The Standard deviation of the probability distribution of possible net present values under the assumption of perfect correlation of cash flows over time is given as under: The standard deviations of the cash flows for 3 years are: 7,500 or more? Is the standard deviation calculated larger or smaller than it would be under an assumption of independence cash flows over time?Įxpected value of the cash flow for three years is set out as follows: Assuming a normal distribution, what is the probability of the project providing a net present value at zero or less of Rs. Calculate the expected value and standard deviation of the probability distribution of possible net present values. 25,000 and the possible cash flows for the three years are:Īssume a risk free discount rate of 5 per cent. It measures the relative variability of returns. The size difficulty can be eliminated by developing a third measure, the coefficient of variation. Measurement of Risk: Method # 3.Ĭoefficient of Variation as a Relative Measure of Risk: However, a large concern would gladly accept a deviation of only 50,000. For example, the possibility of a year’s return varying by Rs, 50,000 is critically significant to a very small concern. The use of the standard deviation is sometimes criticized when taken by itself as a risk measure because it measures absolute variability of returns and ignores the relative size of an investment’s expected return.Ī measured deviation is important for business enterprise only when compared with central tendency. Thus, proposal B has significantly higher standard deviation, indicating a greater dispersion of possible outcomes. The following illustration will explain the above concepts more clearly:Ī company is seized with the problem of choosing one of the two investment proposals with the following probability distribution of expected cash flows in each of the next three years. Is he very certain, very uncertain or somewhere in between? This degree of uncertainty can be defined and measured in terms of the forecaster’s probability distribution. The question that arises in this connection is how much the forecaster is confident about this outcome. This is the most likely or most probable outcome perceived by the forecaster for the proposal. In capital budgeting, usually the forecast of annual cash flow in one single figure is made. Examples are probabilities associated with the flip of a coin or the roll of a dice. In contrast, objective probability is based on prior experience and the laws of chance and on which there is a general agreement. To do this, we make use of subjective probabilities. Rather we forecast the likelihood of future events that will affect different proposals. In capital budgeting, we are not faced with the problem of measuring relative frequency of known events. Probabilities normally are stated as decimal fractions normalized to 1.0 but they can also be expressed in percentage terms as in Table 20.1. The probability that a particular event will occur is a measure of its likelihood of occurrence.
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