Applied Financial Instruments

Duration

45h Th

Number of credits

Lecturer

Julien Hambuckers

Coordinator

N...

Language(s) of instruction

English language

Organisation and examination

Teaching in the second semester

Schedule

Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

The 'Applied Financial Instruments' course provides an introduction to theory and empirical methods that play an important role in finance. We cover selected topics in asset pricing (modern portfolio theory, Black-Litterman model, capital asset pricing model, factor models, prospect theory), fundamental analysis (bond pricing, discounted cash flow) and corporate valuation (methods of the comparables, DCF analysis). 
The course is structured in two parts:
Part I: Asset pricing and portfolio analysis  
Part II: Applied tools in corporate finance 
A Part 0 will review fundamental concepts in statistics, like random variable, distribution, and regression model. 
The course consists in a set of lectures where equilibrium and investor's behaviour theories are presented. Their implications, in terms of real-life investment decisions, are then discussed. In the practical sessions, the students rely on these concepts to derive quantitative analysis techniques, implement them in the software R and find a solution to investment decision, portfolio optimization and corporate valuation problems. 

Learning outcomes of the learning unit

The course provides students with an understanding at the fundamental level of main concepts used in finance disciplines such as market finance and corporate finance. Through the exercise sessions, students will develop analytical and modeling skills in finance as well as strengthen their communication skills in English. In particular, students will improve their skills in empirical analysis - competences that will turn out to be crucial not only for group and individual tasks to be delivered throughout their master studies but as well for the empirical work of their master thesis.

This course contributes to the following Intended Learning Outcomes : 
ILO-6: being able to use accounting, mathematical, statistical and IT tools to solve a management problem
ILO-7: being able to conduct research autonomously and methodically to obtain the information needed to solve this problem using a critical approach 
ILO-9 : being able to work within a team 

Prerequisite knowledge and skills

Fundamental knowledge of financial markets, financial mathematics, statistics and programming.
Good understanding of the concepts seen in courses like "Probabilité et inférence statistique" and "Marchés Financiers" are expected
Students who need to acquire the prerequisites for the financial part are invited to read the following chapters:
- Basics in financial markets: working knowledge of key concepts like risk and return as well as of the capital asset pricing model and the asset pricing theory. Please read Chapters 10 to 13 - Ross, Westerfield and Jaffe. 2008. Corporate Finance. New York: McGraw-Hill, 8th edition.
- Accounting statements and cash flows: working knowledge of key financial statements, i.e. income statement, balance sheet and cash flow statement. Please read Chapters 2 and 3 - Ross, Westerfield and Jaffe. 2008. Corporate Finance. New York: McGraw-Hill, 8th edition;
The exercises of the asset pricing part will be conducted with the software R. Several tutorial, as well as access to a datacamp "An introduction to R" will give the students the needed prerequisites for the exercise session.

Planned learning activities and teaching methods

The course is structured along two lectures per week: 3 hours lecture and 2 hours technical tutorial classes.

Mode of delivery (face to face, distance learning, hybrid learning)

Face-to-face course


Additional information:

Lectures (around 20 hours) and exercise sessions (around 25 hours).

Recommended or required readings

Book chapters and scientific articles will be announced during the class.
  

Assessment methods and criteria

Exam(s) in session

January exam session

- In-person

written exam ( multiple-choice questionnaire, open-ended questions )

May-June exam session

- In-person

written exam ( multiple-choice questionnaire, open-ended questions )

August-September exam session

- In-person

written exam ( multiple-choice questionnaire, open-ended questions )

Written work / report

Continuous assessment


Additional information:

The final exam is a computer-based exam, where students are expected to : 
- solve several asset allocation/portfolio optimization/investment decision problems with the help of R,
- explain theoretical concepts and solve exercises similar to the ones seen during the lecture sessions.
The exam counts for 70% of the final grade.
Assignments during the practical session (to be completed per group) will count for 25%. 
Completion of a datacamp counts for 5%.

Work placement(s)

Organizational remarks

Contacts

Prof. Julien Hambuckers
email: jhambuckers[at]uliege.be
 
Teachinig assistant: P. Hübner.
 

Items online