Postgraduate

Modules

Modules

NBS8002 : Techniques for Data Analysis

Semesters
Semester 1 Credit Value: 10
Semester 2 Credit Value: 10
ECTS Credits: 10.0

Aims

• To introduce a broad range of underlying concepts and methodologies that are used in the data analytics process.
• To enable students to employ various analytical techniques that support effective decision-making in today’s increasingly competitive market. Students will also be equipped to appraise a wide range of applications and techniques for collecting, visualising, organising and analysing financial data that are designed to help financial analysts and other information users to improve their decision-making.
• To enable students to transform, analyse and interpret data, delivering solutions for theevaluation of investment opportunities in the financial sector.

Outline Of Syllabus

1. Descriptive statistics, visualising, organising and presenting data using appropriate tables, diagrams and numerical measures.
2. Basic probability theory and its applications, manipulations of proabilities applying various rules.
3. Referential statistics, sampling, estimation, hypothesis testing.
4. Regression, econometric modelling, autocorrelation, heteroscedasticity, multicollinearity.
5. Event study, literature review, methodology review, research design.
6. Challenges faced by modern financial data analysis in the context of emerging ‘big data’ society.

NB: The programme assumes no prior experience of statistics.

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Scheduled Learning And Teaching ActivitiesLecture152:0030:00N/A
Guided Independent StudyAssessment preparation and completion150:0050:00N/A
Guided Independent StudyDirected research and reading150:0050:00N/A
Scheduled Learning And Teaching ActivitiesSmall group teaching52:0010:004 seminars and 1 cluster session
Guided Independent StudyIndependent study160:0060:00N/A
Total200:00
Teaching Rationale And Relationship

Teaching is a combination of lectures and hands-on workshops held in the computer room. Work in the computer room will develop techniques to enable manipulation, co-ordination and presentation of relevant financial data. Skills relating to computer software are developed interactively on the computer network.

Assessment Methods

The format of resits will be determined by the Board of Examiners

Other Assessment
Description Semester When Set Percentage Comment
Report2A1004000 words - using statistical analysis of real data, examine impact of firm-specific information on a company’s stock returns.
Assessment Rationale And Relationship

There is one project, involving statistical analysis of financial data, including the presentation of data, development of a regression model for an event study, time series analysis and forecasting.

The objective of the report is to examine, using statistical analysis of real data, the impact of firm-specific information on a company’s stock returns. To complete the assignment, students are expected to undertake three types of activities: 1) Selecting a public company for analysis, collecting relevant data, and reviewing literature; 2) Performing appropriate analysis of the impact of multiple information events on the stock returns of a public company; 3) Writing up a report describing your research design and interpreting your research results.

Reading Lists

Timetable