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:
- B.Tech or B.Sc. Statistics
- B.Tech orB.Sc. Financial Statistics
- 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
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COURSE CODE
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COURSE TITLE
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STAF 501
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Core |
Advanced Probability Theory |
STAF 503
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Core |
Statistical Inference |
STAF 505
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Core |
Statistical Computing |
STAF 507
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Elective |
Risk Management |
STAF 509
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Elective |
Econometrics |
STAF 511
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Elective |
Advanced Microeconomics |
YEAR 1, SEMESTER 2
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COURSE CODE
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COURSE TITLE
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STAF 502 |
Core
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Statistical Modeling |
STAF 504 |
Core
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Advanced Research Methods |
STAF 506 |
Core
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Financial Science Statistics |
STAF 508 |
Elective
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Financial Economics |
STAF 510 |
Core
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Applied Time Series Analysis |
STAF 512 |
Elective
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Advanced Macroeconomics |
YEAR 2: RESEARCH-BASED PROGRAMME STRUCTURE
YEAR 1, SEMESTER 2
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COURSE CODE |
COMPONENT |
STAF 12
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M. Tech Thesis I |
STAF 14
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Seminar I |
STAF 13
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M. Tech Thesis II |
STAF 15
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Seminar II |
EMPLOYMENT
Employment Prospects of Graduates are as follows:
- Banking industry
- Stock Market
- Insurance Firm
- Central Bank
- Ministries, e.g. Ministry of Finance and Economic Planning
- Regulatory bodies
- Consultancy viii. Academic institutions
- Research institutions
- Microfinance Companies