Hailey College of Banking & Finance Lahore

Aug 11 - 17, 2008

Whilst it is not necessary to be a qualified accountant or bookkeeper, a basic understanding of what is involved in financial analysis is essential for anyone who wants to invest. It is too enticing, and often too easy, to use "blue skies" thinking and planning investing activities. It is even easier to spend money without fully realizing the return one is getting for it. It is behoven, therefore, on investors, to be more disciplined and analytical in the way they go about planning, executing and evaluating investment plans and strategy. One way of introducing more discipline into the process is by having a basic understanding of the financial implications of decision making, and how such quantitative decisions can be used to monitor and control investments! A quantitative decision, however involves six parts:

a) An objective that can be quantified: Sometimes referred to as 'choice criterion' or 'objective function', e.g. maximization of profit or minimization of total costs.

b) Constraints: Many decision problems have one or more constraints, e.g. limited raw materials, labor, etc. It is therefore common to find an objective that will maximize profits subject to defined constraints.

c) A range of alternative courses of action: For example, in order to minimize costs of a manufacturing operation, the available alternatives may be:

i) To continue manufacturing as at present

ii) To change the manufacturing method

iii) To sub-contract the work to a third party.

d) Forecasting of the incremental costs and benefits of each alternative course of action.

e) Application of the decision criteria or objective function, e.g. the calculation of expected profit or contribution, and the ranking of alternatives.

f) Choice of preferred alternatives. The choices of the investments can be made by considering the projects on the following basis:

i) By project size: Small projects may be approved by departmental managers. More careful analysis and Board of Directors' approval is needed for large projects of, say, half a million dollars or more.

ii) By type of benefit to the firm:

An increase in cash flow

A decrease in risk

An indirect benefit (showers for workers, etc).

iii) By degree of dependence:

Mutually exclusive projects (can execute project A or B, but not both)

Complementary projects: taking project A increases the cash flow of project B.

Substitute projects: taking project A decreases the cash flow of project B.

iv) By degree of statistical dependence:

Positive dependence

Negative dependence

Statistical independence.

Given the uncertainty inherent in investment forecasting and valuation, analysts will wish to assess the sensitivity of investment NPV to the various inputs. In a typical sensitivity analysis the analyst will vary one key factor while holding all other inputs constant, ceteris paribus. The sensitivity of NPV to a change in that factor is then observed (calculated as ? NPV / ? factor). For example, the analyst will set annual revenue growth rates at 5% for "Worst Case", 10% for "Likely Case" and 25% for "Best Case" - and produce three corresponding NPVs.

A further advancement is to construct stochastic or probabilistic financial models - as opposed to the traditional static and deterministic models as above. For this purpose, the most common method is to use Monte Carlo simulation to analyze the project's NPV (introduced to finance by David B. Hertz in 1964). Here, the cash flow components that are (heavily) impacted by uncertainty are simulated, mathematically reflecting their "random characteristics". The simulation produces several thousand trials (in contrast to the scenario approach above) and outputs a histogram of project NPV. The average NPV of the potential investment - as well as its volatility and other sensitivities - is then observed.