Risk Analysis in Capital Investments 219- Add the two to get the expected value at Decision Point 2
= Rs 1941501 - Calculate expected value at B.
= [(450000 × PVIFA15, 2) + (Expected value at Decision Point 2)] 0.7 + (400000 × PVIFA15,10) 0.13]
= Rs 2473520.70 - Deduct investment of 1.3 m to get NPV
= Rs 1173520 - NPV of building small plant
= Rs 1173520
On comparison, building a smaller plant seems to be a better proposition, as its NPV is higher.STEPS IN DRAWING A DECISION TREE
A decision tree is a presentation of various decisions, possible outcomes and their probabilities at various
stages of a project. The steps involved in drawing a decision tree are:
- Identify decision points and alternative actions available at each point.
- Identify the points of uncertainty and the range of alternative outcomes at each point.
- Estimate the probabilities, costs and benefits of various events and actions.
- Analyze and choose a course of action.
The information about investment requirements, market conditions, etc., may come from many sources like
operations research, market research department, R&D, finance and sales personnel. A cross-functional
team may be entrusted with the task of developing all alternatives and developing them. The team should
identify what alternatives and uncertainties exist now and in the future, estimate costs, demand, prices and
competitive action anticipated under alternatives. It may not be possible to identify all future possibilities,
but we can do a reasonable job of it.
In drawing decision trees, we assumed that the outcome could take on discrete values. In reality, the out-
come may not be discrete but continuous. Second, it might be hard to estimate subjective probabilities for all
the outcomes.
SIMULATION
Since each of the factors that enter into investment analysis is subject to some amount of uncertainty (in
isolation and in combination), Simulation, a method of risk analysis, tries to combine the variability inherent
in each of the factors under consideration and assess the odds of earning a healthy return. Monte Carlo
simulation is a technique in which the uncertainty encompassing the main variable is processed in a forecasting
model in order to estimate the impact of risk on the projected results. The model is subjected to a number of
simulation runs usually with the aid of a computer. Simulation involves the following steps: