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Accounting & Finance Finance and Compliance

Certificate for Module (Quantitative Methods in Finance)
證書(單元 : 金融定量分析方法)

CEF Reimbursable Course

CEF Reimbursable Course

Course Code
FN063A
Application Code
2180-FN063A

Credit
6
Study mode
Part-time
Start Date
13 Apr 2024 (Sat)
Duration
1 month to 2 months
Language
English
Course Fee
HK$6800 per programme
Deadline on 27 Mar 2024 (Wed)
Enquiries
2520 4612
2861 0278
Apply Now
This programme helps students acquire statistics and financial techniques. It is suitable for students preparing for further studies in finance and investment disciplines. Accept new application for the April 2024 intake!

Highlights

The programme aims to provide students with fundamental knowledge of statistical and quantitative methods in analyzing financial data. It covers time value of money, descriptive statistics, probability and probability distributions, inferential statistics and regression. Computational tools will be used to assist solving the finance and statistics problems. This programme is suitable for students preparing for postgraduate studies in finance and investment disciplines.
 

Programme Details

On completion of the programme, students should be able to

  1. describe the usage of statistical and quantitative approaches to study financial issues;
  2. explain basic statistical methods and theories to analyze financial data;  
  3. apply computational tools to wrangle financial data; and
  4. discuss the applications of statistical and quantitative methods to solve finance problems.

 

Application Code 2180-FN063A Apply Online Now
Apply Online Now

Days / Time
  • Saturday, 10:00am - 1:00pm & 2:00pm - 5:00pm
Duration
  • 30 hours
Venue

Modules

The programme consists of 30 contact hours with lectures and practical classes in computer laboratory.

Syllabus

(1) The Time value of money (TVM)

  • Introduction to computational tools
  • Present value, future value, annuity and perpetuity
  • TVM problems with different compounding periods, uneven cash flow series and asset valuations

 

(2) Descriptive statistics and data visualization

  • Introduction to statistical analysis and econometrics
  • Data collection and types of variables
  • Population and sample
  • Numerical descriptive measures
  • Financial data visualization using computational tools

 

(3) Probability theory

  • Basic probability concepts
  • Conditional probability
  • Bayes’ Theorem
  • Financial decision making under uncertainty

 

(4) Probability distributions

  • Discrete random variable and its distribution
  • Expected value, covariance and portfolio diversification
  • Skewness and Kurtosis
  • Discrete probability distributions: Binomial distribution, Poisson distribution
  • Continuous probability distributions: Normal distribution, t-distribution
  • Other distributions: Chi-squared distribution, F-distribution
  • Return distribution and VaR for financial risk management

 

(5) Sampling and sampling distributions

  • Types of sampling methods
  • Central Limit Theorem
  • Sampling distribution of the mean and proportion

 

(6) Confidence interval estimation

  • Confidence interval estimation for the mean and proportion
  • Sample size determination
  • Confidence Interval for portfolio returns

 

(7) Hypothesis testing

  • Null hypothesis and alternative hypothesis
  • One-sample tests: z-test, t-test, one-tailed test, two-tailed test
  • Critical value approach and p-value approach
  • Tests of significance
  • Type I and Type II errors
  • The relation between confidence intervals and hypothesis tests
  • Two-sample tests: z-test for the difference between two means, pooled-variance t-test, separate-variance t-test, paired t-test
  • Chi-square test and F-test
  • Hypothesis test for mean returns

 

(8) Linear regression

  • Determination of simple linear regression equation
  • Measures of variation using computational tools
  • Assumptions of linear regression
  • Inferences about the slope and correlation coefficient
  • Estimation of mean values and prediction of individual values
  • Stock beta and CAPM

 

(9) Introduction to multiple regression

  • Introduction to multiple regression and model building
  • Coefficient of multiple determination, adjusted r-square and overall F-test
  • Dummy variables
  • Hypothesis tests and confidence intervals in multiple regression
  • Issues with multiple regression
  • Multiple regression and financial modelling using computational tools

 

Assessment: class exercise (60%) & group presentation (40%)

Upon successful completion of the programme, students who have passed the continuous assessment and final assessment with attendance no less than 70% will be awarded within the HKU system through HKU SPACE the Certificate for Module (Quantitative Methods in Finance).

Class Details

  • Tentative timetable is subject to change and the course commencement is subject to sufficient enrollment
  • In case of cancel class, course fee will be refunded or transferred to next available intake

April 2024 Intake 

Lecture Date Time
1  13 Apr 24 (Sat)  10:00-13:00 & 14:00-17:00 
2   20 Apr 24 (Sat)  10:00-13:00 & 14:00-17:00 
3   27 Apr 24 (Sat)   10:00-13:00 & 14:00-17:00 
4   4 May 24 (Sat)  10:00-13:00 & 14:00-17:00 
5 11 May 24 (Sat) 10:00-13:00 & 14:00-17:00 


*(Class schedule will be given out upon one week prior to course commencement through by Email)

 

Fee

Course Fee
  • Course Fee : HK$6800 per programme

Entry Requirements

Applicants should hold an Advanced Diploma, a Higher Diploma or an Associate Degree awarded by a recognized institution. Those with a mathematics or science background would be at an advantage.

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

 

Teachers

(1) Mr. W. C. Chan

Mr. W. C. Chan, FRM, is professional in mathematical and statistical analysis as well as data analytics. He possessed rich experience in financial risk management, information technology and data science and worked as IT Manager over a decade. Being a practitioner in information technology, he is currently a consultant and trainer at Big Data Consultancy Services Company. He is strong in big data technology, data mining and machine learning. Mr. Chan has obtained a Bachelor of Science Degree in Mathematics from The Chinese University of Hong Kong as well as two Master’s Degrees, namely, Risk Management Science from The Chinese University of Hong Kong and Quantitative Analysis for Business from City University of Hong Kong.

(2) Ms. Rowena Lai

Ms. Lai is good at mathematical and statistical analysis as well as business analytics. With a Bachelor of Science (Major in Mathematics and Minor in Economics) from The Chinese University of Hong Kong, two Master of Science degrees in both International Shipping and Transport Logistics as well as Global Supply Chain Management from The Hong Kong Polytechnic University, she has worked with different industries on business analytics area. Ms. Lai is currently working in a leading banking and leading various projects related to data analytics. She has also worked in an airline industry leader, and shipping industry on revenue management and business analytics. Thanks to her strong business and analytical sense together with her extended working exposure, she would like to share her academic knowledge and practical experience in statistical methods and data analytics.

(3)  Mr. Ferrix Lau, ACS, ACIS, CFA, FRM

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.

(4) Mr. Andy Fung

Mr. Fung obtained his BSBA degree at The Ohio State University and MBA degree at the University of Illinois, Urbana. Mr. Fung is an experienced educator. For almost 20 years, he has been teaching extensively in various programs and in tertiary institutions such as School of Continuing and Professional Studies, The Chinese University of Hong Kong and The Hong Kong Community College.  Prior to joining the teaching profession, Mr. Fung had been working in the business sector for more than 10 years. His job exposure relates to banking, manufacturing and high technology industry. His last position was Finance Manager of Motorola (HK).

CEF

  • The CEF Institution Code of HKU SPACE is 100
CEF Courses
Certificate for Module (Quantitative Methods in Finance)
證書(單元 : 金融定量分析方法)
COURSE CODE 33C134888 FEES $6,800 ENQUIRY 2520-4612
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 (Quantitative Methods in Finance)

  • 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 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.
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 (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.

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 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.