48144 - Corporate Finance

Academic Year 2026/2027

  • Teaching Mode: In-person learning (entirely or partially)
  • Campus: Forli
  • Corso: First cycle degree programme (L) in Management and Economics (cod. 5892)

Learning outcomes

The aim of this course is to provide the students with a set of analytical tools and techniques useful to explore the most relevant important investment and financing decisions taken by firms at different stages of their life cycle. At the end of the course students are able to: (a) select the best business investment strategies a firm should undertake; (b) calculate and interpret the company’s cost of capital; (c) identify the main financing sources available to companies.

Course contents

Module I

- The role of corporate finance in corporations

- Maximization of shareholder value as a company goal

- Financial analysis and financial planning

- Principles of mathematical finance

- Evaluation of bonds and shares

- Investment assessment methods

- Risk – return relationship

Module II

- Estimation of the opportunity cost of capital through the Capital Asset Pricing Model

- Financing decisions

- Risk capital financing: Venture capital and IPOs

- Seasoned equity offerings

- Dividend policy

- Adjusted present value

Readings/Bibliography

Module I - Module II: Lecture notes: The notes will be available on the platform “virtuale.unibo.it".

R. Brealey, S. Myers, and F. Allen. Principles of Corporate Finance, McGraw Hill, 2020 (15th Edition). Chapters 1-9, 12-18, 29. As attending the course is not mandatory, there is no difference between attending students and not attending students.

Module I (Program for the first partial exam): Chapters 1-7, 29.

Module II (Program for the second partial exam): Chapters 8-9 and 12-18.

Teaching methods

The course content will be presented and discussed in depth during lectures. Both theoretical and practical sessions will be offered. The practical sessions (four for each module) will focus on solving exercises and applying the concepts covered in class.

Assessment methods

Assessment is based on a written exam.

The midterm exams (the first is usually held at the end of October or the beginning of November, and the second in December) each consist of 11 multiple-choice questions (22 points) and 1 exercise (10 points). Each midterm exam lasts 50 minutes.

Students may take the second midterm exam only if they obtain a minimum score of 14 points on the first midterm exam.

The final exam consists of 22 multiple-choice questions (worth 44 points in total) and 2 exercises (worth 10 points each). Each module includes 11 multiple-choice questions and 1 exercise. The exam lasts 100 minutes. The final score is calculated by dividing the total number of points obtained by 2. 

For both the partial and the final examinations, each correct answer to a multiple-choice question is worth 2 points. There is no penalty for incorrect answers, and only one answer is correct for each question. Each exercise is worth up to 10 points.

The grading scale is as follows:

- 18–23: sufficient knowledge and analytical skills covering a limited range of topics addressed in the course.

- 24–27: adequate knowledge and analytical skills, although with some limitations; good operational skills, albeit not particularly well developed.

- 28–30: very good knowledge of most topics covered in the course; strong operational and critical thinking skills.

- 30 cum laude: excellent and comprehensive knowledge of the topics covered in the course; outstanding critical analysis and ability to make connections across topics.

Students are not allowed to use books, notes, or other course materials during the examination. A list of the most important formulas will be provided as part of the examination paper.

The course is taught during the first semester. The first two examination sessions are normally scheduled during the winter examination period (December–February), while the third session is held in September. The second partial examination and the first final examination are scheduled on the same date.

The use of artificial intelligence (AI) is strictly prohibited during assessments. Any use of AI will be considered a violation of academic integrity.

Teaching tools

Teaching materials and tools include lecture slides, a projector, and the blackboard.

Office hours

See the website of Barbara Petracci

SDGs

Decent work and economic growth

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.