Accounting & FinanceFinTech and Financial Intelligence
Executive Diploma in Financial Analytics
- Course Code
- Application Code
- Study mode
- Start Date
- 05 Dec 2020 (Sat)
- Next intake(s)
- Feb 2021
- 2 months to 4 months
- Course Fee
- $8,000 per module; $16,000 per programme
The recent advances in Big Data and AI have major impact on the investment...
Accept new application for December intake!
To apply Python programming, Machine Learning and Algorithmic Trading, welcome for enrolling Executive Diploma in Financial Analytics programme.
Python is a high level programming language for tackling data science and computational problems while AI, Machine Learning and Deep Learing are widely using in algorithmic trading system and solving analytical problems.
To ensure that students’ academic progress is not affected, the School may substitute face-to-face classes with online teaching if necessary in the event that face to-face classes cannot be held. Our respective Programme Teams will contact the students concerned with details of such arrangements as necessary.
|This programme aims to provide students with the knowledge to investigate financial data which influences finance and investment decisions. Computer coding using Python will be discussed to handle data, build models and perform financial analysis quantitatively. The programme covers the applications of AI, Machine Learning and computerized algorithms to analyze trends and predict financial data.|
On completion of the programme, students should be able to
Mr. Chung is a specialist in Machine Learning, Statistical Analysis and Data Science. He received his Bachelor and Master Degree in Mathematics from the University of Toronto. He had been a Mathematics and Statistics lecturer in HKUSPACE Community College for more than six years. Since 2013, he became interested and has been doing research in Data Science and Machine Learning. Coming from an academic background, and then working as a machine learning engineer and data scientist, Mr. Chung likes to discuss Data Science and Machine Learning from both theoretical and practical perspectives.
(2) 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. Ken earned a Master in Computer Science from USC and a Bachelor in Computer Science from University of Warwick.
(3) Mr. Mr. Stephen Cheng
Mr. Stephen Cheng has over 30 Years of experience in the IT industry, with senior positions at international corporations such as Oracle, Hewlett Packard, Digital Equipment Corporation, Compaq Computer, Portal Software, Amdocs. Mr. Cheng’s broad industrial experience ranges from R&D, Software development, Consulting, Marketing, Pre-sales and Professional Services. Stephen has a strong track record in delivering successful projects worldwide: Swisscom, Vodafone, China Mobile, Smartone, HSBC, Telstra etc. Mr. Cheng holds a Bachelor of Arts (Physics) from Vassar College; MS and MBA from Rensselaer Polytechnic Institute and Babson College in the US. Mr. Cheng is currently working on a project at the Hong Kong Chinese University, applying Machine Learning and AI techniques on Traditional Chinese Medicine.
|Application Code||1860-EP148A||Apply Online Now|
|Apply Online Now|
Days / Time
- Saturday, 1:00pm - 7:00pm
- Kowloon East Campus
- Hong Kong Island Campus
Module 1: Python for Financial Analytics (30 hours)
- Introduction to Python programming
- IDLE environment for Python
- Python modules and library
- Data Structures, conditional execution and iterations
- Mathematics and Statistics for Financial Analytics
- Mathematical computation using Python
- Statistics using Python
- Data Visualization using Python
- Applications of Financial Analytics for Modelling and Simulation
- Introduction to Financial Analytics
- Regression model for predictive analytics
- Binomial model for bond and option pricing
- Black–Scholes model and option implied volatility
- Risk modelling for financial risk management
- Monte Carlo Simulation for asset pricing
- Simulations using time series models
Assessment method: In-class exercise + group presentation
Module 2: Machine Learning and Algorithmic Trading (30 hours)
- AI and Machine Learning
- Development of AI and Machine Learning (ML)
- Mathematical concepts for Machine Learning
- Applications of Machine Learning and Deep Learning: Natural Language Processing, Sentimental Analysis
- Learning Algorithms and Models
- Supervised Learning: Support Vector Machine, Decision Tree, Random Forest, Regression
- Unsupervised Learning: Clustering, Neural Networks, Principal Component Analysis
- Reinforcement Learning: Markov Decision Processes, Q-Learning, Policy Gradients
- Illustration of computer coding about related algorithms and models for investment
- Algorithmic Trading
- Investment strategies for algorithmic trading
- Trading Execution Algorithms
- Strategy Implementation Algorithms
- Stealth/Gaming Algorithms
- Arbitrage Opportunities
- Illustration of computer coding of trading algorithms
Assessment method: In-class exercise + group presentation
The Executive Diploma will be conferred to candidates who have attained PASS grade and achieved at least 70% attendance of the programme.
Students completing Module 1 can exit the programme with the intermediate award, Executive Certificate in Financial Analytics. For students completing both Modules 1 and 2, they can get the award of Executive Diploma in Financial Analytics.
Module 1: Python for Financial Analytics
|1||5 Dec 20 (Sat)||13:00 - 19:00|
|2||12 Dec 20 (Sat)||13:00 - 19:00|
|3||19 Dec 20 (Sat)||13:00 - 19:00|
|4||9 Jan 21 (Sat)||13:00 - 19:00|
|5||16 Jan 21 (Sat)||13:00 - 19:00|
Module 2: Machine Learning and Algorithmic Trading
|1||March 2021||13:30 - 19:30|
|2||March 2021||13:30 - 19:30|
|3||March 2021||13:30 - 19:30|
|4||March 2021||13:30 - 19:30|
|5||March 2021||13:30 - 19:30|
Remarks : Tentative timetable is subject to change and course commencement is subject to sufficient enrollment numbers.
Applicants shall hold:
a) a bachelor’s degree awarded by a recognized University or equivalent; or
b) an Associate Degree/ a Higher Diploma or equivalent, and have at least 2 years of relevant working experience.
Applicants with qualifications in quantitative areas (e.g., mathematics, engineering, statistics, computer science, economics, finance) are preferred.
Applicants with other qualification and substantial senior level work experience will be considered on individual merit.
**Please upload copy of HKID and proof of degree while applying online.
HK$150 (Student only needs to pay one time application fee for all EC in Big Data Series)Course Fee
- $8,000 per module; $16,000 per programme
Online Application Apply NowEnrolment Method
HKU SPACE provides 24-hour online application and payment service for students to make enrolment for most open admission courses (courses enrolled on first come, first served basis) and selected award-bearing programmes via the Internet. Applicants may settle the payment by using either PPS, VISA or Mastercard online.
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 be admitted 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 programme/course fees by either using:
PPS via 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”.
To know more about online enrolment and payment, please refer to the user guide of Online Enrolment and Payment:
In Person / Mail
For first time enrolment
Applicants must provide all the required information on the application form and any additional information as required after the intial application assessment. Otherwise the School may not be able to process the admission/enrolment further.
- 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.
- 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 course
In person or by post
- 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.
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 S-MILES and Early Bird Discount are supported in 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, 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 or EPS
Cash or EPS are accepted 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 write the programme title(s) and the applicant’s name on the back of the cheque. You may either:
- in person by submitting the payment, completed form(s), and required supporting documents to any of our enrolment centres; or
- by mailing the above documents to any of our enrolment centres, specifying “Course Application” on the envelope.
Course applicants, who are holders of HKU SPACE Mastercard, can enjoy a 10-month interest-free instalment period for courses of HK$2,000 and over. For enquiries, please contact our enrolment centres.
4. Online payment
Online payment for short courses (first come, first served) and selected award-bearing programmes is available using PPS, VISA or Mastercard. Please refer to the Online Services page on the School website.
- For general and short courses, applicants may be required to pay the course fee in cash or by EPS, Visa or Mastercard if the course is to start shortly.
- 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, cheque or online PPS will be reimbursed by a cheque; fees paid by credit card will be reimbursed to 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 teams for details.
- Fees and places on courses are not transferrable. 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 additional copies of receipts, 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. Such copies will normally be issued at the end of a course.
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