ØABED3002 Corporate Finance Emneplan

We start the course with an introduction to basic theoretical elements needed to understand investment decision rules, corporate policy decisions, and capital budgeting/valuation. Then, we move forward to the topic of investment under uncertainty, which provides the main theoretical and methodological insights on portfolio selection, the capital asset pricing model (CAPM model), and the cost of capital. The topic of capital structure builds on the cost of capital to provide the understanding of optimal corporate policy decisions, in regards to capital structure, investment, and payout policy under the perfect capital markets assumption and in the presence of market imperfections (e.g., corporate tax rate, distress or bankruptcy costs). We also cover the interlinkages with operating decisions and other investment decisions of the firm by developing the intuition on working capital management and risk management. The last topic draws on all of the above to cover valuation with leverage and capital budgeting. This last topic provides the grounds for the ØABED3700 "Valuation" course.

Language of instruction is English.

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Det benyttes intern og ekstern sensor til sensurering av besvarelsene.

Et uttrekk på minst 25 % av besvarelsene sensureres av to sensorer. Karakterene på disse samsensurerte besvarelsene skal danne grunnlag for å fastsette nivå på resten av besvarelsene.

Fredrik Wulfsberg

• Økonomisk aktivitet og inflasjon
• Pengepolitikk
• Finanspolitikk
• Åpne økonomier, valutakurs
• Konjunkturer
• Institusjoner
• Finansmarkeder

The course builds on a course in social science research methods at bachelor's degree level and a foundation course in statistical methodology. The course provides in-depth knowledge of key quantitative analysis methods in economics and social science.

The course covers the following topics: the research proces (use of models, forms of validity, causality, reporting and presentation), quantitative data (different data sources: experiment, survey, naturally occurring data and register data; multi-item measures: formative and reflective measurement models), data analyses (multippel regression analysis (OLS), logistic regression analysis, multilevel analysis, factor analysis, reliability analysis).

Through a series of exercises, students develop their skills in practical use of quantitative data. Knowledge of spreadsheets (such as Excel) or statistical software (like SPSS, Jamovi, Stata or R) is an advantage.

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After completing the course, the student should have the following overall learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

The student

• in-depth knowledge of relevant analysis methods
• insight into the use of quantitative data in academic work and professional life
• an understanding of how models are used in social sciences
• an understanding of the importance of relating the research question, context and data to the choice of method

Skills

The student is capable of

• analyzing quantitative data to answer research questions
• relating research questions, context and data to the choice of method
• planning own quantitative research and assess the results of others

General competence

The student can

• assess relevant issues related to quantitative research methods
• apply knowledge and skills in obtaining and analyzing relevant data sources
• interpret and communicate results from quantitative empirical investigations
• communicate about quantitative issues with specialists and to the general public

The following coursework requirements must have been approved in order for the student to take the exam:

• Coursework: Three written assignments with a scope of 4-7 pages each. The assignments are distributed throughout the semester. Each coursework requirement involves carrying out and interpreting quantitative analyses in line with topics discussed at the lectures. The coursework requirements must be submitted in groups of 3-4 participants.

The aim of the coursework requirements is to practice doing one's own data analyses and interpret the results of these to answer a research question.

All required coursework must be completed and approved by the given deadline in order for the student to take the exam. If one or more coursework requirements have not been approved, the student will be given one opportunity to submit an improved version by the given deadline.