MTECH FINANCIAL STATISTICS

The Master of Technology (M.Tech) Degree Programme in Financial Statistics is designed to enable B.Tech Financial Statistics students, and graduates from related programmes pursue advanced education and training in Financial Statistics. The programme aims to provide students with advanced statistics skills for exciting and challenging careers in the industries dealing with financial research and data analysis. Furthermore, the programme does not only seek to equip students with relevant tools to be able to analyse and critically interpret broad data, but is also designed to prepare them to be able to build statistical models of real situations.

The course has been designed to provide a greater depth of knowledge in aspects of advanced data analysis. These will enable the student to design financial data collection procedure, analyse and interpret data and to provide leadership in innovation, research and technology transfer. The curriculum makes adequate provision of several themes in financial data analysis, including financial applications, statistical modelling and inference, applied time series analysis.

 

Admission Requirements

The duration of the Master of Technology programme is two (2) years, and to gain admission to the programme, an applicant must satisfy the following minimum entry requirements.

Applicants must possess any of the underlisted qualification:

  1. B.Tech or B.Sc. Statistics
  2.  B.Tech orB.Sc. Financial Statistics
  3. B.Sc. Economics

 All applicants must have a minimum of one (1) year post-qualification industrial experience. Preference will be given to applicants with 1st Class and 2nd Class Upper Honours. First Class B.Tech Financial Statistics applicants may be admitted without the post-graduation industrial experience. Applicants with a second class (lower division) or lower qualifications will have to pass an interview before admission into the programme.

Applicants with other statistics or mathematics backgrounds would be required to take relevant financial science courses as prerequisites.

 

YEAR 1: COURSE-BASED PROGRAMME STRUCTURE

YEAR 1, SEMESTER 1

 

COURSE CODE

 

 

COURSE TITLE

 

STAF 501

 

Core

Advanced Probability Theory

STAF 503

 

Core

Statistical Inference

STAF 505

 

Core

Statistical Computing

STAF 507

 

Elective

Risk Management

STAF 509

 

Elective

Econometrics

STAF 511

 

Elective

Advanced Microeconomics

 

YEAR 1, SEMESTER 2

 

COURSE CODE

 

 

COURSE TITLE

 

STAF 502

Core

 

Statistical Modeling

STAF 504

Core

 

Advanced Research Methods

STAF 506

Core

 

Financial Science Statistics

STAF 508

Elective

 

Financial Economics

STAF 510

Core

 

Applied Time Series Analysis

STAF 512

Elective

 

Advanced Macroeconomics

 

 

YEAR 2: RESEARCH-BASED PROGRAMME STRUCTURE

YEAR 1, SEMESTER 2

 

COURSE CODE

COMPONENT

STAF 12

 

M. Tech Thesis I

STAF 14

 

Seminar I

STAF 13

 

M. Tech Thesis II

STAF 15

 

Seminar II

 

EMPLOYMENT

Employment Prospects of Graduates are as follows:

  1. Banking industry
  2. Stock Market
  3.  Insurance Firm
  4. Central Bank
  5. Ministries, e.g. Ministry of Finance and Economic Planning
  6. Regulatory bodies
  7. Consultancy viii. Academic institutions
  8. Research institutions
  9. Microfinance Companies

 

Duration: 
2 Years
Options Available: