Accounting & Finance Finance and Compliance
The programme aims to provide students with elementary knowledge of time series analysis for financial data. It introduces basic time series models, models and tests for long-run relationships, volatility models and simultaneous equation models. Computational tools will be used to analyze time series and build financial models. This programme is suitable for students to prepare for postgraduate studies in finance and investment disciplines.
On completion of the programme, students should be able to
- describe the characteristics of financial time series data and linear and non-linear time series models;
- explain long-run relationships models, volatility models and simultaneous equation models;
- apply computational tools to investigate and analyze financial time series data; and
- discuss the applications of time series for financial modeling.
|1||5 Nov 22 (Sat)||10:00-13:00 & 14:00-17:00|
|2||12 Nov 22 (Sat)||10:00-13:00 & 14:00-17:00|
|3||19 Nov 22 (Sat)||10:00-13:00 & 14:00-17:00|
|4||26 Nov 22 (Sat)||10:00-13:00 & 14:00-17:00|
|5||3 Dec 2022 (Sat)||10:00-13:00 & 14:00-17:00|
Days / Time
- Saturday, 10:00am - 5:00pm
- 30 hours
6 hours per meeting
- Hong Kong Island Learning Centre
- Kowloon East Learning Centre
The programme consists of 30 contact hours with lectures and practical classes in computer laboratory.
(1) Fundamentals of Time-Series Models
- Introduction to time series and financial econometrics using computational tools
- The nature of financial time series data and times series decomposition
- Brief review on regression analysis
- Overview of linear time-series models
- Stationary Time Series Models: moving average (MA) processes and MA models, autoregressive (AR) processes and AR models
- Nonstationary Time Series Models: Autoregressive integrated moving average (ARIMA) models
- Seasonal models
- Overview of non-linear time series models
- Exponential Smoothing: Simple Exponential Smoothing, Holt-Winters’ Seasonal Smoothing
- Threshold Autoregressive (TAR) Models
- Self-Exciting Threshold Autoregression (SETAR) Models
(2) Basic Long-Run Relationships Models
- Stationarity and unit root testing: Dicky-Fuller test, Augmented Dickey-Fuller test, Philips-Perron test, KPSS test
- Spurious regressions and cointegration
- Engle-Granger test
- Error-correction models
- General to Specific Modelling
(3) Principles of Volatility Modeling
- ARCH models
- GARCH models
- Extensions to GARCH models
- Usage of GARCH type models
- Forecasting variances using GARCH type models
- Usage of variance forecasts
(4) Introduction to Simultaneous Equation Models (SEM)
- Overview of Structural Model and Reduced-Form Model
- The Identification of Simultaneous Equation Models
- Parameter Estimation
(5) Basic Time Series Applications
- Intervention Analysis and Outlier Detection
- Longitudinal Analysis
- Time Series Regression and Vector Time Series Models: VAR/ARCH Models
- Spectral Analysis
- Financial time series analysis and model building with 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 (Introduction to Financial Time Series Analysis).
- 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
Applicants should hold an Advanced Diploma, a Higher Diploma or an Associate Degree preferably in the areas of business and statistics (e.g., mathematics, statistics, computer science, IT, engineering, economics or finance) awarded by a recognized institution. Applicants with other equivalent qualifications will be considered on individual merit.
(1) Mr. Alan Cheung
Mr. Alan Cheung, PRM, CQF, has solid skills in the applications of the finance time series analysis and financial model building. Also, he has solid experience in fintech in top tier investment banks, versed in architecting low latency, high frequency algorithmic trading systems. He is currently a Quantitative Strategist on the Equities Desk in Bank of America Merrill Lynch. Alan has a Master of Science in Mathematical and Computational Finance from the University of Oxford after graduating with First Class Honours in Mathematics with Statistics for Finance from Imperial College London. Currently, Mr. Alan Cheung is teaching modules under Postgraduate Diploma in Applied Financial Engineering and Postgraduate Diploma in Finance and Data Analytics.
(2) Dr. Zenki Kwan
Dr. Zenki Kwan, FRM, CAIA, CB, is good at quantitative finance and financial time series analysis. He is the investment director of a listed company and a family office in Hong Kong, responsible for investment strategy and portfolio management across equities, fixed income, currency, funds and structured products. He has previously worked in J.P. Morgan, UBS, McKinsey and Samsung Securities. In addition to his doctoral degree, Dr. Kwan also holds Master of Finance and Master of Applied Business Research degrees and completed executive education programs at Harvard Law School and Oxford University Saïd Business School, respectively. Dr. Kwan is currently teaching modules under Postgraduate Diploma in Applied Financial Engineering and Postgraduate Diploma in Finance and Data Analytics.
(3) Mr. Ferrix Lau
Mr. Ferrix Lau, ACS, ACIS, CFA, FRM 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. Kenrick Yeung
Mr. Kenrick Yeung received one MSc in Data Science and Business Statistics from The Chinese University of Hong Kong, and another MSc in Applied Economics from Hong Kong Baptist University, and his bachelor degree in Economics and Finance in Hong Kong Shue Yan University. He has been teaching Microeconomics, Macroeconomics, Statistics, Econometrics, Engineering Economics, Geopolitics and Corporate Finance.
(5) Mr. Felix Chan
Mr. Felix Chan, FRM, ACAMS holds a Master's Degree in Data Science from The University of Hong Kong, and his bachelor degree in Quantitative Finance and Risk Management Science in the Chinese University of Hong Kong. He has strong interests in the areas of Big Data, Machine Learning and Statistical Analysis. Besides, he has years of experience working at multiple major technology companies, through which he has help corporates in various sectors including finance, government, professional services, etc. realize value through technology and data science.
- Course Fee : HK$7600 per programme
- The CEF Institution Code of HKU SPACE is 100
|Certificate for Module (Introduction to Financial Time Series Analysis)
證書(單元 : 金融時間序列分析入門)
|COURSE CODE 33C13554A||FEES $7,600||ENQUIRY 2520-4612|
|Continuing Education Fund
This course has been included in the list of reimbursable courses under the Continuing Education Fund.
Certificate for Module (Introduction to Financial Time Series Analysis)
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