Dynamic Corporate Finance and Investments

Students who register for this course should have followed the graduate finance courses "Advanced Corporate Finance”, “Derivatives and Risk Management”, and ”Asset Pricing”. These courses provide a foundation for the present course. 

More specifically, the course requires that the student has prior knowledge of standard corporate finance issues, such as agency costs, debt capacity, liquidity problems, takeovers, and incentive and information problems. These are all competences acquired in the course Advanced Corporate Finance (course no. B560001101).

The student must also be able to explain and apply methods in continuous-time finance such as, for example, the Black-Scholes differential equation, Itô calculus on Itô processes. Numerical solutions may be used, thus some programming skills (e.g. in Excel, Mathematica, Matlab, or R) are expected. These are all competences acquired in the course Derivatives and Risk Management (course no. B560008101).

The student must understand the central elements of pricing derivatives, securities and understand risk premia. These are all competences acquired in the courses Derivatives and Risk Management (course no. B560008101) and Asset Pricing (course no. B560035101).

Guest- and Exchange students may take this course if they have competences similar to the courses: Advanced Corporate Finance, Derivatives and Risk Management, and Asset Pricing.

The course has two main purposes: (1) to prepare students for working with their master’s thesis, and (2) to learn how to make optimal decisions under uncertainty by using advanced real options analysis.

To prepare the students for working with their master’s thesis they will get into reading academic papers and the students with get practical competences by writing reports as well as making presentations in front of an audience and by that they will practice critical thinking.

The second purpose of the course is a foundation for the first purpose by introducing students to advanced methods and topics. Here, the students learn how mastering real options analysis can help to address questions such as: Why do firms postpone positive NPV investments or keep paying interest on debt despite having a deficit? What happens to a firm's equity beta, if the firm merges or invests in a growth option? This course gives the students the methods to analyze such problems. Thus, the course aims to give the students a thorough understanding of modern models of corporate finance and corporate investment problems and their solutions. The course addresses corporate investments, e.g., investments in production facilities and capital budgeting. Other corporate finance issues can also be addressed, e.g., when to take over another company as well as agency problems due to debt financing. The course discusses how modern option concepts and theory can be applied to value investment projects with option features, e.g., flexibility about the timing of the investment and the possibility to shut down (temporarily or permanently) the project after its initial implementation. Finally, the course presents modern multi-period and continuous-time models for corporate finance problems, e.g., capital structure decisions in companies, and it discusses implications for e.g., the valuation of stocks, corporate debt, valuation of corporate bonds and credit risk, and agency conflicts. The analysis of the topics involves analytical and to some extend numerical solutions of the models.

• Critical reflection and presentation of academic literature.
• Decision-making in multi-period (e.g., continuous-time) models in an uncertain environment
• Understand how real options are present in a specific problem and recognize real options in real life examples.
• Dynamic programming, contingent claims analysis, and stochastic control
• Valuation of stocks and corporate bonds based on firm fundamentals.
• Optimal real investment decisions for firms – possible examples:
• real options analysis (contingent claims analysis as well as dynamic programming)
• valuation of investment project
• capital budgeting.
• entry, exit, lay-up, scrapping.
• sequential investments
• investment timing and liquidity
• investment timing and effects of risk or uncertainty

• Examples of expected topics applying the above framework:
• Dynamic capital structure problems, e.g., structural valuation of stocks and corporate bonds and links to credit risk when the firm can actively change its capital structure.
• Dynamic corporate investments problems, e.g., corporate investments and stock returns.
• Corporate decision making in a dynamic setting, e.g., asymmetric information problems and takeovers, or implications of macroeconomic risk. 

Demonstrate knowledge about the course’s focus areas enabling the student to: 

• Explain the idea of dynamic programming, contingent claims analysis, and the derivation of the Bellman equation in discrete-time models and the Hamilton-Jacobi-Bellman equation in continuous-time models of typical financial optimization problems.
• Describe the principles of real options analysis; including describing the Hamilton-Jacobi-Bellman equation in continuous-time models of typical binary decision problems used in e.g. capital budgeting problems.
• Describe and explain applications of real options analysis, e.g. in a dynamic corporate investment context; discuss and criticize the assumptions made for the applications and interpret the results.
• Explain the difference between contingent claims analysis and dynamic programming.

Demonstrate skills, such that the student is able to:

• Discuss and criticize the assumptions made for the applications and interpretation of the results.
• Reflect upon the conclusions obtained by the analysis in the different applications.
• Apply the Hamilton-Jacobi-Bellman equation and extensions in continuous-time models of typical financial optimization problems.
• Analyze and criticize the principles of real options analysis; including describing and analyzing the Hamilton-Jacobi-Bellman equation in continuous-time models of typical binary decision problems used in e.g. capital budgeting optimization problems.
• Analyze applications of real options analysis, e.g. adjustment of a firm's assets, and valuation of stock and corporate bonds in a dynamic corporate investment context; discuss and criticize the assumptions made for the applications and interpret the results.
• Analyze e.g. equity as a contingent claim with a real options analysis view.
• Evaluate and analyze consequences of agency conflicts, e.g. due to conflicting incentives regarding the decision to the investment decision, when to acquire another company etc.
• Implement standard dynamic models and some extensions numerically.
• Analyze applications of real options analysis in a dynamic corporate finance context.
• Recognize and identify embedded real options in practical applications as well as in an abstract sense.

Demonstrate competences, such that the student is able to:

• Apply the principles of real options analysis -- including modifying the Hamilton-Jacobi-Bellman equation of typical binary decision problems – to independently develop models applicable for analyzing new topics.
• Understand when to use contingent claims analysis and dynamic programming in a given context and use that to independently identify a need for further development.
• Independently apply applications of real options analysis in a dynamic corporate finance context to take on professional responsibility regarding strategic decision making under uncertainty.
• Use the above knowledge and skills to participate in team work and to present the outcome of an analysis; i.e., the student obtains competences in collaboration, communication, and presentation. 

Examples:

• Flor, C. R. “Dynamic Corporate Finance Theory”, Lecture notes, University of Southern Denmark, newest edition, or similar material.
  
• Chapters from Dixit, A. K. and R. S. Pindyck. “Investment under Uncertainty”, Princeton University Press, 1994, or similar material.
• Articles (papers and working papers) and additional lecture notes.
• Cases. 

The course is designed as a study group.

Scheduled classes

2 times (in 2x45 minute sessions) per week for approximately the first five weeks

Workload:

The study group activities result in an estimated distribution of the work effort of an average student as follows:

• Preparation of introduction package: 10 hours.
• Lectures/class work/case work/discussions/case presentation: 185 hours.
• Catching up, reflect on material, prepare for take home: 50 hours.
• Exam/take home 1: 25 hours.

Total: 270 hours

This corresponds to an average weekly workload of 13 hours during the semester, including the exam.

At most 25% of the lectures will be held online. The specific distribution between attendance lectures and online lectures will be done subject to didactic and pedagogical aspects. To provide the possibility of making replacement lectures due to cancelled lectures may, however, imply that the realized share of online lectures exceeds 25%.