Download Buy-and-Hold Versus Market Timing

Buy-and-Hold Versus Market Timing
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By Wayne A. Thorp, CFA
T
he market collapse of 2008–
2009 has led some investors
to question the merits of “buy-andhold” investing. This is not surprising, seeing that this was the second
time in this decade the market has
fallen by more than 45%. It has
also led to renewed interest in ways
of sidestepping such market meltdowns—namely, market timing.
For proponents of Burton Malkiel’s
“random walk” theory, market timing
is a fool’s errand. They argue that you
cannot use past market activity to
predict future movements.
Poking Holes in
Buy & Hold
In a series of articles for
Advisor Perspectives, Inc.
(www.advisorperspectives.
com) between May and July
2009, Theodore Wong set
out to defend the veracity
of market timing using one
of the simplest mechanical trading systems—the
moving average crossover
(MAC). Originally an MITeducated electrical engineer,
Wong shifted his focus to
investing and earned an
MBA. He now combines his engineering analytics with econometric
modeling to create quantitative
investing strategies.
His goal wasn’t to present the
MAC as the best means of timing the
market. Instead, his aim was to see
whether it was possible to use active
investment management to outperform a buy-and-hold approach over a
long period of time.
best investing days. However, Wong
points out that missing out is a twoway street; when considering the
impact of missing the best days, you
should also consider what happens if
you miss the worst days.
For his research, Wong analyzed
stock market price data maintained
by Yale economics professor Robert
Shiller over the period starting at the
beginning of 1871 and going through
the end of April 2009. The data,
which is updated daily, is available
for free online at (www.econ.yale.
edu/~shiller/data/ie_data.xls). In the
spreadsheet, the price data is referred
to as the S&P Composite Stock
Price Index. However, Standard and
Poor’s did not introduce its first
over the period would have
lowered the buy-and-hold benchmark return to 6.4%;
• Excluding the worst 24 months
would have increased the return
to 11.5%.
Examining daily stock market data
from January 1942 through April
2009 yielded even more striking
results:
• The buy-and-hold benchmark
annual return for the period was
10.0%;
• Excluding the best 50 days lowers the annual return to 6.1%;
• Eliminating the worst 50 days
increases the annual return to
15.2%.
Wong also discovered that excluding the best and worst
periods over both timeframes did not give the
buy-and-hold investor any
appreciable advantage.
In fact, looking at daily
data from 1942 to 2009,
missing the best and worst
days would have boosted
your annual return relative
to the buy-and-hold return. As Wong concludes:
“Who would mind getting
similar returns to buy-andhold without the volatile
extremes?”
“Theodore Wong set out to
defend the veracity of market
timing using one of the simplest
mechanical trading systems—
the moving average crossover.”
The “Missing Out” Argument
The first of Wong’s articles tackles
a common argument used to discredit market-timing—the notion of
“missing out.” Missing out refers to
the impact on investment returns if
someone were to mistime the market and “miss out” on some of the
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stock market index until 1923, and
the widely followed S&P 500 index
did not arrive in its current form
until March 4, 1957. According to
“Market Volatility” (The MIT Press,
1992), a book Shiller wrote that also
makes use of the data, the data dating back from the start of 1871 was
compiled using Standard & Poor’s
Statistical Service “Security Price
Index Record,” from tables entitled
Monthly Stock Price Indexes—Long
Term.
Analyzing this data set, Wong made
some interesting discoveries:
• A buy-and-hold investor would
have earned a compound annual
growth rate of 8.6% over the
period;
• Excluding the best 24 months
Drawdown: Measuring
“Emotional Pain”
Wong also addresses another
market phenomenon that seems to
benefit buy-and-hold investors—the
upward bias of the market. This
means that, in theory, the longer you
hold an equity investment, the more
likely you are of earning a positive
return.
To analyze the breakeven holding
period, Wong calculated the “drawdown” of the stock market total
return index over the 137-year period
from 1871 through April 2009.
Drawdown is the percentage decline
from the last equity peak. Wong deComputerized Investing
scribes drawdown as the “emotional
pain” investors endure while holding
stocks that have fallen in value. For
example, in the last market downturn, many investors experienced
too much emotional pain and moved
their investments to cash. As a result,
they missed out on the significant rebound in the market between March
2009 and April 2010.
Wong discovered that the market
was below breakeven a staggering
92% of the time from 1871 through
April 2009 (meaning it was at or
above the previous peak only 8%
of the time). Even during the supposed “bullish” 1990s, the market
was underwater over 50% of the
time. Keep in mind that this means
the market could have been down
any amount, no matter how slight.
However, Wong also found that,
between 1871 and 2009, the market
was down from its previous peak by
more than 40% fully one-third of the
time. This seemingly dispels the notion that such severe market declines
are “once-in-a-lifetime” events, as the
last decade confirms. No matter how
non-risk-averse some investors claim
to be, Wong doubts that many would
be able to stay fully invested in the
market faced with such frequent and
pronounced market downturns.
In addition, Wong’s analysis indicated that it can take a long time to
recover from large drawdowns. Using
an extreme example, it took 26 years
for an investor to recover from the
losses of the 1929 stock market crash
and Great Depression.
What Diversification Benefit?
Most investors will tell you that
the best way to lower the overall risk
of a portfolio is with diversification.
By constructing a portfolio of low or
negatively correlated assets, we lower
the risk inherent to individual assets
(unsystematic risk). (Correlation
is the degree to which assets move
together.)
However, no amount of diversification can eliminate all risk from a
portfolio. During bear markets, as
the most recent one made abundantly
Third Quarter 2010
Table 1. Formula for a 10-Period Exponential Moving Average
1. SMA
2. Multiplier
3. EMA
=
=
=
=
=
=
10-period sum ÷ 10
[2 ÷ (Time periods + 1)]
[2 ÷ (10 + 1)]
0.1818
18.18%
[Close – EMA (previous day)] × multiplier + EMA (previous day)
clear, most stocks will decline. However, the economic shocks that hit the
market in 2008–2009 caused almost
all asset classes to fall in value—U.S.
and foreign equities, real estate, and
commodities. In this case, Wong feels
that the benefits of diversification
“failed” investors at exactly the time
they needed it the most. As it turned
out, only cash and U.S. Treasuries
bucked the stock market’s downward
trend in 2008.
Unfortunately, many investors
viewed diversification as holding different types of equities, without sufficient holdings of cash or bonds. But,
diversification did seemingly do its
job, according to Sam Stovall of S&P
Equity Research. In his March 2010
AAII Journal article [“Diversification:
A Failure of Fact or Expectation?”],
he showed that a portfolio invested
60% in large-cap U.S. equities and
40% in long-term government bonds
experienced a loss of around 13%
in 2008, versus a loss of 37% in the
S&P 500 total return index.
It is Wong’s opinion that allocating
your portfolio to a greater percentage of cash or bonds as the market
declines is not market timing, it is
merely prudent diversification.
The MAC System
After providing some compelling
arguments as to why market timing
deserves a closer look, Wong shifts
his attention to illustrating a way in
which investors can use market timing to lower risk and preserve capital
during market downturns. He is
quick to point out that he is not advocating an optimal strategy, nor does
he claim to have found investing’s
“holy grail.” He is only attempting to
disprove the myths often associated
with market timing.
To illustrate his point, Wong uses
one of the simplest trading systems
used by investors—the moving average crossover, or MAC. In articles
for Advisor Perspectives, market
timers Brian Schreiner and Mebane
Faber wrote about using a 10-month
MAC to avoid the bear markets of
2000 and 2008. [You can find these
articles, as well as those written by
Theodore Wong, by going to the Advisor Perspective’s website and using
the search function.]
With a moving average crossover
system, you buy when the price
crosses over (rises above) the moving
average and you sell when the price
drops below the moving average.
Exponential Moving Average
(EMA)
Wong prefers using an exponential
moving average (EMA), which reduces the lag between the actual price
and the smoothed average by applying more weight to recent prices. The
weighting applied to the most recent
price depends on the number of periods in the moving average. There are
three steps to calculating an exponential moving average:
1.Calculate the simple moving
average (SMA). An EMA has
to start somewhere, so a simple
moving average is used as the
previous period’s EMA in the
first calculation;
2.Calculate the weighting multiplier (discussed momentarily);
3.Calculate the exponential moving
average.
Table 1 shows the formula for a
10-period EMA.
A 10-period exponential moving
average applies an 18.18% weighting
to the most recent price. Notice that
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Feature
Table 2. Example of 10-Day Exponential Moving Average
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
Date
4/30/2010
5/3/2010
5/4/2010
5/5/2010
5/6/2010
5/7/2010
5/10/2010
5/11/2010
5/12/2010
5/13/2010
5/14/2010
5/17/2010
5/18/2010
5/19/2010
5/20/2010
5/21/2010
5/24/2010
5/25/2010
5/26/2010
5/27/2010
5/28/2010
Smoothing 10-Day
Constant
10-Day
Close
SMA
2/(10 + 1)
EMA
1186.69
1202.26
1173.60
1165.87
1128.15
1110.88
1159.73
1155.79
1171.67
1161.63
1157.44
1161.21
0.1818
1161.55
1135.68
1156.11
0.1818
1160.56
1136.94
1149.58
0.1818
1158.56
1120.80
1144.30
0.1818
1155.97
1115.05
1139.21
0.1818
1152.92
1071.59
1133.56
0.1818
1149.40
1087.69
1131.24
0.1818
1146.10
1073.65
1122.63
0.1818
1141.83
1074.03
1114.45
0.1818
1136.85
1067.95
1104.08
0.1818
1130.90
1103.06
1098.64
0.1818
1125.03
1089.41
1094.02
0.1818
1119.39
the weighting for the shorter time
period is more than the weighting for
the longer time period. In fact, the
weighting drops by half every time
the moving average period doubles.
This reduces the lag between the
actual price curve and the smoothed
moving average curve. Table 2 illustrates the calculation of a 10-day
EMA using closing price data for
the S&P 500 total return index from
April 30, 2010, through May 28,
2010.
To learn more about moving
averages and using a spreadsheet to
calculate them, see the Spreadsheet
Corner column beginning on page 12
in this issue.
Testing the MAC System
When testing the MAC, Wong outlines three explicit assumptions:
• All proceeds from selling are
held in non-interest-bearing cash;
• There are no transaction costs
(commissions, bid-ask spreads,
etc.); and
• There are no tax implications.
In addition, he assumes that he is
buying and selling in the same month
the signal is generated. He says it is
possible to do this buy trading in the
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<< 9-day SMA
=(D14-F13)*E14+F13
closing moments of the last trading
day in the month when it is apparent
what the signal for that month will
be.
As mentioned earlier, a buy-andhold investor would have earned
around 8.6% a year between 1871
and April 2009 by investing in the
total market. Using exponential
moving averages (while he doesn’t
explicitly state this, we assume he
uses exponential moving averages
since he states his preference for
them) ranging in length from two to
23 months, Wong found that moving
averages of 10 months or less consistently outperformed the buy-and-hold
benchmark return. Furthermore, on a
risk-adjusted basis (using the ratio of
the compounded annual growth rate
to the annualized standard deviation of monthly standard deviation),
the MAC beat buy-and-hold over all
moving average lengths.
Wong feels that standard deviation
as a risk measure has one significant
drawback—it treats volatility to the
upside the same as downside volatility. In his opinion, however, investors
who have long positions in stock
do not have a problem with aboveaverage gains. They are concerned
only with downside risk. Therefore,
Wong looks at drawdown to consider
only the downside risk. To reiterate,
drawdown is the percentage decline
from the latest equity peak.
Wong’s analysis found that buyand-hold investors experienced
a maximum drawdown of –85%
from January 1871 through April
2009. This took place between the
pre-crash peak of 1929 through the
trough of 1932. The average drawdown over the entire period from
1871 to 2009 was –26%. Using
exponential moving averages from
two months to 23 months in length,
Wong found a maximum drawdown
of –15% and an average drawdown
of –4%. This indicates that the MAC
offers significant downside protection
during market declines relative to
buy-and-hold.
Table 3 summarizes Wong’s
analysis, presenting data for the buyand-hold benchmark as well as the
six-month MAC, which yielded the
best results, and the 23-month MAC,
which did the worst.
While transaction costs (commissions) were not considered when
calculating the performance of the
MAC system, Wong was aware of
their potential negative impact.
However, he found that the MAC
would have generated, on average,
less than 0.4 round-trip trades (buy
and sell) a year across all moving
average lengths. Over 137 years,
this translates into one round-trip
trade every 2.6 years. Even using a
two-month moving average, which
is most susceptible to price changes,
would have generated 0.9 round-trip
trades a year or one round-trip trade
every 1.1 years. Not only does this
show that transaction costs would
have had only a negligible impact
on returns, it also shows that the
MAC system, on average, would
generate only long-term capital gains
(which are taxed at a lower rate than
ordinary income). However, Wong
does acknowledge that over shorter
periods, it is possible for the MAC to
generate false signals, also known as
whipsaw, that would have investors
Computerized Investing
Feature
entering and exiting trades on a more
frequent basis.
Wong had seemingly found a market timing system that outperforms
buy-and-hold on both an absolute
and risk-adjusted basis over the last
137 years. He proceeded to examine
the MAC returns by decades across
the entire period. Specifically, he
wanted to see how the MAC performed relative to buy-and-hold during bear markets.
Decadal Analysis
Between January 1871 and June
2009, $1 invested in the S&P 500 total return index using the six-month
MAC system would have grown
to $332,000. In stark contrast, the
same investment in the index using
buy-and-hold would have grown to
$105,000. However, Wong was concerned that the 1929 stock market
crash may have skewed the results
in the MAC’s favor. So he looked at
the period from January 1941 to June
2009 and found that the six-month
MAC and buy-and-hold yielded
almost identical results—roughly a
1,000% cumulative gain. Over these
seven decades, however, buy-andhold outperforms MAC most of the
time. It was not until the most recent
bear market that the returns equalized.
Wong then broke the 137-year test
period into decades. Over the 14
decades between 1871 and 2009,
buy-and-hold outperforms MAC in
only six of them, but outperformance
in five of those decades was only by
slight margins. In all of the decades
where buy-and-hold outperformed
MAC, the margin was never more
than 4% over 10 years, or less than
0.4% a year.
In contrast, in eight of the 14
Table 3. Comparison of Buy-and-Hold Versus MAC, Using S&P Stock Price
Index Data From January 1871–April 2009
Buy & Hold
6-Mo MAC
23-Mo MAC
Compound
Annual
Growth
(%)
8.6
9.6
7.9
Ending
Value
of $1
($)
84,660
319,000
36,000
Average
Draw-
down
(%)
(25.9)
(2.0)
(4.0)
Maximum
Drawdown
(%)
(81.8)
(13.8)
(14.9)
*Source: Theodore Wong/Robert Shiller.
decades in which MAC outperformed
buy-and-hold, the margin was never
less than 4%.
Since 2001, MAC has outperformed buy-and-hold by over 8%
(although the decade isn’t quite yet
over). In addition, the current decade
thus far is the only one where buyand-hold has experienced a loss over
the last 137 years.
Over the entire 137-year test period, buy-and-hold outperformed the
MAC over half of the time. However,
Wong believes that buy-and-hold has
benefited from the strong “secular”
bull markets of the last six decades as
the U.S. economy and its stock market exploded following World War II.
In a secular bull market, strong investor sentiment drives prices higher,
as there are more net buyers than
sellers. Furthermore, he feels that the
research that supports buy-and-hold
is based on the secular bull markets
over this period. As a result, the research has concluded that no one can
outperform the market.
Paradigm Shift?
However, the last decade has painted a very different picture as investor
sentiment has dipped in the face of
more frequent economic shocks. As
a result, investors have not had the
Wayne A. Thorp, CFA, is editor of Computerized Investing and
a senior financial analyst at AAII. Follow him on Twitter @CI_Editor.
Third Quarter 2010
Annual
Risk-Adjusted
Return
(%)
23.8
37.4
31.9
benefit of these same bull markets
to recover from the 2000 market
bubble. Furthermore, they were hit
by another market collapse only eight
years later. Wong’s research has led
him to conclude that buy-and-hold
works during periods of economic
expansion, but underperforms during
economic slowdowns and contractions. Once again, in his opinion, this
opens the door for market timing.
If you had invested $1 in the S&P
500 total return index at the beginning of 2000, this investment would
have fallen to less than $0.80 through
mid-2009. By contrast, $1 invested
in the index using the six-month
MAC would have grown to more
than $1.40 over the same period (this
mimics the investment return if you
had bought and held the S&P 600
SmallCap total return index over the
same period).
Conclusion
In the end, Wong contends that
the MAC doesn’t predict markets; it
merely follows market trends. The
MAC doesn’t sell at market peaks or
buy at market bottoms. What it does
do, as his research seems to indicate,
is preserve wealth in bear markets
and accumulate wealth in good times.
The question he poses is whether we
believe a strong secular bull market
will return once this recession is over.
Only time will tell.
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