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
2
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
2
