Course Outline

1.2 PRINCIPLES OF FINANCIAL DECISION-MAKING

(Session 1, Course 2)

Jaap Spronk, professor of finance, EUR

Winfried G. Hallerbach, associate professor of finance, EUR

spronk@few.eur.nl,hallerbach@few.eur.nl

http://www.finance-on-eur.nl

1. Introduction

This course consists of eight sessions of each three hours. Students are also expected to spend an equivalent amount of time individually studying the literature and in groups preparing assignments and cases.

The main objective of the course Principles of Financial Decision-Making in Session 1 is to provide a consistent framework for applied financial decision-making. This framework integrates available financial theory and decision technologies. The motivation of the need for integration is twofold:

Starting from the distinction between conditional-normative models on the one hand and descriptive models on the other, we observe that financial theory largely focuses on the latter. However, since descriptive models are built on “representative” decision-makers, this questions the relevance of decision rules distilled from descriptive models. Hence we need to direct the focus on non-average decision-makers and investigate the potential contribution of financial theory to financial decision-making in practice.

Decision technology provides a decision-maker with a large toolbox, offering a wide selection of techniques. However, many efforts in this direction are tool-oriented and not problem-oriented. Consequently they tend to ignore the peculiarities of the decision context and fail to incorporate useful principles and insights offered by financial economic theory. In addition, many techniques are optimum-oriented in that they provide ?the optimal decision?. This, however, often requires making very strong (and even utopian) assumptions which transform the real decision context into an oversimplified model-context. These assumptions often redefine the particular problem at hand. For example it is assumed that the decision-maker has complete information, and uncertainty is molded in the form of easily tractable probability distributions. For improving financial decision-making in practice it is necessary to recognize the limitations of the available information and to improve the process of learning in order to cope with limited and flawed information.

This framework is built on the principle that assumptions should be made where they help the modeling process the most and hurt the particular decision problem the least. The underlying assumptions must be validated and the effectiveness and efficiency of the actions taken must be evaluated systematically.

The framework consists of the following steps:

1. characterizing different financial decision problems

2. the identification and description of the choice alternatives

3. the modeling of the uncertainty, attached to the outcomes of the alternatives

4. the evaluation of the choice alternatives vis à vis the preferences of the decision-maker at hand.

Through the use of assignments and case studies, students are expected to develop a firm understanding of the problems and challenges of applied financial decision-making.

2. Course details

The course is structured in four parts:

1. What’s the problem?: this part focuses on key areas of financial decision-making, analyzes the characteristics of financial decision problems and confronts this analysis with textbook solutions and the underlying assumptions. The main goal is to structure decision problems. This is a complicated task since there are many reasons to treat financial-economic problems as multiple criteria decision problems (because of multiple actors, multiple policy constraints, multiple sources of risk, etc.).
In an assignment the students are asked to describe the characteristics of a selected financial decision problem in detail.

2. A typology of problem classes: elaborating further on how to structure decision problems it will be argued that financial decision problems can be categorized by using three criteria: [1] the degree of uncertainty involved, [2] the degree of decision flexibility offered (real option aspects), and [3] the degree in which the decision outcome is affected by actions taken by other players in the field (game aspects).
In an assignment the students are asked to analyze selected financial decision problems from this perspective and to classify them according to the criteria mentioned above.

3. Perception: this involves the perception of the decision problem at hand and of the choice alternatives. The goal is to construct an adequate representation of the choice alternatives. Attention will be paid to describing choice alternatives, collecting and structuring of data, processing data into useful information, and handling partial and incomplete information. Special focus will be on the perception and multi-dimensional modeling of uncertainty and the subsequent derivation of probability information.

In an assignment the students are asked to provide a suitable description of the choice alternatives of selected financial decision problems, with a special emphasis on the degree and form of uncertainty.

4. Preferences: this part focuses on describing the decision-maker’s preference structure including goals and restrictions; on deriving this preference information; on shaping preferences with respect to the choice alternatives; and on evaluating the alternatives in relation to the preferences in order to take a decision. Cognitive biases in evaluating choice alternatives are also discussed. In this final step it will become clear that preferences and perceptions are interdependent. This is illustrated with a case in portfolio management.
In an assignment the students are asked to provide a suitable analysis of selected financial decision problems, elaborating on the potential interactions between shaping preferences and perceiving choice alternatives.

Upon completion of the course the students should be able to:

• understand how to structure financial decision processes
• recognize different key types of financial decision problems
• understand the critical role of assumptions in the modeling process
• understand how to collect and structure information under uncertainty
• understand how uncertainty affects all stages of the decision process
• interpret data and to learn from limited (and even flawed) available information
• analyze preferences and goals of decision-makers (either individuals or organizations)
• confront preferences and choice alternatives in order to take a decision
• communicate the decision process and its outcomes amongst decision-makers and to stakeholders

3. Course organization details

Group submissions

Students must form themselves into groups of four (4) and submit the names of their group members at the start of the second lecture. You should ensure that all members of the group are prepared prior to the lectures as students may be selected at random to represent the group.

Requirements for successful completion of the course

Students are expected to actively contribute during their group meetings and lecture sessions. In-class assignments / cases and participation provide the grading for the course. There is no final exam.

4. Course materials

Textbook:

BMA: Brealey, R.A., S.C. Myers & F. Allen, Corporate Finance, McGraw-Hill, New York NY, 8th international edition 2006 (ISBN 0-07-111551-X)

Reader:

In addition to the textbook, the following selected papers and book chapters will be used:

Bazerman, M.H., 2002, Judgment in Managerial Decision Making, John Wiley & sons, NY, chapter 2

Hallerbach, W.G. & J. Spronk, 1997, Financial Modeling: Where to Go? With an Illustration for Portfolio Management, European Journal of Operational Research 99, 1997, pp. 113-125

Hallerbach, W.G. & J. Spronk, 2000, "A Multicriteria Framework for Risk Analysis", in: Y.Y. Haimes & R. Steuer (eds), "Research and Practice in Multiple Criteria Decision Making", Lecture Notes in Economics and Mathematical Systems, Vol. 487, Springer Verlag, Berlin

Hallerbach, W.G. & J. Spronk, 2002a, "The Relevance of Multi-Criteria Decision Making for Financial Decisions?, The Journal of Multicriteria Decision Analysis 11/4-5, pp.187-195

Hallerbach, W.G. & J. Spronk, 2002b, ?A Multidimensional Framework for Financial-Economic Decisions?, The Journal of Multicriteria Decision Analysis 11/3, pp.111-124

Hallerbach, W.G., H. Ning, A. Soppe & J. Spronk, 2003, "A Framework for Managing a Portfolio of Socially Responsible Investments?, European Journal of Operational Research 153/2, pp.517-529

Spronk, J., 1981, Interactive Multiple Goal Programming?, Kluwer, Boston: Multiple goals in capital budgeting and financial planning, pp. 10-29,
A survey of multiple criteria decision methods?, pp. 30-57, and:
Large numbers of goal variables?, pp. 200-205

This material can be downloaded (in *.pdf) from the homepages of the professors and/or will be made available on Blackboard.

Learning aid:

Brealey, R.A., S.C. Myers & F. Allen, Student CD-ROM Accompanying?Corporate Finance, McGraw-Hill, New York NY, 8th int?l edition 2006

On this CD-Rom you will find a wealth of additional material, including quizzes with each chapter (with automatic correction), financial analysis spreadsheet templates and web links.

Case studies, workshop material and assignments:

Will be handed out during class.