NO.PZ2022122801000022
问题如下：
Rohan Roggen is the founder
of a successful business in Europe. Roggen also created the Roggen Family
Charitable Foundation (RFCF) to fund projects in perpetuity that will provide clean
drinking water in developing countries.
RFCF’s current
portfolio is valued at EUR 250 million, with 50% in equities and 50% in fixed income.
The portfolio’s equity holdings are in a fund tracking a broad index of EUR-denominated
stocks; the fixed-income holdings are in a fund tracking an all-maturity index of
EUR- denominated government bonds. Roggen rebalances the foundation’s portfolio
every six months.
Roggen hires
Michaela Loucks, an investment consultant, to advise on RFCF’s asset allocation
and investments. Roggen explains that he wants the foundation to achieve the
following objectives:
Spend at least 3% of the fund’s
beginning value on projects each year in order to satisfy a legal requirement.
As part of this annual distribution, spend at least EUR 5 million
(inflation-adjusted) each year on projects in emerging countries in Europe.
Minimize the likelihood of a decline in the portfolio’s value of
more than 10% in any single year.
Loucks also
evaluates available methods for determining the target asset class weights in
the IPS. She decides to use a Monte Carlo simulation rather than single-period
mean-variance optimization (MVO) to establish these target weights. She
determines that RFCF has an above-average risk tolerance.
D.
Support, with two reasons, Loucks’ choice of Monte Carlo simulation, rather
than MVO, to determine RFCF’s target asset class weights.
选项：
解释：
Loucks’ use of
Monte Carlo simulation for determining RFCF’s target asset allocation weights
is more appropriate than MVO because of the following:
The foundation is expected to
operate in perpetuity, so it has a multi-period framework. Monte Carlo simulation
is able to incorporate the effect of changes to variables over time. In this
case, Loucks can demonstrate how various spending policies could affect the
portfolio’s value and ability to grow in real terms. MVO is a single-period
framework, so as an example, it cannot be used to evaluate the likelihood of the
foundation dropping below the EUR 5 million (real) desired spending level in
the future.
Roggen currently rebalances the
portfolio every six months. Monte Carlo analysis allows Loucks to analyze different
rebalancing policies and their costs over time. In a single-period setting,
such as that assumed by MVO, rebalancing is not taken into account.
As there are cash flows out of
the portfolio each year, terminal wealth (or the portfolio’s value at a given point
in the future) will be path-dependent. Withdrawing 3% of the portfolio’s
beginning balance (or EUR 5 million) during a period of low asset prices will
be more harmful than if the outflow occurs during a bull market. Similarly,
Monte Carlo simulation addresses the sequencing issues in looking at returns.
For example, it adjusts for the potential of large losses in early years.
Monte Carlo can incorporate
statistical properties outside the normal distribution, such as skewness and excess
kurtosis, in the distribution of the equity portion of RFCF’s portfolio. It can
also be incorporated in alternative investments (such as private equity, real
estate, and commodities), which RFCF is considering adding to the portfolio.
a) Monte Carlo simulation takes factors such as multiple periods into consideration when rebalancing portfolio while MVO does not. Because RFCF rebalances the portfolio every six months, Monte Carlo simulation should be more appropriate.
b) Monte Carlo simulation can solve the problem of path dependency. Because Roggen wants the foundation to spend at least 3% of the fund's beginning value and at least EUR 5 million on legal requirement and projects in emerging countries each year, the large amount of cash outflow will negatively impact the terminal value of the portfolio, resulting in the problem of path dependency. Thus, Monte Carlo simulation is a better choice.
