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Chapter 6. Mean-Variance Portfolio Theory || Part 2 본문
6.2 Random Variables
Random Returns
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Frequently the amount of money to be obtained when selling an asset is uncertain at the time of purchase
- In that case, return is random and can be described in probabilistic terms
Random Variable
Expected Value
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Expected value of a random variable x is the average value obtained by regarding the probabilities as frequencies
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Terms mean or mean value are often used for the expected value
Variance
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Measure of the degree of possible deviation from the mean
Standard Deviation
- We frequently use the square root of the varianceàStandard deviation
Independent variables : Outcome probabilities for one variable do not depend on the outcome of the other
Covariance
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When considering two or more random variables, their mutual dependence can be summarized conveniently by their covariance
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Covariance can also be expressed as
Variance of a Sum
6.4 Portfolio Mean and Variance
Mean Return of a Portfolio
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Rate of return of the portfolio in terms of the return of the individual returns is
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We can take the expected value of both sides to get (using linearity)
- Expected rate of return of the portfolio is found by taking the weighted sum of the individual expected rate of returns
Variance of Portfolio Return
- Variance of the rate of return of a portfolio can be found by performing a straight forward calculation
만약 2개가 아니고 3개라면
Diversification
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Portfolios with only a few assets may be subject to a high degree of risk, represented by a relatively large variance
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Risk of the return of a portfolio can be reduced by including additional assets in the portfolioe => Diversification
- Effect of diversification can be explained by the mean-variance framework
- >> By using variance for measuring risk
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In general, diversification may reduce the overall expected return while reducing the variance
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Diversification is not desirable without an understanding of its influence on both the mean and variance of return
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Mean-variance approach helps understand the trade-off between mean and variance