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Unformatted text preview: The method is named after a 1990 Nobel Prize recipient, a
financial theorist, who first introduced the technique in his 1952 paper entitled
Portfolio Selection. Markowitz diversification is less intuitive than simple diversification and uses analytical portfolio techniques to maximise portfolio returns
for a particular level of risk. This approach also incorporates the fact that assets with 106 low correlation to each other when combined have a much lower risk relative to their
return (Whiteside, 1997).
Using these principles, portfolio optimisation is a methodology from finance theory
for determining the investment program and asset weightings that give the maximum
expected value for a given level of risk or the minimum level of risk for a given
expected value. This is achieved by varying the level of investment in the available
set of assets. The efficient frontier is a line that plots the portfolio, or asset mix,
which gives the maximum return for a given level of risk for the available set of
assets. Portfolios that do not lie in the efficient frontier are inefficient in that for the
level of risk they exhibit there is a feasible combination of assets that result in a
higher expected value and another which gives the same return at lower risk. (Note,
in reality, due to real world constraints such as the indivisibility of assets, trading
costs and the dynamic nature of the world, all practical portfolios are inefficient).
To calculate the efficient frontier it is imperative to determine the mean return of each
asset (usually the EMV in industrial applications), the variance of this value (defined
as risk in finance theory) and each asset’s correlation to the other assets in the
available set of investments (Whiteside, 1997). This classification of risk assumes
that:
• Firms’ long run returns are normally distributed and can, consequently, be
adequately defined in terms of the mean and variance. In reality, it is likely that
the distribution describing long run returns would be “skewed”. • Variance is a useful measure of risk. In calculating variance, positive and negative deviations from the mean are equally weighted. In fact, decisionmakers
are often more preoccupied with downside risk – the risk of failure. A solution to
this problem is to determine the efficient set of portfolios by using another risk
measure. A group of suitable risk measures that only takes the dispersions below
a certain target into account are the downside risk measures. In the mean downside risk investment models the variance is replaced by a downside risk
measure then only outcomes below a certain point contribute to risk. 107 • There is enough information to estimate the mean and variance of the distribution
of outcomes. This does require a high level of information that, in some cases, is
not available (Ross, 1997). However, provided that the assumption that variance is a useful approximation of risk
is accepted, the aim is to maximise the expected return under a c...
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 Summer '14
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