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Accounting & Finance FinTech and Financial Analytics

Certificate for Module (Technical Analysis and Data Analytics for Stock Investment)
證書(單元 : 股票投資的數據與技術分析)

CEF Reimbursable Course

CEF Reimbursable Course

Course Code
FN093A
Application Code
2365-FN093A

Credit
6
Study mode
Part-time
Start Date
13 Jan 2026 (Tue)
Next intake(s)
May 2026
Duration
30 hours
Language
English
Course Fee
Course Fee: $9900 per programme (* course fees are subject to change without prior notice)
Deadline on 05 Jan 2026 (Mon)
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)

Confirmed Launch for Jan 2026 intake! There are practical classes in the computer laboratory. By visualizing stock prices using computational tools, technical analysis can be performed professionally, and stock trends can be identified efficiently. Our professional lecturer will share analytical techniques to filter stocks based on technical indicators and predict stock price movement for investment decision-making. Welcome to your online application!

Highlights

The programme aims to provide students with the basic knowledge of stock investment and data analytics, and the essential skills in analysing trends and patterns of stock prices using technical analysis. The programme illustrates techniques of web scraping and data wrangling of stock price data using computational tools. It also discusses technical analysis charts using data visualization. Students can learn how to analyse stock price trends and predict stock price movement to support investment decision-making through practical classes in the computer laboratory.
 

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This programme facilitates you to learn how to use data visualization techniques with a systematic approach to understand predictive analytics by focusing on the following scope of practical work: how to

  1. Understand the recent ambience of the stock market as a whole,
  2. Perform sectoral analysis of stocks,
  3. Select stocks that recently performed well,
  4. Look for stocks that recently performed poorly to find oversold stocks,
  5. Visualize a stock's price strength change to predict its recent price trend before making an appropriate stock trading decision, and
  6. Collect historical stock prices with Excel.

Besides, this programme would also cover the following common chart design for supplementary stock price analytics:

  • Candlestick Chart
  • Bollinger Band Chart
  • Moving Average Stock Price Chart
  • MACD Line Chart
  • RSI Distribution Chart

As you will use Tableau for the above chart design in the practical classes of this programme, the lecturer will introduce the basic techniques of using Tableau before teaching stock analytics.

Programme Details

On completion of the programme, students should be able to

  1. explain the principles of technical analysis and data analytics for stock investment;
  2. analyse patterns on technical analysis charts with the use of technical indicators;
  3. apply computational tools to perform data wrangling, data visualization, statistical analysis and trend prediction of stock prices; and
  4. discuss data-driven decision making and evaluate stock investment performance

 

Application Code 2365-FN093A Apply Online Now
Apply Online Now

Days / Time
  • Tue - Wed, 7:00pm - 10:00pm
Duration
  • 30 hours per programme
Venue
  • Kowloon East Campus
  • Hong Kong Island Learning Centre
  • Kowloon West Campus

Modules

Syllabus

(1) Introduction to technical analysis, data analytics and stock investment  

  • Introduction to data analytics and computational tools
  • Basic analysis of price data for stock investment
  • Principles and assumptions of technical analysis
  • Linkages between technical analysis and behavioral finance
  • Comparison of technical analysis and fundamental analysis for stock investment

(2) Technical analysis and descriptive analytics for stock investment

  • Sources of stock prices and techniques of web scrapping
  • Development of stock price datasets and application of descriptive analytics
  • Data wrangling of stock prices using computational tools
  • Comprehensive stock selection with common filters on price change, turnover, moving average prices and range of technical indicator values
  • Application of technical analysis charts and technical indicators: candlestick charts, Bollinger Bands, MACD curves
  • Visual analytics for stock investment (e.g., price trend in motion)

(3) Stock investment and predictive analytics

  • Overview of stock investment strategies and data-driven decision making
  • Smoothing of stock price trend to facilitate price movement prediction
  • Predictive analytics and stock price analysis
  • Analysis of stock investment by sectors and visualization of investment dashboard
  • Measurement of accuracy and investment performance evaluation

Assessment method: Two in-class exercise + Group Project Presentation

Upon successful completion of the programme, students who have passed the final examination with attendance no less than 70% will be awarded within the HKU system through HKU SPACE a Certificate for Module (Technical Analysis and Data Analytics for Stock Investment).

Teacher

(1) Mr W. C. Chan

Mr Chan, FRM, is currently a consultant and trainer at a Big Data Consultancy Services Company. He is very professional in teaching big data analytics and data automation for business. He possesses rich experience in financial risk management, information technology and data science and has worked as an IT Manager for over a decade. He is strong in cloud-based solutions, big data technology, data mining and machine learning. Mr Chan has delivered training in data science areas, covering R, machine learning, statistics, database programming, AWS cloud architecture and SAS programming for IT professionals and university graduates for over 2 years. He worked as the Head of BI Data Analytics and R&D Team in Li & Fung Group Company, GBG Asia (HK) Limited, IDS Group Ltd. & LF Asia and so on, devoting himself to IT development and project management.

Mr Chan has obtained a Bachelor of Science Degree in Mathematics from The Chinese University of Hong Kong as well as three Master's Degrees, namely, Risk Management Science from The Chinese University of Hong Kong, Quantitative Analysis for Business from the City University of Hong Kong and Industrial Logistics Systems from The Hong Kong Polytechnic University.

Class Details

Lecure Date Time
1 13 Jan 26 (Tue) 19:00-22:00
2 14 Jan 26 (Wed) 19:00-22:00
3 20 Jan 26 (Tue) 19:00-22:00
4 21 Jan 26 (Wed) 19:00-22:00
5

27 Jan 26 (Tue)

19:00-22:00
6 28 Jan 26 (Wed) 19:00-22:00
7 3 Feb 26 (Tue) 19:00-22:00
8 4 Feb 26 (Wed) 19:00-22:00
9 10 Feb 26 (Tue) 19:00-22:00
10 11 Feb 26 (Wed) 19:00-22:00

 

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

 

 

Fee

Application Fee

HK$150 (Non-refundable)

Course Fee
  • Course Fee: $9900 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. Those with economics, finance, business, IT or computer science background are preferred.

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

CEF

  • The CEF Institution Code of HKU SPACE is 100
CEF Courses
Certificate for Module (Technical Analysis and Data Analytics for Stock Investment)
證書(單元 : 股票投資的數據與技術分析)
COURSE CODE 33C151243 FEES $9,900 ENQUIRY 2867-8331
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 (Technical Analysis and Data Analytics for Stock Investment)

  • 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.