Lecture 5

Lecture 5
Financial Management

Investment decisions

Agenda
- Investment decisions under uncertainty
- Toolbox: Bayes Theorem and Decision Trees
- Multi-attributive investment planning
- Risk preferences and behavioral aspects

Discounting – options
- Stage 1: investment y/n
- Stage 2: selling equipment if cash flow is low y/n
- We assume that the decision-maker is risk-neutral and focus on expected payoffs

Analytical tool: decision tree




The value of information
- Initial assumption: cash flow is uncertain (50% high, 50% low)
- Suppose we can do a market research for the new services to forecast whether
demand and the cash flow will be high or low
- We ‘update’ our initial assumptions
- Shall we do it and how much would we pay for it?

Use of decision tress
- Quality of market analysis can be measured by the ‘likelihoods’, i.e. a measure of
forecast quality (1)
- Be aware: in terms of probabilities, our intuition may be misleading
- What we have: the probability that the forest reports ‘high cash flow’ conditional on
the fact that the cash flow is high
- But we need: the probability that the cash flow is high conditional on the fact that
the forecast reports ‘high cash flow’.  use Bayes Theorem to transform.. (2)


1

, - (1)




- (2)




Main takeways so far:
- Decision making under uncertainty: context and risk preferences matter!
- Decision trees are a valuable tool for multi-stage decision analysis; not only in the
context of investment decisions

Multi-attributive investment planning
• „A strategic approach to allocating capital in health care organizations“ (Kleinmuntz
& Kleinmuntz 1999)
• Consideration of multiple non-financial and financial evaluation measures


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