| Language of instruction : English |
| | | Exam contract: not possible |
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Sequentiality
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No sequentiality
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Change the language, year or choose another item in the dropdown list if it is available.
| Degree programme | | Study hours | Credits | P2 SBU | P2 SP | 2nd Chance Exam1 | Tolerance2 | Final grade3 | |
 | master TEW-AFF | Compulsory | 81 | 3,0 | 81 | 3,0 | Yes | Yes | Numerical |  |
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| | | Learning outcomes |
- EC
| The holder of the degree applies acquired knowledge independently. (Self-direction and entrepreneurial spirit)
| - EC
| The holder of the degree communicates clearly and correctly in writing and orally, in a business and academic context, if necessary supplemented with visual support. (Communication) | - EC
| The holder of the degree shows autonomy in implementing scientific research methods. (Research skills) | - EC
| The holder of the degree shows autonomy in analysing, interpreting, evaluating and reporting research results. (Research skills) | - EC
| The holder of the degree is able to apply in-depth insights and argumentation methods from business science and relevant supporting and/or related disciplines in solving strategic policy issues. (Problem-solving capacity) |
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| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
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The student is interested in mathematics and statistics/econometrics in a macroeconomic and financial context.
The student knows the basic principles of estimating a linear regression analysis in a multivariate setting.
The students is able to formulate and estimate a regression model. We note that these principles are taught in any basic econometric course.
The use of any software package using econometric tools is required. The course will use STATA as a software package but prior knowledge of STATA is not a minimum requirement for the competence.
The student is able to gain financial insights in data interpretation.
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The structure of the course entails a theoretical part whereby empirical methods are explained using financial applications as well as an empirical part whereby students work on computer applications using statistical software (STATA). In addition, some pratical assignments will also be organized. The following topics will be discussed:
*Regression and volatility
*forecasting techniques (Direct forecasting models, (G)ARCH modellen)
*Portfolio theory of Markowitz with an empirical application
*Capital Asset Pricing Model (CAPM)
*Efficient Market Hypothesis
*Exchange rate forecasting
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Lecture ✔
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Small group session ✔
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Empirical Assignment ✔
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Period 2 Credits 3,00
| Evaluation method | |
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| Written evaluaton during teaching periode | 20 % |
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| Other | Empirical assignments |
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Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
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| Explanation (English) | Second reset exam is written and closed book and counts for the entire (100%) final grade. |
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| Compulsory textbooks (bookshop) |
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[Empirical Methods for Finance and Banking],[Robert Sollis],[1st],[Wiley],[9780470512890],[] |
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| 1st Master of Business Engineering - Accountancy and Finance - Finance track | Compulsory | 81 | 3,0 | 81 | 3,0 | Yes | Yes | Numerical | |
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| | | Learning outcomes |
- EC
| The holder of the degree applies acquired knowledge independently. (Self-direction and entrepreneurial spirit) | - EC
| The holder of the degree communicates clearly and correctly in writing and orally, in a business and academic context, if necessary supplemented with visual support. (Communication) | - EC
| The holder of the degree shows autonomy in implementing scientific research methods. (Research skills) | - EC
| The holder of the degree shows autonomy in analysing, interpreting, evaluating and reporting research results. (Research skills) | - EC
| The holder of the degree applies in-depth insights from business science and relevant supporting/related disciplines in the analysis of financial and technical business problems. (Problem-solving capacity) | - EC
| The holder of the degree models, designs and evaluates solutions for financial and technical business problems to support decision-making at different levels in a complex context. (Problem-solving capacity) | - EC
| The holder of the degree uses IT applications and basic programming skills to translate financial and technical business data into business-relevant information. (Programme-specific competencies) |
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| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
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The student is interested in mathematics and statistics/econometrics in a macroeconomic and financial context.
The student knows the basic principles of estimating a linear regression analysis in a multivariate setting.
The students is able to formulate and estimate a regression model. We note that these principles are taught in any basic econometric course.
The use of any software package using econometric tools is required. The course will use STATA as a software package but prior knowledge of STATA is not a minimum requirement for the competence.
The student is able to gain financial insights in data interpretation.
|
|
|
|
The structure of the course entails a theoretical part whereby empirical methods are explained using financial applications as well as an empirical part whereby students work on computer applications using statistical software (STATA). In addition, some pratical assignments will also be organized. The following topics will be discussed:
*Regression and volatility
*forecasting techniques (Direct forecasting models, (G)ARCH modellen)
*Portfolio theory of Markowitz with an empirical application
*Capital Asset Pricing Model (CAPM)
*Efficient Market Hypothesis
*Exchange rate forecasting
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Lecture ✔
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Response lecture ✔
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Small group session ✔
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|
|
|
|
Empirical Assignment ✔
|
|
|
|
Period 2 Credits 3,00
| Evaluation method | |
|
| Written evaluaton during teaching periode | 20 % |
|
| Other | Empirical assignments |
|
|
|
|
|
|
Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
| Explanation (English) | Second reset exam is written and closed book and counts for the entire (100%) final grade. |
|
|
|
|
|
| Compulsory textbooks (bookshop) |
| |
[Empirical Methods for Finance and Banking],[Robert Sollis],[1st],[Wiley],[9780470512890],[] |
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| Master Business Economics - minor Accountancy and Finance - Finance track | Compulsory | 81 | 3,0 | 81 | 3,0 | Yes | Yes | Numerical | |
|
| | | Learning outcomes |
- EC
| The holder of the degree applies acquired knowledge independently. (Self-direction and entrepreneurial spirit)
| - EC
| The holder of the degree communicates clearly and correctly in writing and orally, in a business and academic context, if necessary supplemented with visual support. (Communication) | - EC
| The holder of the degree shows autonomy in implementing scientific research methods. (Research skills) | - EC
| The holder of the degree shows autonomy in analysing, interpreting, evaluating and reporting research results. (Research skills) | - EC
| The holder of the degree is able to apply in-depth insights and argumentation methods from business science and relevant supporting and/or related disciplines in solving strategic policy issues. (Problem-solving capacity) |
|
| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
|
|
The student is interested in mathematics and statistics/econometrics in a macroeconomic and financial context.
The student knows the basic principles of estimating a linear regression analysis in a multivariate setting.
The students is able to formulate and estimate a regression model. We note that these principles are taught in any basic econometric course.
The use of any software package using econometric tools is required. The course will use STATA as a software package but prior knowledge of STATA is not a minimum requirement for the competence.
The student is able to gain financial insights in data interpretation.
|
|
|
|
The structure of the course entails a theoretical part whereby empirical methods are explained using financial applications as well as an empirical part whereby students work on computer applications using statistical software (STATA). In addition, some pratical assignments will also be organized. The following topics will be discussed:
*Regression and volatility
*forecasting techniques (Direct forecasting models, (G)ARCH modellen)
*Portfolio theory of Markowitz with an empirical application
*Capital Asset Pricing Model (CAPM)
*Efficient Market Hypothesis
*Exchange rate forecasting
|
|
|
|
|
|
|
|
|
Lecture ✔
|
|
|
|
Response lecture ✔
|
|
|
|
Small group session ✔
|
|
|
|
|
|
|
|
Empirical Assignment ✔
|
|
|
|
Period 2 Credits 3,00
| Evaluation method | |
|
| Written evaluaton during teaching periode | 20 % |
|
| Other | Empirical assignments |
|
|
|
|
|
|
Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
| Explanation (English) | Second reset exam is written and closed book and counts for the entire (100%) final grade. |
|
|
|
|
|
| Compulsory textbooks (bookshop) |
| |
[Empirical Methods for Finance and Banking],[Robert Sollis],[1st],[Wiley],[9780470512890],[] |
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|
|
|
| Exchange Programme Business Economics | Optional | 81 | 3,0 | 81 | 3,0 | Yes | Yes | Numerical | |
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| |
|
|
The student is interested in mathematics and statistics/econometrics in a macroeconomic and financial context.
The student knows the basic principles of estimating a linear regression analysis in a multivariate setting.
The students is able to formulate and estimate a regression model. We note that these principles are taught in any basic econometric course.
The use of any software package using econometric tools is required. The course will use STATA as a software package but prior knowledge of STATA is not a minimum requirement for the competence.
The student is able to gain financial insights in data interpretation.
|
|
|
|
The structure of the course entails a theoretical part whereby empirical methods are explained using financial applications as well as an empirical part whereby students work on computer applications using statistical software (STATA). In addition, some pratical assignments will also be organized. The following topics will be discussed:
*Regression and volatility
*forecasting techniques (Direct forecasting models, (G)ARCH modellen)
*Portfolio theory of Markowitz with an empirical application
*Capital Asset Pricing Model (CAPM)
*Efficient Market Hypothesis
*Exchange rate forecasting
|
|
|
|
|
|
|
|
|
Lecture ✔
|
|
|
|
Response lecture ✔
|
|
|
|
Small group session ✔
|
|
|
|
|
|
|
|
Empirical Assignment ✔
|
|
|
|
Period 2 Credits 3,00
| Evaluation method | |
|
| Written evaluaton during teaching periode | 20 % |
|
| Other | Empirical assignments |
|
|
|
|
|
|
Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
| Explanation (English) | Second reset exam is written and closed book and counts for the entire (100%) final grade. |
|
|
|
|
|
| Compulsory textbooks (bookshop) |
| |
[Empirical Methods for Finance and Banking],[Robert Sollis],[1st],[Wiley],[9780470512890],[] |
|
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|
|
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1 Education, Examination and Legal Position Regulations art.12.2, section 2. |
| 2 Education, Examination and Legal Position Regulations art.16.9, section 2. |
3 Education, Examination and Legal Position Regulations art.15.1, section 3.
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| Legend |
| SBU : course load | SP : ECTS | N : Dutch | E : English |
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