GARRISON | SERA | CRIBBS
Contributions
A Simple Dynamic Strategy for
Portfolios Taking Withdrawals: The
Case for Using a 12-Month Simple
Moving Average
by Michael M. Garrison, CFP®; Carlos M. Sera; and Jeffrey G. Cribbs, CFP®
Michael M. Garrison, CFP®, is a principal at Chicago
Wealth Management Inc. and a portfolio manager of the
Executive Summary
CWM Fund LP. He holds a finance degree from Indiana
University’s Kelley School of Business.
Carlos M. Sera is a managing principal at Chicago Wealth
Management Inc. and a portfolio manager of the CWM Fund
LP. He holds an undergraduate degree from Johns Hopkins
University and an MBA from the University of Rochester.
Jeffrey G. Cribbs, CFP®, is a managing principal at Chicago
Wealth Management Inc. and a portfolio manager of the
CWM Fund LP. He holds an undergraduate degree from
Johns Hopkins University and an MBA from Carnegie
Mellon University.
T
he life of an investor can typically
be broken up into two distinct
phases: the accumulation phase
and the withdrawal phase. For individuals,
the withdrawal period typically starts at
retirement or soon after. For institutions,
there is no phase distinction, because withdrawals are an ongoing concern.
While investing for accumulation has
been studied for years, withdrawal planning is a relatively recent topic. With a
large number of investors worried about
how much they can withdraw from a portfolio without running out of money, maximizing this initial withdrawal rate has been
the subject of much new research.
In the last few years, the first wave of
baby boomers has started to retire. Unfortunately for them, their retirement has coinwww.FPAjournal.org
• This paper examines the long-term
effects of using a dynamic investment
strategy based on a 12-month simple
moving average for portfolios in both
the accumulation and withdrawal
phases. It compares the results of this
dynamic strategy to standard static
portfolio allocations based on Modern
Portfolio Theory to determine
whether such a strategy is optimal.
• We created six portfolios using historical data (1926–2008) from two asset
classes: U.S. large-cap equities and U.S.
intermediate-term government bonds.
The six portfolios were examined for
3, 4, 5, 6, and 7 percent withdrawal
rates over 30- and 40-year annual
rolling periods from 1927–2008.
• For the first year, we took the beginning portfolio value and subtracted the
first year withdrawal, then added its
return for the year. For each subsequent year we adjusted the withdrawal
for inflation. All withdrawals occurred
cided with a more than 50 percent drop in
the S&P 500 from November 1, 2007,
through February 28, 2009 (based on
month-end data). In addition, over the last
83 years, the 10-year period ending in 2008
at the beginning of the year.
• During the withdrawal phase, the
dynamic portfolio produced the highest
initial safe withdrawal rate, greatest probability of success across all withdrawal
rates, and consistently highest terminal
values compared to the static portfolios.
• The differences in terminal values were
considerable.
• For long-term investing periods (more
than 10 years), the dynamic portfolio
earned comparable rates of return to
a 100 percent equity portfolio with
less risk, as measured by maximum
drawdown. As the investing period
increased, the dynamic portfolio
tended to outperform the 100 percent
equity portfolio.
• This paper concludes that a dynamic
asset allocation using a 12-month
simple moving average is a consistently
better strategy over statically allocated
portfolios for investors in both the
accumulation and withdrawal phases.
was the worst 10-year rolling annual period
for the S&P 500, with a cumulative return
of –13 percent. Notwithstanding the direct
effect of losses on their portfolios, many
investors cannot psychologically stand
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GARRISON | SERA | CRIBBS
these losses and make poor timing decisions, leading to potentially lower returns.
Financial advisers, investment consultants, and institutional portfolio money
managers have started to really focus on
withdrawals and the question asked by
many investors: How much can I safely
take? Our investment advice and strategies
are one of the primary reasons we are
hired in the first place. Ideally, the investment and withdrawal strategies we develop
will provide our clients with the ability to
live comfortably in retirement and afford
them peace of mind.
Market losses have different consequences in the accumulation and withdrawal periods. In the accumulation phase,
market losses can be mitigated by longer
investing time horizons, as long as these
losses do not cause an investor to abandon
an effective long-term strategy. However,
in the distribution phase, market losses
can be devastating. As William Bengen
pointed out in his article “Determining
Withdrawal Rates Using Historical Data”
(1994), basing a withdrawal rate on a portfolio’s historical average rate of return
instead of looking at the actual order of
historical returns can inflate the safe withdrawal percentage to the investor’s detriment. An initial period of negative returns
coupled with high inflation is likely to
cause a portfolio withdrawal strategy based
on averages to run out of money much
sooner than one based on the historical
order of returns. Investors in the withdrawal phase should keep this in mind
when developing a withdrawal strategy.
To date, the majority of research on withdrawals has focused on two areas: the optimization of static asset-class allocations to
improve a sustainable withdrawal rate and
the incorporation of withdrawal decision
rules based on either portfolio performance
or market indicators. These are two of the
three obvious approaches that may improve
the withdrawal rate. The three are:
1. Improve the asset allocation strategy
by incorporating additional asset
classes and/or optimizing portfolio
weightings
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2. Improve the withdrawal strategy by
setting up distribution rules for the
investor to follow during the withdrawal phase
3. Improve the asset allocation strategy
by using a dynamic investment
approach based on a formula or technical market indicators
Investment research has shown that for
the S&P 500, using a simple moving average methodology can produce comparable
returns to a buy-and-hold strategy with
lower maximum losses (Faber 2007).
Given the effect large losses have on portfolios in the withdrawal phase, would an
investment strategy mitigating these losses
be beneficial during the distribution period?
The purpose of this paper is to introduce
a dynamic asset allocation strategy using a
simple moving average system as an alternative to the static investment approach
for both the withdrawal and accumulation
phases of an investor’s life. The simple
moving average system is explained in
detail later in this paper.
Classic Research
The pioneer of withdrawal rate research is
William Bengen. As noted above, his article “Determining Withdrawal Rates Using
Historical Data” examined asset allocation
strategies based on actual historical
returns, not averages. His article sheds
light on the fact that the order of returns is
a very important component for determining whether a withdrawal rate is sustainable. Using average returns can inflate the
actual initial safe withdrawal rate, leading
an investor to run out of money. He found
a withdrawal rate of approximately 4 percent, increased subsequently by inflation,
would be appropriate for most retirees. If
they keep equity allocations between 50
percent and 75 percent, there is little fear
of running out of money.
Asset Allocation Improvement.
In additional research, Bengen (1997)
determined that adding small-cap U.S. equities to a portfolio experiencing withdrawals
was beneficial, increasing the safe with-
drawal rate from 4.1 percent to 4.3 percent
for portfolios in the distribution phase. The
question of whether international equities
improved portfolios in the distribution
period was addressed by Cooley, Hubbard,
and Walz (2003), who found that “retirees
who prefer portfolios of at least 50 percent
equities benefit modestly from including
EAFE stocks as 25 percent of the market
value of their portfolios.”
Withdrawal Strategies. Adding to
Bengen’s withdrawal rate findings, research
by Guyton (2004) and by Guyton and
Klinger (2006) focuses on enhanced withdrawal strategies. They implemented a
series of decision rules based on factors
such as portfolio value, portfolio returns,
and inflation. Using their guidelines, they
have been able to increase the initial safe
withdrawal rate. However, we find some of
their rules to be potentially restrictive and
wonder if clients would be willing (or able)
to receive lower distributions during bad
market periods. We also question the
effects of adding even more withdrawal
decision rules. Is it realistic to assume
these would be followed?
Kitces’s 2008 paper looks at macroeconomic factors such as current market P/E
ratios to determine the safe withdrawal
rate for a recent retiree. It’s our hope that
after a huge drop in the market—resulting
in a low P/E ratio and suggesting a higher
initial withdrawal rate—a new retiree or
the retiree’s financial adviser would feel
comfortable with some of the withdrawal
rates suggested, but we’re concerned that
this may be hard to achieve because of the
psychological impact that a market drop,
and the resulting loss in portfolio value,
has on an investor.
Dynamic Allocation Research.
Blanchett’s article on glide paths (2007)
presents four dynamic allocation
approaches with different starting equity
and bond percentages. He concluded that a
static 60 percent equity and 40 percent
bond allocation is appropriate for most
retirees. However, his dynamic approaches
are not based on market conditions or
technical indicators.
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GARRISON | SERA | CRIBBS
The Portfolios
Using month-end historical return data from
the Ibbotson SBBI 2009 Classic Yearbook starting in 1926, we examined six portfolios:
• 0/100 portfolio: The portfolio is allocated 100 percent to U.S. intermediate-term government bonds.
• 40/60 portfolio: 40 percent allocated
to U.S. large-cap equities and 60 percent allocated to U.S. intermediateterm government bonds. The portfolio
is rebalanced annually on January 1.
• 60/40 portfolio: 60 percent allocated
to U.S. large-cap equities and 40 percent allocated to U.S. intermediateterm government bonds. The portfolio
is rebalanced annually on January 1.
• 80/20 portfolio: 80 percent allocated
to U.S. large-cap equities and 20 percent allocated to U.S. intermediateterm government bonds. The portfolio
is rebalanced annually on January 1.
• 100/0 portfolio: The portfolio is allocated 100 percent to U.S. large-cap
equities.
• 12-month simple moving average
(SMA) portfolio: The portfolio is allocated 100 percent to U.S. large-cap
equities in every monthly period in
which the last month’s ending price is
above the average price for U.S. largecap equities for the previous 12
months, based on month-end prices.
For example, if the closing price of
U.S. large-cap equities on January 31,
2000, is 100, and the average monthend price for the period February 1,
1999, through January 31, 2000, is 98,
then the portfolio would be 100 percent allocated to U.S. large-cap equities for the month of February.
The portfolio is allocated 100 percent to
U.S. intermediate-term government bonds
in every monthly period in which last
month’s ending price is below the average
price of U.S. large-cap equities for the previous 12 months, based on month-end
prices. Continuing the above example, if
the closing price of U.S. large-cap equities
is 100 on February 29, 2000, and the averwww.FPAjournal.org
age month-end price for the period March
1, 1999, through February 29, 2000, is 102,
then the portfolio would be 100 percent
allocated to U.S. intermediate-term government bonds for the month of March.
Methodology
The six portfolios were examined for 3, 4,
5, 6, and 7 percent withdrawal rates over
30- and 40-year annual rolling periods
from 1927–2008. We did not start in the
year 1926 because the 12-month SMA
portfolio needs one year of returns to calculate the 12-month moving average. We
also did not include withdrawal rates of more
than 7 percent, because we have not seen any
credible research showing this is a sustainable withdrawal rate for any portfolio strategy
over a 30-year (or more) time frame.
Our methodology for determining yearend portfolio values, and thus the ability of
a portfolio to survive over a given period, is
similar to that of other researchers in this
area who have focused on distributions.
For the first year, we took the beginning
portfolio value and subtracted the first year
withdrawal, then added its return for the
year. For each subsequent year we adjusted
the withdrawal for inflation. All withdrawals
occurred at the beginning of the year.
As an example, given a $1 million, 100
percent equity portfolio, 15 percent return,
and a 5 percent withdrawal rate, the first
year ending portfolio value is $1,092,500.
($1 million less the 5 percent withdrawal
($50,000) yields $950,000, which is multiplied by the 15 percent return, yielding
$1,092,500.)
No stochastic analysis (for example,
Monte Carlo analysis) was performed. The
order of returns, as it applies to using a
simple moving average system, is very
important. Past returns are the cornerstone
of a moving average system. Faber (2007)
demonstrates that a simple moving average
system picks up trends in the marketplace
and, although it’s not a perfect indicator of
when to be invested in the market (wouldn’t that be nice!), it provides reasonable
signals on which an investor can act. It is
Contributions
implied that market returns may not be
random. There is a growing body of evidence showing an investment’s past performance can somewhat predict future performance relative to other investments.
Dimson, Marsh, and Staunton (2008) have
shown this persistency to occur with individual stocks. If stocks and markets do
have persistency, we wonder how this will
affect the use of Monte Carlo analysis in
the investment management realm.
As this paper was written toward the end
of 2009, we have only included distribution and return information through 2008.
However, the last two signals of the 12month SMA approach were a move to
bonds in February of 2008, returning to
equities in August of 2009. Although not
giving a perfect signal, the 12-month SMA
approach would have avoided the massive
market losses from 2008 through the
beginning of 2009.
Fees and Expenses. We excluded transaction costs and underlying investment
expenses. From 1927 through 2008, there
were a total of 102 signals generated by the
12-month SMA approach (including the
initial trade). This equates to approximately two-and-a-half trades per year
(every signal after the initial trade generates two trades—one in or out of the S&P
500 and one in or out of bonds). In comparison, there were 82 rebalancings
(including the initial allocation) for an
annually rebalanced portfolio over this
same period, creating 2 trades per year.
With the availability of exchange-traded
funds (ETFs) that can be bought and sold
today for less than $20 per trade from
many custodians and brokerage firms, an
investor with a $1 million portfolio would
average less than 1 basis point per year in
transaction costs.
SPY (an ETF for the S&P 500) has an
underlying investment expense ratio of 10
basis points and is very liquid with the
bid/ask spread averaging 1 basis point.
The frequency and low costs of trading
combined with the low ETF expense ratio
make these expenses immaterial.
Management fees will lower the sustainable
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GARRISON | SERA | CRIBBS
distribution rate, decrease the probability
of any given portfolio strategy being successful, and decrease portfolio terminal
values. Clark and Hood (2009) have
shown that decreasing the percentage of
equities in a portfolio has a disproportionately negative effect on the probability of
portfolio success and portfolio terminal
values. Of the portfolios examined, the
12-month SMA portfolio produced the
highest and most consistent returns, and
will be the least-affected portfolio for any
given management fee. While we recognize that management fees will result in
lower outcomes across all portfolios, they
can vary over a broad range based on
investment adviser and account size, thus
they have been excluded.
In line with other research on this topic,
we have excluded the effect of taxes. For
taxable accounts, the SMA approach may
create higher realized gains in some periods, compared to the static portfolios.
However, there are three factors that mitigate the potential taxes of the 12-month
SMA approach versus the static portfolios:
1. The 12-month SMA portfolio has
higher average pretax investment
returns than the other portfolios
(from 1927–2008)
2. All portfolios have tax consequences
when portions of the portfolios are
being sold for distributions
3. There are periods in which the 12month SMA portfolio is 100 percent
invested in stocks and will generate
long-term capital gains, resulting in
lower tax rates than a portfolio with a
fixed income allocation
Withdrawal Phase Analysis
Before we get into our analysis, let’s
address the question of what defines a successful portfolio strategy. We considered
these four questions:
1. What was historically the highest maximum withdrawal rate a portfolio
strategy could experience without running out of money in a given period?
2. Given a withdrawal rate, which portfo54
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lio strategy had the highest probability
of success?
3. In periods during which a portfolio
strategy failed, what was the minimum number of years the portfolio
survived?
4. What was the terminal value of the
portfolio after the withdrawal period
ended?
A portfolio strategy with the highest historical maximum withdrawal rate, the highest probability of success given a withdrawal
rate, the longest minimum number of years
lasted in periods of failure, and the highest
terminal values is considered optimal.
Safe Withdrawal Rate
For purposes of this paper, we define the
safe withdrawal rate as the initial maximum withdrawal rate adjusted annually for
inflation that has historically not run out of
money over a given period. Since life
expectancies are increasing, we look at
both 30- and 40-year periods. It is important to note that unfortunately, safe does
not mean guaranteed. There are many
events that can affect the actual safe withdrawal rate in the future. We do, however,
think the historical safe withdrawal rate is
a reasonable starting point to begin determining distribution rates.
As we can see from Table 1a, our
research for a 60/40 portfolio is in line
with that of others who have researched
the subject, with a withdrawal rate being
historically safe at approximately 4 percent
for the balanced portfolios (40/60, 60/40,
and 80/20). In this analysis, the 60/40
portfolio did not have the highest historically safe withdrawal rate. This distinction
goes to the 12-month SMA portfolio, which
provided the maximum safe withdrawal
rate in both the 30-year (4.37 percent) and
40-year (4.11 percent) periods. Over 30year periods, the 12-month SMA portfolio
allowed for a withdrawal rate 8.4 percent
greater than the 60/40 portfolio, and over
40-year periods, the 12-month SMA portfolio’s withdrawal rate was more than 9.9
percent higher than the 60/40 portfolio.
Although not shown, the 12-month SMA
portfolio also had the highest safe withdrawal rate among portfolios with fixed
income allocations (or the ability to have
fixed income) if we look for the portfolio
that allowed for the highest safe withdrawal rate during any annual 30-year
period.
In the modern era (since 1945), the difference between the 12-month SMA portfolio and the other portfolios is even more
pronounced. Comparing Table 1a to Table
1b, we see the maximum safe withdrawal
rate of all the other portfolios either stayed
the same or increased modestly, while the
safe withdrawal rate for the 12-month SMA
portfolio increased by more than 16 percent
and 18 percent, for 30- and 40-year rolling
periods, respectively.
Although we consider maximum safe
withdrawal rate to be an important consideration to determine a portfolio strategy,
by itself it does not make a portfolio strategy optimal.
Probability of Success
The portfolio success rate is the probability
a portfolio does not run out of money
given the withdrawal rate and time frame.
Table 2a illustrates portfolio success
rates for 30 scenarios based on six different
portfolios and five different withdrawal
rates. The portfolios highlighted in green
are the portfolios that provided the greatest
probability of success given each withdrawal rate. As we can see, all portfolios in
our sample with stock exposure survived a
3 percent withdrawal rate from the period
1927–2008. At 4 percent, the two portfolios with static stock exposure of at least 80
percent were not 100 percent successful.
The 5 percent withdrawal rate is where
Table 2a gets interesting. The 40/60,
60/40, 80/20, and 100/0 portfolios all had
huge drop-offs in success rates, with each
of these portfolios being successful less
than 75 percent of the time. Although its
probability of success did drop, the
dynamic portfolio using a 12-month simple
moving average fell considerably less,
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GARRISON | SERA | CRIBBS
down to only 96 percent. Additionally, as
withdrawal rates increased to 6 percent
and 7 percent, the static portfolios with the
most equity exposure, as well as the 12month SMA portfolio (which has the ability to go to 100 percent equity), were the
most successful. In every historical withdrawal rate scenario, the 12-month SMA
portfolio was dominant.
Analyzing 40-year periods, the 12-month
SMA portfolio again demonstrates it had
the highest probability of success for all
withdrawal rate scenarios. As the period
examined increased from 30 to 40 years,
the 4 percent withdrawal rate was where
the 12-month SMA portfolio starts to differentiate itself, whereas in 30-year periods
this did not manifest until the 5 percent
withdrawal rate. Again, we can see how the
portfolios with the higher percentages in
stocks (or the ability to have a high percentage in stocks) were more successful as
withdrawal rates and time periods
increased, suggesting that investors with
longer time horizons or higher withdrawal
needs should limit bond exposure.
Table
T
able 1a:
Table
T
able 1b:
Safe
Withdrawal
S
afe W
ithdrawal
R
ates 1927–2008,
Rates
A
nnual Rolling 30Annual
and 40-Y
Year P
eriods
40-Year
Periods
Portfolio
0/100
40/60
60/40
80/20
100/0
12-Month SMA
30 Years
40 Years
2.40%
4.03%
4.03%
3.98%
3.77%
4.37%
1.83%
3.56%
3.74%
3.73%
3.62%
4.11%
Portfolio
0/100
40/60
60/40
80/20
100/0
12-Month SMA
0/100
40/60
4
60/40
80/20
100/0
12-Month
12-M
onth SMA
40 Years
2.78%
4.03%
4.03%
3.98%
3.86%
5.07%
2.10%
3.68%
3.74%
3.73%
3.67%
4.85%
Portfolio S
Portfolio
Success
uccess Rates
Rates 1927–2008,
927–2008,, A
Annual
nnual Rolling 30-Year
30-Y
0-Y
Year
ear
Periods
P
eriods
Withdrawal
W
ithdrawal R
Rates
ates
e
Portfolio
P
ortffolio
ol
30 Years
SSource:
ource: Ibb
otson (mon
th-end data)
data)
Ibbotson
(month-end
SSource:
ource:: Ibb
Ibbotson
otson (mon
(month-end
th-end da
data)
ta)
Table
T
able
2a:
a
T
Safe
Safe Withdrawal
Withdrawal
Rates 1945–2008,
Rates
A
nnual Rolling 30Annual
and 40-Y
Year Periods
Periods
40-Year
3%
4%
5%
6%
7%
79%
100%
100%
100%
100%
100%
34%
34%
100%
100%
100%
100%
98%
92%
100%
100%
9%
9%
57%
72%
74%
74%
96%
0%
0%
25%
45%
53%
60%
77%
0%
0%
2%
30%
40%
47%
55%
SSource:
ource: Ibb
Ibbotson
otson (mon
(month-end
th-end da
data)
ta)
Years Until Failure
While historical portfolio success rate can
be a good measure to evaluate different
portfolio strategies, it does not tell the
entire story. Investors are also concerned
about how long their money will last in
periods of failure. For example, it may not
be an ideal strategy if a portfolio is successful 95 percent of the time in lasting 30
years, but only lasts five years in the 5 percent of the time when the portfolio strategy fails—especially when compared to a
portfolio strategy with an 80 percent success rate of lasting 30 years, with money
lasting a minimum of 27 years in the periods the portfolio fails. Investors concerned
about running out of money would more
likely adopt a strategy in which, even when
it fails, they would have 27 years before
their portfolio is exhausted.
As 100 percent equity and 100 percent
bond portfolios have been shown by previous research to be inefficient strategies
www.FPAjournal.org
ST
Table
T
able 2b:
P
Portfolio
ortfolio S
Success
uccess R
Rates
ates 1927–2008,
927–2008,, A
Annual
nnual Rolling 40-Y
40-Year
0-Y
Year
ear
P
Periods
eriod
ds
Withdrawal
W
ithdrawal R
Rates
ates
Portfolio
P
ortfolio
0/100
4
40/60
60/40
80/20
1
100/0
12-Month
12-M
onth SMA
3
3%
53%
100%
100%
100%
100%
100%
4%
0%
0%
70%
91%
91%
91%
88%
100%
100%
5%
0%
0%
26%
53%
67%
67%
72%
91%
91%
6%
0%
0%
2%
30%
49%
49%
56%
67%
67%
7%
0%
0%
0%
9%
33%
33%
40%
42%
42%
SSource:
ource: Ibb
Ibbotson
otson (mon
(month-end
th-end da
data)
ta)
during the withdrawal phase, we have
excluded them from our analysis. The figures that folllow focus on the dynamic and
balanced portfolios. From Table 2a, we saw
the most striking difference in probability
of success between balanced portfolios and
the dynamic portfolio occurred at the withdrawal rate of 5 percent, and thus this is
the withdrawal rate illustrated.
Figure 1a (on page 56) shows the years
money lasted at a 5 percent withdrawal rate
for the 12-month SMA portfolio. The first
bar on the left represents an investor starting the withdrawal phase in 1927 and
ending in 1956. As we can see in Figure 1a,
the 12-month SMA portfolio failed in the
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Contributions
35
30
25
20
15
10
5
–
Annual 30-Year Periods, 12-Month SMA Portfolio, 5% Withdrawal
Rate (1927–2008)
'
1927
1929
1931
1933
1935
1937
1939
1941
1943
1945
1947
1949
1951
1953
1955
1957
1959
1961
1963
1965
1967
1969
1971
1973
1975
1977
1979
Years Portfolio Lasts
Figure 1a:
GARRISON | SERA | CRIBBS
Year Withdrawals Start (Beginning of Year Withdrawals)
Source: Ibbotson (month-end data)
35
30
25
20
15
10
5
–
Annual 30-Year Periods, 40/60 Portfolio, 5% Withdrawal Rate
(1927–2008)
'
'
'
'
'
1927
1929
1931
1933
1935
1937
1939
1941
1943
1945
1947
1949
1951
1953
1955
1957
1959
1961
1963
1965
1967
1969
1971
1973
1975
1977
1979
Years Portfolio Lasts
Figure 1b:
Year Withdrawals Start (Beginning of Year Withdrawals)
Source: Ibbotson (month-end data)
Terminal Value
Annual 30-Year Periods, 60/40 Portfolio, 5% Withdrawal Rate
(1927–2008)
35
30
25
20
15
10
5
–
1927
1929
1931
1933
1935
1937
1939
1941
1943
1945
1947
1949
1951
1953
1955
1957
1959
1961
1963
1965
1967
1969
1971
1973
1975
1977
1979
Years Portfolio Lasts
Figure 1c:
Year Withdrawals Start (Beginning of Year Withdrawals)
Source: Ibbotson (month-end data)
30-year periods beginning in 1937 and 1939.
This makes intuitive sense to those who
have studied monthly market data, because
there was extraordinary monthly volatility
during the beginning of this era. There were
21 months during the period from January
56
Journal of Financial Planning
|
than 10 percent). This led to poor signals for
the 12-month SMA portfolio. In spite of this
poor signaling early on, the 12-month SMA
portfolio still lasted a minimum of 17 years
for the period starting in 1939.
Similar graphs of 40/60, 60/40, and
80/20 portfolios at the 5 percent withdrawal rate illustrate what has been shown
in Table 2a: The 40/60 portfolio was successful approximately 57 percent of the
time, while the balanced portfolios with
greater than 50 percent equity had success
rates in excess of 70 percent. Illustrated by
Figure 1b, 1c, and 1d, the minimum
number of years the 40/60, 60/40, and
80/20 portfolios survived was 20, 19, and
18, respectively.
An important observation from Figures
1a–1d is that, although the 12-month SMA
portfolio minimum survival was 17 years, it
only ran out of money in 20 years or fewer
once, while this occurred more than four
times for each of the balanced portfolios.
Focusing on the postwar era (starting in
1945), there have been no annual 30-year
rolling periods in which the 12-month SMA
portfolio did not survive for at least 30 years.
FEBRUARY 2010
1937–June 1940 in which U.S. large-cap
equities were either up or down more than
5 percent, and in nine of those months,
large-cap equities were either up or down
more than 10 percent (four months down
over 10 percent and five months up more
Many investors would like to leave a legacy
to people or institutions they care about.
So although the primary goal of many
investors is to not run out of money, the
ability to leave the maximum amount of
wealth possible to heirs or charitable
organizations is also of great concern. If two
strategies can make an investment last during
the withdrawal phase, but one of the strategies has no terminal value and the other has
double the initial investment remaining,
which strategy will the investor choose?
The upper-left section of Table 3 shows
the 30-year annual rolling average
($1,547,361), median ($921,086), minimum ($0), and maximum ($5,766,712)
ending values for the 0/100 portfolio at a 3
percent withdrawal rate. For each withdrawal rate, the numbers highlighted in
green are the highest average, median,
minimum, and maximum values. Again,
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Contributions
GARRISON | SERA | CRIBBS
Table
T
able 3:
Figure 1d:
35
30
25
20
15
10
5
–
Annual 30-Year Periods, 80/20 Portfolio, 5% Withdrawal Rate
(1927–2008)
'
'
'
'
'
1927
1929
1931
1933
1935
1937
1939
1941
1943
1945
1947
1949
1951
1953
1955
1957
1959
1961
1963
1965
1967
1969
1971
1973
1975
1977
1979
Years Portfolio Lasts
the 12-month SMA portfolio came out on
top having the highest average, median,
minimum, and maximum ending values
compared with the other portfolio strategies across all tested withdrawal rates. We
were somewhat surprised that the 100/0
portfolio did not have the highest average,
median, or maximum terminal values for
any withdrawal rate scenario.
Let’s examine the details more closely. For
reasons stated previously, we focus on the
terminal values for the 12-month SMA portfolio, 60/40 portfolio, and the 80/20 portfolio using 4 percent and 5 percent withdrawal rates. Because of its lower terminal
values as compared to the other balanced
portfolios, we excluded the 40/60 portfolio.
Analyzing the data in Figure 2a and 2b (on
page 58), using a 4 percent withdrawal rate,
the 12-month SMA portfolio had the highest
terminal value in 48 out of 53 30-year peri-
Year Withdrawals Start (Beginning of Year Withdrawals)
Source: Ibbotson (month-end data)
ods, while the 80/20 portfolio had the highest terminal value in the remaining 5 periods. At the 5 percent withdrawal rate, the 12month SMA portfolio had the highest
terminal value in 48 out of 53 periods, with
the 80/20 portfolio having the highest terminal value in 4 periods. There is one period,
starting in 1937, in which all portfolios
failed, so the terminal value of each portfolio
was $0.
Annual
A
nnual 30-Y
30-Year
Year
Y
ear T
Terminal
erminal V
Values
alues a
att D
Different
iffferent W
Withdrawal
ithdrawal R
Rates
ates 1927–2008 ($1 M
Million
illion S
Starting
tarting P
Portfolio
ortffolio
ol Value)
Value)
Portfolio
P
ortffolio
0/100
40/60
60/40
80/20
100/0
12-Month
12-Month SMA
3%
4%
5%
6%
7%
Average
Average
$1,547,361
$378,160
$45,732
$0
$0
Median
Median
$921,086
$0
$0
$0
$0
$0
M
Min
in
$0
$0
$0
$0
M
Max
ax
$5,766,712
$3,690,690
$1,614,668
$0
$0
A
Average
verage
$4,709,967
$2,450,788
$887,614
$218,171
$12,852
M
Median
edian
$4,137,662
$1,967,086
$301,443
$0
$0
M
Min
in
$1,625,370
$126,208
$0
$0
$0
M
Max
ax
$12,101,076
$8,640,459
$5,486,718
$3,083,936
$681,155
A
Average
verage
$7,186,609
$4,445,651
$2,282,943
$1,065,876
$340,378
Median
Median
$6,691,115
$3,995,477
$1,655,217
$0
$0
Min
Min
$2,949,151
$152,566
$0
$0
$0
M
Max
ax
$17,526,368
$13,454,642
$9,382,916
$5,311,191
$2,506,939
A
Average
verage
$10,395,222
$7,067,771
$4,421,039
$2,689,079
$1,434,591
M
Median
edian
$9,477,597
$6,409,190
$3,434,404
$1,512,492
$0
M
Min
in
$3,104,809
$0
$0
$0
$0
M
Max
ax
$24,093,146
$19,382,271
$14,671,397
$9,960,522
$6,273,570
A
Average
verage
$14,432,384
$10,441,863
$7,314,706
$5,076,858
$3,327,584
Median
Median
$12,515,162
$9,154,399
$6,470,492
$3,058,972
$0
Min
Min
$2,350,972
$0
$0
$0
$0
Max
Max
$32,268,806
$28,178,476
$24,088,145
$20,059,934
$16,061,844
A
Average
verage
$19,778,765
$15,211,653
$10,720,286
$6,803,157
$4,014,266
Median
Median
$17,976,976
$14,216,924
$8,677,086
$4,834,137
$592,498
Min
Min
$5,418,168
$1,473,505
$0
$0
$0
Max
Max
$45,527,432
$39,739,521
$33,951,611
$28,163,700
$22,375,790
SSource:
ource: Ibb
otson (mon
th-end data)
data)
Ibbotson
(month-end
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FEBRUARY 2010
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Journal of Financial Planning
57
Contributions
$45,000,000
$40,000,000
$35,000,000
$30,000,000
$25,000,000
$20,000,000
$15,000,000
$10,000,000
$5,000,000
$0
Terminal Values 4% Withdrawal Rate (1927–2008), 12-Month
SMA vs. 60/40 and 80/20
1927
1929
1931
1933
1935
1937
1939
1941
1943
1945
1947
1949
1951
1953
1955
1957
1959
1961
1963
1965
1967
1969
1971
1973
1975
1977
1979
Figure 2a:
GARRISON | SERA | CRIBBS
Year Withdrawals Start (Beginning of Year Withdrawals)
60/40
80/20
12-Month SMA
Source: Ibbotson (month-end data)
Figure 2b:
Terminal Values 5% Withdrawal Rate (1927–2008), 12-Month
SMA vs. 60/40 and 80/20
1927
1929
1931
1933
1935
1937
1939
1941
1943
1945
1947
1949
1951
1953
1955
1957
1959
1961
1963
1965
1967
1969
1971
1973
1975
1977
1979
$40,000,000
$35,000,000
$30,000,000
$25,000,000
$20,000,000
$15,000,000
$10,000,000
$5,000,000
$0
Year Withdrawals Start (Beginning of Year Withdrawals)
60/40
80/20
12-Month SMA
Source: Ibbotson (month-end data)
Figure 2c:
Terminal Values 5% Withdrawal Rate (1927-2008), 12-Month
SMA vs. 100/0
$40,000,000
$35,000,000
$30,000,000
$25,000,000
$20,000,000
$15,000,000
$10,000,000
$5,000,000
$0
1927
1929
1931
1933
1935
1937
1939
1941
1943
1945
1947
1949
1951
1953
1955
1957
1959
1961
1963
1965
1967
1969
1971
1973
1975
1977
1979
'
Year Withdrawals Start (Beginning of Year Withdrawals)
100/0
12-Month SMA
Source: Ibbotson (month-end data)
The differences in terminal values
between the balanced portfolios and the
dynamic portfolio are striking. When the
withdrawal rate is 4 percent, the 12-month
58
Journal of Financial Planning
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FEBRUARY 2010
SMA portfolio’s terminal value is at least
$2.5 million greater than the 60/40 and
80/20 portfolios in 49 periods and 45 periods, respectively. Examining a 5 percent
withdrawal rate, there are 43 periods in
which the difference between the 12month SMA portfolio and the 60/40 portfolio is more than $2.5 million, and it
keeps this $2.5 million terminal value difference in 42 periods when compared to
the 80/20 portfolio.
Out of curiosity, we also tested the 12month SMA portfolio and compared it to
the 100/0 portfolio to see how it held up.
When compared to the 100/0 portfolio, the
12-month SMA portfolio had a higher terminal value in 40 of 53 30-year periods
when the distribution rate was 5 percent, as
shown by Figure 2c. During the 1927–2008
period, the investor with a high risk tolerance looking to potentially maximize terminal value would have been better served
investing in the 12-month SMA portfolio as
opposed to the 100/0 portfolio.
The 12-month SMA portfolio had the
highest average, median, minimum, and
maximum terminal values compared to all
of the portfolios tested. We found that
these higher terminal values were not the
result of a few periods of outperformance,
and the difference in terminal values for
the 12-month SMA portfolio was significant. For an investor looking to maximize
the ending value of his or her portfolio, we
conclude the 12-month SMA portfolio is
optimal compared to the other portfolios.
What does this mean for the investor?
We recognize that targeting a safe withdrawal percentage and never deviating
from it is not realistic. Withdrawal rates
will probably be lumpy, with the investor
needing more than the safe withdrawal
rate in some years. Completely restricting
lifestyle because of a targeted withdrawal
rate is not ideal, because investors may
need to give up life experiences that are
important to them. A strategy with consistently higher terminal values gives the
investor more opportunities to enjoy life
and deal with unplanned situations.
Sensitivity Analysis
Does the time frame of the moving average
matter? We researched withdrawal rates
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GARRISON | SERA | CRIBBS
Compared to the statically allocated portfolios, the 12-month SMA approach consistently achieved superior results regardless
of whether the S&P 500 was performing
well or not. A period of high monthly
return volatility (from high positive
monthly returns to high negative monthly
returns and vice versa) leading to a whipsawing effect, not long-term market trends,
is the biggest potential weakness in the 12month SMA approach. This extreme whipsawing in returns has not occurred since
the beginning of the 1940s.
At the 5 percent distribution level, the
two most relevant 30-year periods during
which the balanced portfolios outperformed the dynamic portfolio were from
1937–1966 and 1939–1968. In the period
ending in 1966, the 12-month SMA portfolio ran out of money after 21 years, equaling the 40/60 portfolio, but less than the
60/40 portfolio (23 years) and the 80/20
portfolio (24 years). During this period, if
the investor had reduced his or her withdrawal rate to 4 percent, the 12-month
SMA portfolio would have survived with a
terminal value of more than $2.1 million,
which was greater than all of the terminal
values of the balanced portfolios except the
80/20 portfolio ($2.3 million).
In the period ending in 1968, the balanced
strategies were even more dominant, using a
5 percent distribution rate. The 60/40 and
80/20 balanced portfolios succeeded, while
the 12-month SMA portfolio and 40/60 portfolio failed. The 40/60 portfolio survived five
years longer than the 12-month SMA portfolio. The cause of this failure was the extreme
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16.00%
14.00%
12.00%
10.00%
8.00%
6.00%
4.00%
2.00%
0.00%
–2.00%
–4.00%
Compounded Annual Growth Rate Through 2008,
12-Month SMA Portfolio vs. 100/0 Portfolio
1927
1930
1933
1936
1939
1942
1945
1948
1951
1954
1957
1960
1963
1966
1969
1972
1975
1978
1981
1984
1987
1990
1993
1996
1999
Examining Failures of the Dynamic Approach
Figure 3:
Compounded Annual
Rate of Return
using 10-, 11-, 13-, and 14-month moving
averages in addition to the 12-month moving
average presented. The results were very similar to that of the 12-month SMA portfolio
relative to maximum safe withdrawal rate,
probability of success, and terminal values.
The number of years the money lasted fluctuated some. However, none of the tested
moving averages lasted fewer than 14 years
when the distribution rate was 5 percent.
Contributions
Year Buy and Hold Starts
100/0
12-Month SMA
Source: Ibbotson (month-end data)
market volatility from January 1937–June
1940. As stated previously, there were 21
monthly periods with returns of at least +/–
5 percent, and nine of those were +/– 10
percent. This caused the dynamic approach
to receive mixed signals and be in and out of
the market at the wrong times. However,
these were the only 2 periods in which the
12-month SMA portfolio failed, while the
40/60, 60/40, and 80/20 portfolios failed in
23, 15, and 14 periods, respectively. With
greater liquidity in financial markets combined with more government controls in
place now than in the 1930s, a long period of
high volatility may be less likely to occur.
Looking at the modern era (starting in
1945), the 12-month SMA portfolio had 0
failures at a 5 percent withdrawal rate while
the three balanced portfolios all failed in
more than 10 30-year periods.
What About the Accumulation Phase?
Although we believe we have presented
persuasive evidence for using a dynamic
approach during the portfolio distribution
phase, the question still remains whether it
is an appropriate strategy for investors to
use in the accumulation phase. For longterm investors not taking withdrawals,
higher equity percentages typically lead to
higher returns. How does our dynamic 12-
month SMA portfolio compare to the
100/0 portfolio for long-term periods?
Figure 3 shows the compounded annual
rate of return an investor would have
earned from investing in the 100/0 portfolio compared to the 12-month SMA portfolio, depending on the year the investment
was started (through 2008). Moving left to
right in Figure 3, an investor starting in
1927 would have earned a 9.6 percent compounded annual return by buying and
holding U.S. large-cap equities until the
end of 2008 (82 years). Investing in the 12month SMA portfolio, that same investor
would have earned an 11.9 percent compounded annual rate of return over the
same period. The next pair of bars on
Figure 3 shows the period 1928–2008 (81
years), followed by 1929–2008 (80 years),
and the final bars show the returns since
1999 (10 years). We excluded periods of
fewer than 10 years.
The results are remarkable. Historically,
in every year since 1927, an investor using
the 12-month SMA portfolio until 2008
would have achieved a higher rate of
return than if the investor would have
bought and held the 100/0 portfolio.
This may be a bit unrealistic, as most
investors do not have an unlimited time
horizon giving them the ability to buy and
hold an investment for an infinite period.
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59
Contributions
Table
T
able 4:
GARRISON | SERA | CRIBBS
C
Annual
nnual Rates
Rates of Return,
Return,, 12-Month
12
12-Month SMA Portfolio
Portffo
vs. 100/0 Portfolio
Portffo
Compounded
ompounded A
olio vs.
olio
1945
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
2009
100/0
12-Month
12-Month SMA
9.7%
100/0
17.1%
23.9%
12-Month
12-Month SMA
16.1%
22.8%
1955
1960
1965
1970
1975
1980
100/0
16.4%
19.4%
15.0%
12-Month
12-Month SMA
15.4%
18.3%
14.0%
100/0
14.9%
16.4%
12.8%
10.7%
12-Month
12-Month SMA
14.1%
15.6%
12.1%
10.3%
100/0
12.9%
13.4%
10.1%
7.8%
12-Month
12-Month SMA
11.8%
12.4%
9.1%
6.7%
3.2%
100/0
10.2%
10.1%
6.9%
4.3%
1.2%
12-Month SMA
12-Month
11.4%
11.7%
9.1%
7.5%
6.2%
9.3%
100/0
10.8%
10.9%
8.4%
6.8%
5.6%
5.9%
14.8%
12-Month SMA
12-Month
11.3%
11.6%
9.5%
8.3%
7.7%
10.0%
10.8%
10.8%
100/0
11.3%
11.4%
9.5%
8.4%
7.8%
8.8%
14.8%
14.8%
1985
1990
1995
2000
19.6%
5.0%
-2.4%
12-Month SMA
12-Month
12.3%
12.7%
11.1%
10.5%
10.6%
13.1%
15.1%
100/0
12.3%
12.5%
10.9%
10.3%
10.2%
11.6%
16.6%
17.6%
20.4%
12-Month SMA
12-Month
13.1%
13.5%
12.2%
11.9%
12.3%
14.6%
16.5%
19.4%
19.3%
100/0
11.9%
12.1%
10.7%
10.1%
10.0%
11.0%
14.6%
14.5%
14.4%
8.7%
12-Month SMA
12-Month
12.4%
12.7%
11.5%
11.1%
11.3%
13.0%
13.9%
14.9%
12.7%
6.4%
100/0
13.3%
13.6%
12.5%
12.2%
12.4%
13.7%
17.3%
17.9%
18.9%
18.2%
28.6%
12-Month
12-Month SMA
13.6%
13.9%
13.0%
12.9%
13.2%
15.0%
16.2%
17.6%
16.9%
15.8%
25.9%
100/0
12.0%
12.1%
10.9%
10.5%
10.5%
11.3%
13.8%
13.5%
13.2%
10.9%
12.1%
-2.3%
12-Month
12-Month SMA
13.2%
13.5%
12.6%
12.5%
12.8%
14.2%
15.0%
15.9%
15.0%
13.6%
17.3%
9.4%
100/0
10.8%
10.8%
9.7%
9.1%
9.0%
9.5%
11.3%
10.7%
9.9%
7.3%
6.8%
-3.6%
12-Month
12-Month SMA
12.8%
13.1%
12.2%
12.0%
12.2%
13.5%
14.1%
14.7%
13.7%
12.2%
14.4%
8.5%
In addition, the huge market drop in 2008
overstates the 12-month SMA portfolio’s
advantage, so we broke down the returns into
five-year increments, starting in 1945.
Depending on the time frame, Table 4 shows
us there are periods in which a buy and hold
in the 100/0 portfolio outperformed the 12month SMA portfolio. For example, an
investment in the 100/0 portfolio earned a
10.7 percent annual return from the beginning of 1945 to the beginning of 1950, while
the 12-month SMA portfolio earned 9.7 percent during the same period. However, a key
observation from this table is that the compounded annual rate of return for the 12month SMA portfolio improves versus the
100/0 portfolio as the holding period
increases. For investors (such as institutions)
with long to infinite time horizons, the 12month SMA portfolio has a noticeable advantage over the 100/0 portfolio.
60
1950
10.7%
Journal of Financial Planning
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FEBRUARY 2010
A Quick Word About Risk
In the investment community, it is generally assumed that investors with longer
time horizons should be willing to take
more risk, with risk measured by portfolio
standard deviation. In our examples above,
we assume the investor will have the internal fortitude to execute a buy-and-hold
methodology and will be able to follow a
portfolio strategy under any circumstance.
We have found that this is not always the
case. When the market continually
decreases, investors get scared. Even if they
know they are using a portfolio strategy
that has proven to work over time, they
just cannot stick with it.
Maximum drawdown (or maximum
loss), is in our opinion, the most appropriate measure of risk to consider when analyzing a portfolio. Maximum drawdown is
the highest percentage loss a portfolio
experiences over a given time period.
Table 5 illustrates the maximum drawdown each of these three portfolios experienced from 1945 through 2008, using
month-end data. (Please note that the maximum drawdown for the 100/0 portfolio
would exceed 50 percent if this table
included returns through June 2009.) The
implications of maximum drawdown are
far-reaching. Would an accumulation phase
investor stick to the 100/0 portfolio even
after experiencing a loss greater than 44
percent? And after a significant portfolio
loss, would the investor be able to invest
subsequent funds using the same strategy?
Table 4 shows that, in some periods, the
100/0 portfolio has a better compounded
annual rate of return than the 12-month
SMA portfolio. However, a 100/0 portfolio
is clearly not superior, and probably will
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GARRISON | SERA | CRIBBS
Table
T
able 5:
Maximum D
Maximum
Drawdowns
rawdowns
1945–2008
12-Month
SMA
Maximum 25.2% 44.7% 23.3%
Drawdown
60/40 100/0
Source:
Source: Ibb
Ibbotson
otson (mon
(month-end
th-end da
data)
ta)
experience a loss of almost double that of
the 12-month SMA portfolio. We argue the
12-month SMA portfolio would help mitigate the risk of an investor switching his or
her investment strategy at inopportune
times because of the lower maximum
losses it has historically incurred. When
incorporating risk into the discussion for
the accumulation investor, a dynamic 12month simple moving average strategy
should definitely be considered.
Implementation
It is very easy for investors to use a simple
moving average in their portfolio management. The only rule that must be followed is
to be in the market when the last month’s
ending price is above the average price of the
market over the last 12 months, and be in the
dedicated “safe” asset class when the previous
month’s ending price is below the 12-month
moving average. There are no complex withdrawal rules or tactical allocation procedures
to follow.
Further Research
We believe the investment community
could benefit from future research related
to dynamic allocations using simple
moving averages. Using this technique
across other asset classes may lead to
better portfolio performance.
Depending on additional research documenting investment return persistency, the
use of stochastic analysis or random return
generators for investment return results
should be further questioned. The results
we found just using a simple moving average method suggest that the order of
returns may not be random.
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There is still a lot of space for research
using other technical market indicators
and dynamic portfolio approaches, as well
as combinations of multiple strategies. We
look forward to reading other research that
has yet to be done in these areas.
The use of target-date retirement and
lifecycle funds has grown considerably over
the past few years, with assets expected to
be more than $1 trillion by 2015 (Marcks
2008). We question how, by nature of an
investor’s birthday, these funds can force
an investor into a lower equity percentage
that may occur after a large market loss.
This eliminates the possibility of recovery
from the equity assets that have been
shifted to bonds. We have shown how, as
the equity percentage decreases, the probability of being able to maintain higher
withdrawal rates also declines, potentially
destroying an investor’s retirement. We call
on researchers in the investment management and financial advising community to
illustrate the potential for wealth-destroying
effects of these funds.
Conclusion
From 1927–2008, the 12-month moving
average investment method has been a
better strategy for investors requiring distributions compared with statically allocated portfolios. For many periods, it has
been superior for the accumulation phase
investor as well. Financial advisers who
provide investment management for their
clients should examine ways to employ
this methodology in their recommendations. In doing so, they likely will better
serve their clients.
References
Bengen, William P. 1994. “Determining
Withdrawal Rates Using Historical
Data.” Journal of Financial Planning
(October): 171–180.
Bengen, William P. 1997. “Conserving
Client Portfolios During Retirement,
Part III.” Journal of Financial Planning
Contributions
(December): 84–97.
Blanchett, David M. 2007. “Dynamic Allocation Strategies for Distribution Portfolios: Determining the Optimal Distribution Glide Path.” Journal of
Financial Planning (December).
Clark, John M. and Matthew Hood. 2009.
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