Job 2: Expected Income = £1,500 Variance = £ 9,900 5 (£500) = £500įor the second job, the average deviation is calculated as: In the first job, the average deviation is £500:Īverage Deviation =. Table 5.2 gives the deviations of actual incomes from the expected income for the two sales jobs: The variability can be analysed by a measure that presumes that large differences between actual payoffs and the expected payoff, called deviations, signal greater risk. But the variability of the possible payoffs is different for the two jobs. The two jobs have the same expected income because. Table 5.1 summarizes these possibilities: The second job pays £ 1510 most of the time, but would pay £510 in severance pay if the business goes burst. There are two equally likely incomes under the first job - £2,000 for a good sales effort and £1,000 for a moderate effort. Suppose we are choosing between two sales jobs that have the same expected income (£1,500). More generally, if there are two possible outcomes having pay offs X 1 and X 2, and the probabilities of each outcome are given by Pr and Pr 2, then the expected value E(X) is: E (X) = Pr 1X 1 + Pr 1 X 2 …………. The expected value in this case is given by:Įxpected Value = Pr (success) (£40/share) + Pr (failure) (£20/share) Suppose we are considering an investment proposal in an offshore oil company with two possible outcomes: success yields a payoff of £40 per share, while failure yields a payoff of £20 per share. The expected value measures the central tendency. ![]() ![]() The expected value of an uncertain event is a weighted average of the values associated with all possible outcomes, with the probabilities of each outcome used as weights. One measure tells us the expected value and the other variability of the possible outcomes. Whatever be the interpretation of probability, it is used to calculate two important measures that help us describe and compare risky choices. Subjective probability is the perception that an outcome will occur and the perception is based on a person’s judgment or experience, but not on the frequency of outcome observed in the past. Then the probability of success of 1/4 is objective because it is based on the frequency of similar experiences.īut what if there are no similar past experiences to help measure probability? In these cases, objective measures of probability cannot be obtained, and a more subjective measure is needed. Suppose we know from our experience that, of the last 100 offshore oil explorations, 1/4 have succeeded and 3/4 have failed. Objective probability relies on the frequency with which certain events have occurred. Probability could be objective and subjective. ![]() Suppose the probability that the oil exploration project is successful might be 1/4, and the probability that it is unsuccessful 3/4. Probability refers to the likelihood that an outcome will occur. To analyse risk quantitatively, we need to know all possible outcomes of a particular action and the likelihood that each outcome will occur. ![]() In different situations, people must choose the amount of risk they wish to bear. or by investing in additional information. Next, we will see how people can deal with risk or reduce risk - by diversification, by buying insurance, etc. To answer these questions, we must be able to quantify risk so as to be able to compare the riskiness and alternative choices. Is it better to work for a large, stable company where job security is good but the chances of advancement are limited, or to join a new venture, which offers less job security but quicker advancement?
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