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ALLOCATION BASICS
The science of asset allocation is concerned with
determining the most efficient combinations of assets
for a portfolio, in other words, the combinations that
yield the highest return for a given level of risk or
the lowest level of risk for a given level of return.
Most portfolios are not efficient—they yield too little
return for the risk or too much risk for the return.
An endowment portfolio that yields the highest level of
return for the risk an organization is willing to assume
is the optimal portfolio for that organization.
Optimizing the portfolio is the most important decision
endowment managers, trustees, and fiduciaries can make.
An optimal asset allocation can result in higher
endowment returns and more robust endowment growth. An
optimal allocation can also result in less variable
endowment returns thereby providing more reliable
program support and institutional stability. No other
endowment management decision is as important.
To build an optimal endowment portfolio, we start with
three tasks each requiring a set of informed judgments
about the asset categories we are considering for
investment. The Asset Allocation Advisor considers
seventeen asset classes.
First, we make judgments about the likely returns
provided by each class. (View
table of the projected
three-to-five year total returns (pdf) from each asset class).
Commentary explaining the projected returns is available
in the Asset Allocation Advisor. The Advisor does not
just rely on historical returns for future projections
but develops projections based on fundamental analysis
of market conditions and valuations trends for various
asset classes. This analysis is spelled out as
explicitly as possible to allow readers to evaluate the
analyses and to make alternative projections should
their judgment differ significantly on key factors.
Second, we make judgments about the risks associated
with an investment in each class. A
table of the
projected standard deviations of annual returns
(pdf) for each
asset class is available. Commentary regarding risk assessment is
available in the article “Risk” in the
Q4 2006 issue and throughout subsequent issues
of the Advisor.
Third, we make judgments about how the various asset
classes are likely to perform relative to each other.
View a table of the projected correlations of returns
(pdf). Commentary
regarding correlations is available in the article
“Correlation” in the Q4 2006 issue and throughout subsequent issues of the Advisor.
Please note that the current table of projected
correlations has been revised from that in the Q4 2006
issue.
Given a set of expected returns, risks, and
correlations, we can calculate the most efficient
combination of assets for each risk or return level. If
we map the maximum return/minimum risk levels achievable
by various asset combinations, we get the following
picture:
The red line is the efficient frontier. It represents
the maximum return/minimum risk levels that can be
achieved with any combination of assets. It is
impossible to achieve return and risk levels above the
line no matter how we combine assets. The arrow on the
chart points to the location along the efficient
frontier corresponding to a portfolio with a 15%
standard deviation of annual returns. The maximum
expected return from all portfolios with a 15% standard
deviation is indicated by this point. The maximum
expected return in this case is approximately 11.2% per
year. To achieve a higher expected return, we have to
assume more risk.
Each point along the efficient frontier has a specific
combination of assets corresponding to it – from a
mixture dominated by low risk/low return assets at the
left end of the efficient frontier to a mixture
dominated by high risk/high return assets at the right
end of the efficient frontier.
We are most interested in the portfolio that matches our
organization’s risk tolerance. For how to determine your
organization’s endowment risk tolerance see the article
“Quantifying
Risk Tolerance: Part 1” from the Q1 2007 issue.
Since organizations have different risk tolerances, we
have picked a benchmark portfolio along the efficient
frontier to track over time to see how changing market
conditions, valuations, and expected asset class returns
affect the composition of the portfolio. The benchmark
portfolio is the most efficient one yielding an expected
return of ten percent. The location of this portfolio
along the efficient frontier is marked with a star. As
one can see from its location on the efficient frontier,
this portfolio has an expected risk of more than ten
percent. See the composition of the
Ten Percent Portfolios – one including venture capital and
one without venture capital. The chart above shows the
efficient frontier for portfolios without venture
capital.
Finally, it should be noted that calculating efficient
frontiers and the portfolios along them is not an
elementary task. Although it is possible to do simple
mean-variance optimization with a spreadsheet, more
robust calculations require advanced computational
techniques. In addition, simple mean-variance
optimization has been superseded by a new optimization
methodology, resampled efficiency, that calculates
efficient frontiers over a range of statistically
equivalent sets of assumptions and reduces the extent to
which simple mean-variance optimization results were
critically dependent on assumptions that could easily be
mis-specified. The results reported by the Asset
Allocation Advisor make use of the more advanced
optimization methodologies.
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West Hartford