and computing methods will reviewed. Topics related to time series analysis, panel data analysis, qualitative response models, limited dependent variable models, advanced regression techniques, and model building will be covered. Data pre-processing and web scraping, financial data analytics, financial risk measurement and modelling, machine learning and data analytics in financial modelling will be discussed.

Highlights

The programme aims to provide students with contemporary knowledge of applied econometrics and financial modelling. It equips students with practical skills to perform econometric analysis and financial data analytics using computational tools. The programme also covers advanced regression techniques, high-frequency data analysis and financial risk modelling.
 

Programme Details

On completion of the programme, students should be able to

  1. examine applied econometrics and financial data analytics;
  2. apply computational tools to wrangle data and build models;
  3. analyse quantitative results and draw inferences; and
  4. measure financial risks and evaluate financial models.
Application Code 2370-FN138A Apply Online Now
Apply Online Now

Days / Time
  • Saturday, 10:00am - 5:00pm
Duration
  • 30 hours per programme
Venue
  • Hong Kong Island Learning Centre
  • Kowloon West Campus
  • Kowloon East Campus

Modules

Course Content :

(1) Applied econometrics and model building

  • Review of basic econometrics and computing methods
  • Introduction to economic issues and applied econometrics
  • Basic time series analysis for economic and financial modelling
  • Panel data analysis
  • Qualitative response models
  • Limited dependent variable models
  • Advanced regression techniques and model building

(2) Financial modelling and model evaluation

  • Review of basic financial theories and models
  • Basic economic rationales and financial modelling
  • Data pre-processing and web scraping with computation tools
  • Financial data analytics
  • High-frequency data analysis and high-frequency trading
  • Financial risk measurement and modelling
  • Machine learning and data analytics in financial modelling
  • Model evaluation, diagnostics and remediation

Assessment method: Individual Assignment + Group Project Presentation

 

Award

Upon successful completion of the programme, students who have passed the assessments with attendance no less than 70% will be awarded within the HKU system through HKU SPACE a "Certificate for Module (Applied Econometrics and Financial Modelling)".

 

Class Details

Timetable

Lecture Date Time
1 28 Feb26 (Sat) 10:00-13:00 & 14:00-17:00
2 7 Mar 26 (Sat) 10:00-13:00 & 14:00-17:00
3 14 Mar 26 (Sat) 10:00-13:00 & 14:00-17:00
4 21 Mar 26 (Sat) 10:00-13:00 & 14:00-17:00
5 28 Mar 26 (Sat) 10:00-13:00 & 14:00-17:00

Remarks: Tentative timetable is subject to change, and course commencement is subject to sufficient enrollment numbers 

Teacher Information

Mr Max Lee

Background

Mr Max Lee is a co-founder of a fintech startup specializing in smart contracts and token certificates, focusing on innovative solutions in digital asset ownership and blockchain-driven efficiencies. Before that, Mr Lee spent over 19 years in wealth management. He was with HSBC for 11 years and held a few leadership roles where he led strategic initiatives and managed complex investment portfolios. Max has a Master of Financial Innovation and Technology from the Smith School of Business, Queen’s University, and earned the Dean’s Entrance Scholarship. He also holds a Master of Finance in Financial Engineering from the University of Hong Kong and is a Chartered Financial Analyst (CFA).

Mr Ian Chan

Background

Mr Ian Chan holds a Bachelor’s degree and a Research Master’s degree in Economics from The Chinese University of Hong Kong (CUHK). With professional experience spanning key regulatory institutions, including the Competition Commission, the Census and Statistics Department, and the Hong Kong Monetary Authority (HKMA), Mr Chan has cultivated deep expertise in data analytics and regulatory frameworks.

Specializing in big data and granular data analytics, Mr Chan has hands-on experience in data automation, database management, quantitative analysis, and data visualization. Their work also extends to advanced methodologies such as textual analysis, network analysis, and the integration of generative AI applications into data analysis workflows. This unique combination of skills enables him to derive actionable insights and drive innovation in data-driven decision-making.

Fee

Application Fee

HK$150 (Non-refundable)

Course Fee
  • Course Fee: $10,200 per programme (* course fees are subject to change without prior notice)

Entry Requirements

Applicants should hold an Advanced Diploma, a Higher Diploma or an Associate Degree awarded by a recognised institution where the language of teaching and assessment is English. Applicants who do not have a background in economics, finance, mathematics, statistics, science or engineering are required to complete the Certificate for Module (Introduction to Econometrics and Data Analytics) awarded within the HKU system through HKU SPACE before studying this programme.

Applicants with other equivalent qualifications will be considered on individual merit.

**Please upload copy of HKID and proof of degree while applying online

CEF

  • The CEF Institution Code of HKU SPACE is 100
CEF Courses
Certificate for Module (Applied Econometrics and Financial Modelling)
證書(單元:應用計量經濟學與金融建模)
COURSE CODE 33C163640 FEES $10,200 ENQUIRY 2867-8424
Continuing Education Fund Continuing Education Fund
This course has been included in the list of reimbursable courses under the Continuing Education Fund.

Certificate for Module (Applied Econometrics and Financial Modelling)

  • This course is recognised under the Qualifications Framework (QF Level [5])

Apply

Online Application Apply Now

Application Form Download 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 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 personal information and 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 (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, new and continuing students of award-bearing programmes with available online service, they may also pay their course fees by Online WeChat Pay, Online Alipay or 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 Enrolment Centres and avoid making cheque payment under this circumstance.

  • 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, FPS or PPS by Internet will be reimbursed by a cheque, and fees paid by credit card will be reimbursed to the credit card account used for payment. 

  • 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.
  • HKU SPACE will not be responsible for any loss of payment, receipt, or personal information 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.