Timing Model
The Timing Model is
a proprietary computer-based model that issues buy and sell signals as it detects
changes in the direction of stock market cycles based on a set of predictive
indicators.
Performance
The
accompanying table and charts summarize the tested (theoretical) performance of
the timing model over selected time periods.
|
Timing Model Version: 2008 |
Ending |
Per Year |
Years to |
|
Max Annual |
|
1970s |
$20,378 |
7.4% |
9.7 |
|
|
|
Treasury-Bills |
18,335 |
6.2% |
11.4 |
0.0% |
|
|
Buy & Hold |
17,505 |
5.8% |
12.4 |
7.2% |
-26.6% |
|
Model Standard |
34,616 |
13.2% |
5.6 |
1.8% |
-6.6% |
|
Model Aggressive |
44,974 |
16.2% |
4.6 |
5.3% |
-16.6% |
|
1980s |
$16,438 |
5.1% |
13.9 |
|
|
|
Treasury-Bills |
23,354 |
8.9% |
8.2 |
0.0% |
|
|
Buy & Hold |
50,038 |
17.5% |
4.3 |
2.4% |
-5.0% |
|
Model Standard |
85,274 |
23.9% |
3.2 |
0.4% |
None |
|
Model Aggressive |
126,850 |
28.9% |
2.7 |
2.3% |
-0.5% |
|
1990s |
$13,320 |
2.9% |
24.2 |
|
|
|
Treasury-Bills |
16,089 |
4.9% |
14.6 |
0.0% |
|
|
Buy & Hold |
53,094 |
18.2% |
4.2 |
1.4% |
-3.2% |
|
Model Standard |
66,842 |
20.9% |
3.6 |
0.1% |
None |
|
Model Aggressive |
129,669 |
29.2% |
2.7 |
0.3% |
None |
2000s |
$12,478 |
2.8% |
25.1 |
|
|
|
Treasury-Bills |
12,858 |
3.2% |
22.1 |
0.0% |
|
|
Buy & Hold |
11,385 |
1.6% |
42.8 |
6.8% |
-22.1% |
|
Model Standard |
16,589 |
6.5% |
11.0 |
1.9% |
-3.5% |
|
Model Aggressive |
19,286 |
8.6% |
8.4 |
2.8% |
-11.2% |
|
1970-2007 |
$55,674 |
4.6% |
15.3 |
|
|
|
Treasury-Bills |
88,586 |
5.9% |
12.1 |
0.0% |
|
|
Buy & Hold |
529,438 |
11.0% |
6.6 |
4.3% |
-26.6% |
|
Model Standard |
3,273,083 |
16.5% |
4.5 |
1.0% |
-6.6% |
|
Model Aggressive |
14,267,180 |
21.1% |
3.6 |
2.7% |
-16.6% |
|
|
|||||
Buying and holding stocks
from 1970 forward would have returned an annualized 11.0%,
including eight losing years with losses up to 27%. The standard timing model
returned an average 16.5%, while the
aggressive timing model further upped the return to 21.1%.
Putting $10,000 into stocks in 1970 and letting it ride would have accumulated
about $529 thousand by the end of last year. The equivalent
money market indexed on T- 
Bills would have been about $89
thousand. The same starting amount based on the timing system would have grown
to about $3.3 million using the
standard strategy and $14.3 million
using the aggressive strategy. The average performance of the standard timing
model doubles a portfolio in 4.5
years.
The aggressive timing
model gained an impressive 30% during the debilitating bear-market in 1973-74
and the standard model lost just 3%, while buy and holders liquidated about 42%
of an S&P portfolio. During the bear
market of 2000-2002, buy & hold portfolios shrank 46%, while the standard
portfolio gained 1% and the aggressive portfolio gained 44%. The timing model
remained faithful to 1980's key signals, getting in the market in August, 1982,
out before the October crash in 1987, and back in near the bottom in late
November. The 42% return in 1987 for the standard model trounced the 5% S&P
500 return, while avoiding the heart-pounding, if not terrifying, S&P 500
roller coaster’s two-week 20% plunge following the sell signal. That
seminal year was made to order for the aggressive model, as it logged a
stunning 108% return.
The timing model has its warts as well. The standard model had three losing years ranging from under 3% to nearly 7%, while the aggressive model had six losing years from under 1 to 17%. By comparison, buy and holders lost money in eight years, with losses ranging from 3 to 27%. Out of 38 years, the standard model under-performed buy & hold in eight years, breaking even in thirteen, and winning seventeen.
Still, the timing
model's strategy yielded superior results over the popular, although
theoretical, buy-and-hold strategy. And it accomplished this with much less
risk of under performing the money market alternative during weak stock
market years. In particular, note the results for the risky and tough
investment period spanned by the 1970s. During that turbulent
decade, buy-and-hold under performed money markets. Worse yet, inflation
sprinted to an annualized rate of 7.4%, giving a real (inflation-adjusted) negative
return for both money markets and stocks!
Typically, risk is a
measure of volatility in returns. From my perspective, however, it's not simply
a measure of volatility; it's a measure of downside volatility. In this
version, as implemented by Morningstar Mutual Funds, a portfolio
exhibits risk if it under performs the money market alternative. For example,
in 1990 the buy-and-hold S&P 500 strategy lost 3.2%, whereas T-Bills
returned 7.8%. The risk for that year is the 11.0 percentage points by which
the S&P 500 under performed T-Bills. The risk for a year is zero whenever a
portfolio's return exceeds the T-Bill rate. A risk calculation in the table is
the sum of risk results for each year divided by the number of years. By this
definition of risk, a money market's risk based on T-Bills is zero. Note that
the standard model's risk is about one- 
quarter that of the considerably
riskier buy-and-hold S&P 500 strategy.
The accompanying Return vs
Risk chart shows the standard portfolio above (higher return) and to the left
(lower risk) than the buy & hold portfolio.
A good timing model “can have its cake and eat it too.” It can achieve higher return with lower risk
than the widely-promoted buy-and-hold strategy.
Note, however, that the aggressive strategy yields higher return than
the standard strategy, but at the expense of greater risk. This result is consistent with financial
research (and conventional wisdom) that higher return incurs higher risk. Yet, the aggressive model sustains just 62%
of the risk of buying and holding. A
timing model can turn conventional wisdom on its head.
Maximum drawdown is another risk
criterion. For buy and holders this risk amounted to a 27% loss (in
1974), compared to almost 7% (1977) for the standard portfolio, and 17% (1977)
for the aggressive portfolio. During the strongly cyclical decades of the
1970s and 1980s, the standard model exhibits much less risk than buying and
holding, by any measure.
Yet another take on risk is
value at risk (VAR), which in our case addresses the
question "How much do we stand to lose from one week to another?" The
table below yields some interesting answers, including responses to the dual
question "How much can we gain in a week?"
From a VAR viewpoint, the
red cells tell a potentially harrowing story for risk-averse investors. Buy
& holders suffered losses in 43% of the weeks, about the same as the
aggressive model; the standard model reduces this risk to 28%. The worst weekly
drawdown was about 12% for both buying & holding and the aggressive model;
again, the standard model shows lower risk at about 8%. The maximum drawdown
for buy & holders 
was sustained during Black-Monday
week in October, 1987; the model's maximum loss was in the second week of
September, 1986, as the market gave back strong gains from the preceding month.
Out of 1983 weeks, the standard model lost more than 7.5% in just one week. Buy
& holders incurred seven such losses, but the aggressive model showed twelve
severe weekly losses exceeding seven and one-half percent.
The aggressive model does
compensate the risk takers, with some spectacular weekly returns. The maximum
returns in the table are not misprints; these were achieved in the second week
of October, 1974, as the S&P 500 vaulted from the bottom of the 1973-74
bear market during a buying panic, a point in time that many analysts cite as
the beginning of the great secular (long-term) bull market that ended in
2000.
By the way, the traditional
measure of risk (volatility) in financial analysis is standard deviation, a statistic that
measures variations (both up and down) from the average or mean. As seen near
the bottom of the table, the model's standard portfolio shows lower risk than
buying and holding, as expected. The aggressive model shows the highest
variability, although this measure is influenced by returns both below and above the average return.
A popular measure of risk-adjusted
return is the Sharpe ratio, named after Nobel Laureate William
Sharpe. This is defined as excess return
for a portfolio divided by the portfolio’s standard deviation, where
excess return is the amount by which a portfolio exceeds a risk-free return
such as that given by the 90-day T-bill, our money market benchmark. In other words, the Sharpe ratio is a measure
of excess return per unit of standard deviation (risk). It’s useful in comparing the performances
of different portfolios during the same time period. As seen, the standard model has the highest
Sharpe ratio, more than twice that of buy and hold. It also outperforms the aggressive
portfolio. While the standard portfolio
has a lower return than the aggressive portfolio, its much lower standard
deviation more than compensates when risk is taken into consideration.
The stock market can be
hazardous to our short-term wealth, with severe price shocks to the downside.
The standard model has historically reduced this form of risk, but it does take
a steady hand at the helm during these short-term squalls.
The timing model calculates
a score in the range 0 to 100. A score of 50 is dead neutral, roughly stating
that the odds of a currently up trending market are the same as a currently
down trending market. A score of 80, for example, says that the likelihood of a
primary uptrend is 80%, or four to one odds; a score of 10 indicates only a 10%
probability (odds of 1 to 9) of a primary uptrend. A primary uptrend is
defined as an increase of 10% or more in the S&P 500 Index over at least
eight weeks. Similarly, a primary downtrend is defined as a decrease of
10% or more in the index over at least eight weeks. Basically, we want to be in
stocks during primary uptrends and in cash during primary downtrends.
Buy and sell signals are
triggered by comparing the model's score to rigorously tested buy and sell
bands. A score at or above the buy band
(currently 73) is positive or bullish
for stocks; a score at or below the sell band
(currently 42) is bearish or negative. If
we're in a sell phase (the last signal was a sell signal), the score must hit
or pop above the buy band for the model to issue a buy signal; otherwise, it remains on the sell signal. Likewise, if we're in a buy
phase, the score must hit or sink below the sell band to issue a sell signal;
else the model stays on its buy signal.
The accompanying chart shows 51
switch signals over 38 years, averaging about three signals every two years. An
average 39 weeks passed between signals.
Buy phases ranged from 1 to 237 weeks, averaging 57 weeks, where
one-half were above 20 weeks in length; sell phases lasted anywhere from 3 to 83
weeks, averaging 22 weeks, with one-half the sell signals lasting over 15
weeks. Of the 51 switch signals, just 2 were one-week switchbacks, both buy
signals. The model spent 72% of the time in stocks.
A score is generated by
pattern-recognition techniques based on a distilled set of indicators.
More than forty indicators were carefully constructed (derived or transformed)
from a set of thirty weekly raw data items, based on financial and technical
hypotheses. (No miniskirt or Super Bowl indicators here!) Of these, just eleven indicators passed
experimental muster over the test period from 1970 to date.
We can group indicators
into four categories for descriptive purposes. Monetary indicators
include levels, changes, and differences in various interest rates; certain
actions by the Federal Reserve that implement changes in monetary policy; and
money supply measures that influence economic activity, such as the widely
reported M2. Technical indicators reflect levels, changes, and other
measures of stock market activity. Changes, trends, and volatility in
stock market indexes, up and down volume action, relationships between new
highs and lows, and measures of advancing issues versus declining issues are
all examples of technical indicators. Sentiment indicators gauge emotion
in the market. Many of these indicators take advantage of the "herd
mentality" by giving signals that run contrary to extremes in
sentiment. For example, high levels of cash in mutual funds not only may
mean that cash is available to fuel an up move in the stock market but also
that stock fund managers are bearish on the market. As another example,
extremely bullish sentiment among financial newsletter writers or small investors
often means that the market is about to reverse course to the downside (if
everyone is already bullish, who's left to buy?). Fundamental
indicators describe economic and valuation activities. These include
measures of inflation, growth, and other factors related to the overall
economy; they also embrace relationships among stock prices, corporate
earnings, and dividends, such as price/earnings ratios and dividend yields.
Note that no one indicator
dominates the model. Many analysts focus
on one or two indicators regarding market direction, a decidedly narrow view
that ignores other competing influences.
For example, many investors view a meaningful rise in interest rates as
a time to sell. The extent of this
influence depends on other factors as well.
At what point are we in the interest rate cycle? Where are we in the business or profit
cycle? Is market momentum strong? Is the market overvalued, undervalued, or
fairly valued? How much is emotion
influencing the market at this time?
Reality is much more complex and subtle.
Note also that external factors such as terrorist attacks
and geopolitical events are unpredictable and not directly accounted for by the
model, but the model does monitor how the market “patient” reacts
to these events, much like a real patient’s vital signs are measurable by
instrumentation. The effect of a shock
to the system is much more pronounced when the patient is weak (the model is on
a sell signal or shows a low score) than when a patient is strong (the model is
on a buy signal or has a high score).
Declines during “emotional” times suggest opportunities for
additional, although scary, commitments to the market, providing that the model
remains “comfortably” above its sell trigger. In sum, the model stirs eleven indictors into
the pot, making its decisions based on the interactions that determine this
brew’s composite flavor.
Note:
See download page for Excel workbook that includes time
series of the S&P 500, timing model scores, buy/sell bands, switch signals,
T-Bills, and dividend yields from 1970 forward.
An investment strategy
based on the standard model is simple to implement. Telephone or online
switches are made between money market funds and stock funds whenever market
conditions favor one or the other based on switch signals. Thus, an investor
who wishes to closely follow the standard model would be in a money market fund
during a sell signal and in an S&P 500 Exchange Traded Fund (ETF) such as
SPY or an Index fund such as Fidelity's Spartan Market Index (FSMKX) during a
buy signal. The counterpart to the aggressive model is to be in funds such as Rydex Nova (RYNVX) during buy signals and Rydex Ursa (RYURX) during sell
signals. The FAQs page identifies
alternative standard and aggressive investments.
Those of you who wish to
mimic the behavior of the aggressive portfolio should keep in mind that this
strategy requires a high tolerance for volatility... and nerve. At a buy
signal, this portfolio switches all funds into a 150% long position basis the
S&P 500 Index. This would be equivalent to a mutual fund with beta 1.5, or one that generates 50%
greater gains (on the upside) and 50% greater losses (on the downside) than the
S&P 500 Index. At a sell signal, all money is 100% short the S&P 500
(beta -1.0). Thus, if the S&P 500 were to lose 10%, this position would
gain 10%. Conversely, a 10% gain in the Index translates into a 10% loss for
the portfolio. In theory the aggressive
strategy should work very well, providing signals are followed faithfully. But... I wouldn't bet the bank on volatile investment
strategies... and I would restrict funds to only a modest portion of my overall
portfolio.
Abiding by the timing
model's signals does require patience and discipline. False switchbacks aside,
the timing system has an intermediate to long-term perspective, months to
years, rather than days to weeks. The less we trade the better off we are with
respect to the payment of expenses and taxes. Moreover, we have to control
emotions when following a switch signal. More often than not, the model gives a
buy signal at a time of high investor anxiety, as in December, 1987, November,
1990, September, 1998, and April 2003. And it can give a sell signal when times
look okay, as it did in early October, 1987 and September, 2000.
The timing model is tuned
to anticipate changes of 10% or more in the S&P 500 Index. It leaves
the smaller, riskier, choppier waves for the traders to try to fathom.
Declines of about 5% are common and scary, but extremely difficult to
anticipate with any accuracy. I treat these with equanimity (usually!)
when they happen, letting the model tell me when to consider a switch.
Market timing is controversial
and not suitable for everyone. "Buying and holding" is the current
mantra, but few souls can hold through thick and thin, or commit new money when
times are scary. Asset allocation strategies are more conservative, giving up
gain for lower risk, although those who rebalance portfolios are practicing a
form of market timing. And how about buying good stocks and sticking with them?
How do we pick the good stocks? Do we really hang on? Academic studies and
research in behavioral finance suggest that individuals buy high and sell low
their individual stocks and mutual funds. Long-term good stock picking surely
rewards the pickers and their followers. Witness Peter Lynch, George Soros, and
Warren Buffett. But few of us have neither the time, the
emotional makeup, nor the talent for successful stock picking... and how
do we pick the good pickers? And will we ride it down with them during
prolonged and severe market downturns?
Few bulls come out the back end of a serious bear market.
Any trading system is
imperfect in practice. I accept the bad along with the good, as long as the
good outweighs the bad. This underscores a key advantage of working with a good
system: It offers an investment plan and promotes discipline, while stabilizing
emotions and curtailing actions that constantly play to fear and greed. I can't
guarantee future results based on past performance, but I haven't found a
better way for myself.
Live Market Timing Phases
The performances described are
theoretical in the sense that the model's structure is tested and
revised annually to optimize return based on historical data. The model is
"live" when it is actually used in practice. The timing model's
actual performance is described in Reality Check,
starting with its earliest implementation in 1989.
Last revised 02/01/2008
Distribution
Copyright © 2008 Richard Mojena. All rights reserved. The information presented here may not under any circumstances be resold or redistributed
for compensation of any kind without prior written permission from Richard
Mojena at mojena.com.
Disclaimer
Specific and personalized investment advice is not intended by this
communication. Its contents are for the public record as a free public service.
Information is based on the analysis of past data and assessments by the
models. Future performance may not reflect past performance. Profitable trades are
not guaranteed. No system or methodology ensures stock market profits. No
guarantee is made regarding the reliability or accuracy of data. In other
words, use this stuff at your own risk!