Main content start
Change.每天多學一點 改變.可大可小

Accounting & Finance FinTech and Financial Analytics

Certificate for Module (Technical Analysis and Quantitative Investing)
證書(單元 : 技術分析與量化投資)

Course Code
FN185A
Application Code
2460-FN185A
Credit
6
Study mode
Part-time
Start Date
09 Dec 2026 (Wed)
Next intake(s)
Mar 2026
Duration
30 hours
Language
English
Course Fee
Course Fee: HK$10,800 per programme (* course fees are subject to change without prior notice)
Deadline on 27 Nov 2026 (Fri)
Enquiries
2867 8331 / 2867 8424
2861 0278
Apply Now

Accept New Applications for Dec 26 intake! There will be practical classes in the computer laboratory.

Highlights

The programme aims to equip students with foundational knowledge of behavioural finance, advanced technical analysis, and practical algorithmic programming skills tailored to quantitative investing. Following a logical progression from market structure, price action, and indicator taxonomy to platform scripting (Pine Script and MQL5), systematic backtesting, generative artificial intelligence (GenAI) strategy integration, and institutional risk modelling, students will learn to design, code, and evaluate automated trading systems that exploit market inefficiencies and optimise portfolio execution. The programme also cultivates students’ ability to apply quantitative tools and programmatic indicators to solve real-world investment problems, while embedding systematic risk management, bias mitigation, and governance of emerging technologies to deliver robust, risk-adjusted trading strategies.

Programme Details

On completion of the programme, students should be able to

  1. critically examine the principles of behavioural finance and technical analysis, and their intersection with quantitative investing;
  2. evaluate the performance of various technical analysis techniques for different financial instruments and market situations;
  3. utilise programming languages on technical analysis software platforms to identify historical trends and trading signals;
  4. develop and test proprietary trading rules for various financial instruments with selected technical indicators on the software platform; and
  5. discuss risk management using quantitative measures, and the risks of emerging technologies in quantitative investing.
Application Code 2460-FN185A Apply Online Now
Apply Online Now

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

Modules

Course Content :

(1) Introduction to behavioural finance and quantitative investing

  • Basics of behavioural finance
  • Overview of algorithmic (algo) and quantitative trading
  • The intersection of behavioural finance and quantitative investing

(2) Introduction to technical analysis

  • Overview of technical analysis
  • The foundations of price action and market structure
  • Indicator categories and technical indicators for quantitative investing
    • Trend indicators: moving averages (MA), and moving averages convergence divergence (MACD)
    • Momentum indicators (oscillators): relative strength index (RSI), and stochastic oscillator
    • Volatility indicators: Bollinger bands, and average true range (ATR)
    • Volume indicators: On-balance volume (OBV), and volume rate of change
    • Others: candlesticks (K-lines) and Fibonacci retracement
  • Limitations of technical analysis

(3) Introduction to software platform

  • Overview of MetaTrader 5 and TradingView
  • Basic programming skills (Pine Script and MQL5)
  • Use the software platform to select relevant technical indicators to analyse historical trends and identify trading signals

(4) Deep dive into quantitative trading

  • Introduction to market microstructure and quantitative trading
  • Overview of popular quantitative trading strategies
  • Role of generative artificial intelligence (GenAI) in quantitative trading strategies
  • Backtesting and biases
  • Evaluation of strategy performance across different financial instruments and market situations

(5) Risk management for quantitative investing

  • Overview of financial risk management
  • Understanding popular risk management measures: Sharpe ratio, Sortino ratio, maximum drawdown, and value at risk (VaR)
  • Development of relevant risk management measures for trading strategies
  • Evaluation of risks of artificial intelligence (AI) and emerging technologies on quantitative investing

Assessment method: In-class Exercise + Group Project Presentation

 

Award

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

Class Details

Timetable

Lecture

Date

Time

1

9 Dec 26 (Wed)

19:00-22:00

2

11 Dec 26 (Fri)

19:00-22:00

3

16 Dec 26 (Wed)

19:00-22:00

4

18 Dec 26 (Fri)

19:00-22:00

5

6 Jan 27 (Wed)

19:00-22:00

6

8 Jan 27 (Fri)

19:00-22:00

7

13 Jan 27 (Wed)

19:00-22:00

8

15 Jan 27 (Fri)

19:00-22:00

9

20 Jan 27 (Wed)

19:00-22:00

10

22 Jan 27 (Fri)

19:00-22:00

Teacher Information

Dr Francis Lau

Background

Dr Lau is a seasoned financial data analytics practitioner, and a professional trainer in finance-related disciplines. He has over 22 years of experience in business planning, data analytics, management information, regulatory compliance, and risk management acquired from working for multinational analytics vendors, banks, consulting firms, and universities. Dr Lau is a subject matter expert in applying data analytics to enhance business decision-making, constructing quantitative models to gauge business performance, and streamlining the management reporting processes. In addition to industry experiences, Dr Lau also has extensive exposures in developing and delivering academic and professional education programs for financial institutions, professional associations and universities. Dr Lau is a well-recognized trainer in compliance, data science, financial markets, risk management, and sustainability.

Fee

Application Fee

HK$150

Course Fee
  • Course Fee: HK$10,800 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. Those with a background in business, accounting, finance, economics, mathematics, statistics, science, engineering, IT or computer science would have an advantage.

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

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

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.
More Programmes of
FinTech and Financial Analytics