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2. Statistical measures of standalone risk Remember, the expected value of a probabisity distribution is a statistical measure of the average (mean) value expected to

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2. Statistical measures of standalone risk Remember, the expected value of a probabisity distribution is a statistical measure of the average (mean) value expected to occur during all possible circumstances. To compute an asset's expected retum under a range of possible circumstances (or states of nature), multiply the anticipated return expected to result during each state of nature by its probability of occurrence. Consider the following case: Aaron owns a two-stock portfolio that imvests in Happy Dog Soap Company (HDS) and Black Sheep Broadcasting (BSB). Three-quarters of Aaron's portfollo value consists of HDS's shares, and the balance consists of BSB's shares. Each stock's expected return for the next year will depend on forecasted market conditions. The expected returns from the stocks in different market conditions are detailed in the following table: Calculate expected returns for the individual stocks in Aaron's portfolio as well as the expected rate of return of the entire portiolio over the three possible market conditions next year: - The expected rate of return on Happy Dog Soap's stock over the next year is - The expected rate of return on Black Sheep Broadcasting's stock over the next year is - The expected rate of return on Aaron's portfolio over the next year is The expected returns for Aaron's portfollo were calculated based on three possibie conditions in the market. Such conditions will vary from time to time, and for each condition there will be a specific outcome. These probabilities and outcomes can be represented in the form of a continuous probability distribution graph. For example, the continuous probability distributions of rates of return on stocks for two different companies are shown on the following graph: Based on the graph's information, which of the following statements is true? Company A has a tighter probability distribution. Company B has a tighter probability distribution

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