Market timing systems are based on patterns of activity in the
past. Every system that you are likely to hear about works well
when it is applied to historical data. If it didn’t work
historically, you would never hear about it. But patterns change,
and the future is always the great unknown. A system developed
for the market patterns of the 1970s, which included a major
bear market that lasted two years, would have saved investors
from a big decline. But that wasn’t what you needed in the
1980s, which were characterized by a long bull market. And a
system developed to be ideal in the 1980s would not have done
well if it was back-tested in the 1970s. So far in the 1990s,
any defensive strategy at all has been more likely to hurt
investors than help them.
If your emotional security depends on understanding what’s
happening with your investments at any given time, market timing
will be tough. The performance and direction of market timing
will often defy your best efforts to understand them. And
they’ll defy common sense. Without timing, the movements of the
market may seem possible to understand. Every day, innumerable
explanations of every blip are published and broadcast on
television, radio, in magazines and newspapers and on the
Internet. Economic and market trends often persist, and thus
they seem at least slightly rational. But all that changes when
you begin timing your investments. Unless you developed your
timing models yourself and you understand them intimately, or
unless you are the one crunching the numbers every day, you
won’t know how those systems actually work. You’ll be asking
yourself to buy and sell on faith. And the cause of your
short-term results may remain a mystery, because timing
performance depends on how your models interact with the
patterns of the market. Your results from year to year,
quarter to quarter and month to month may seem random.
Most of us are in the habit of thinking that whatever has just
happened will continue happening. But with market timing, that
just isn’t so. Performance in the immediate future will not be
influenced a bit by that of the immediate past. That means you
will never know what to expect next. To put yourself through a
"timing simulator" on this point, imagine you know all the
monthly returns of a particular strategy over a 20-year period
in which the strategy was successful. Many of those monthly
returns, of course, will be positive, and a significant number
will represent losses. Now imagine that you write each return
on a card, put all the cards in a hat and start drawing the
cards at random. And imagine that you start with a pile of poker
chips. Whenever you draw a positive return, you receive more
chips. But when your return is negative, you have to give up
some of your chips to "the bank" in this game. If the first
half-dozen cards you draw are all positive, you’ll feel pretty
confident. And you’ll expect the good times to continue. But
if you suddenly draw a card representing a loss, your euphoria
could vanish quickly. And if the very first card you draw is a
significant loss and you have to give up some of your chips,
you’ll probably start wondering how much you really want to play
this game. And even though your brain knows that the drawing is
all random, if you draw two negative cards in a row and see your
pile of chips disappearing, you may start to feel as if you’re
on "a negative roll" and you may start to believe that the next
quarter will be like the last one. Yet the next card you draw
won’t be predictable at all. It’s easy to see all this when
you’re just playing a game with poker chips. But it’s harder
in real life. For example, in the fourth quarter of 2002, our
Nasdaq portfolio strategy, with an objective to outperform the
Nasdaq 100 Index, produced a return of 5.9 percent, very
satisfactory for a portfolio invested in technology funds only.
But that was followed by a loss of 7.8 percent in the first
quarter of 2003. Most investors in this strategy, at least those
we know of, stuck with it. But they experienced significant
anxiety at the loss and the shock of a sharp reversal in what
they had thought was a positive trend. The same phenomenon
happened, with more dramatic numbers, in our more aggressive
strategies. Some investors entered those portfolios in the
winter of 2002, and then were shocked to experience big
first-quarter losses so quickly after they had invested. Some,
believing the losses were more likely to continue than to
reverse, bailed out. Had they been willing to endure a little
longer, they would have experienced double-digit gains during
the remainder of 2003 that would have restored and exceeded all
of their losses. But of course there was no way to know that in
advance.
Most timers won’t tell you this, but all market timing systems
are "optimized" to fit the past. That means they are based on
data that is carefully selected to "work" at getting in and out
of the market at the right times. Think of it through this
analogy. Imagine we were trying to put together an enhanced
version of the Standard & Poor’s 500 Index, based on the past
30 years. Based on hindsight, we could probably significantly
improve the performance of the index with only a few simple
changes. For instance, we could conveniently "remove" the
worst-performing industry of stocks from the index along with
any companies that went bankrupt in the past 30 years. That
would remove a good chunk of the "garbage" that dragged down
performance in the past. And to add a dose of positive return,
we could triple the weightings in the new index of a few
selected stocks; say Microsoft, Intel and Dell. We’d get a new
"index" that in the past would have produced significantly
better returns than the real S&P 500. We might believe we have
discovered something valuable. But it doesn’t take a rocket
scientist to figure out that this strategy has little chance
of producing superior performance over the next 30 years. This
simple example makes it easy to see how you can tinker with
past data to produce a "system" that looks good on paper. This
practice, called "data-mining," involves using the benefit of
hindsight to study historical data and extract bits and pieces
of information that conveniently fit into some philosophy or
some notion of reality. Academic researchers would be quick to
tell you that any conclusions you draw from data-mining are
invalid and unreliable guides to the future. But every market
timing system is based on some form of data-mining, or to use
another term, some level of "optimization." The only way you can
devise a timing model is to figure out what would have worked
in some past period, then apply your findings to other periods.
Necessarily, every market timing model is based on optimization.
The problem is that some systems, like the enhanced S&P 500
example, are over-optimized to the point that they toss out the
"garbage of the past" in a way that is unlikely to be reliable
in the future. For instance, we recently looked at a system that
had a few "rules" for when to issue a buy signal, and then added
a filter saying such a buy could be issued only during four
specific months each year. That system looks wonderful on paper
because it throws out the unproductive buys in the past from
the other eight calendar months. There’s no ironclad rule for
determining which systems are robust, or appropriately optimized,
and which are over-optimized. But in general terms, look for
simpler systems instead of more complex ones. A simpler system
is less likely than a very complex one to produce extraordinary
hypothetical returns. But the simpler system is more likely to
behave as you would expect.
To be a successful investor, you need a long-term perspective
and the ability to ignore short-term movements as essentially
"noise." This may be relatively easy for buy-and-hold investors.
But market timing will draw you into the process and require
you to focus on the short term. You’ll not only have to track
short-term movements, you’ll have to act on them. And then
you’ll have to immediately ignore them. Sometimes that’s not
easy, believe me. In real life, smart people often take a final
"gut check" of their feelings before they make any major move.
But when you’re following a mechanical strategy, you have to
eliminate this common-sense step and simply take action. This
can be tough to do.
You will have long periods when you will underperform the market
or outperform it. You’ll need to widen your concept of normal,
expected activity to include being in the market when it’s going
down and out of the market when it’s going up. Sometimes you’ll
earn less than money-market-fund rates. And if you use timing to
take short positions, sometimes you will lose money when other
people are making it. Can you accept that as part of the normal
course of events in your investing life? If not, don’t invest
in such a strategy.
Even a great timing system may give you bad results. This should
be obvious, but market timing adds a layer of complication to
investing, another opportunity to be right or wrong. Your timing
model may make all the proper calls about the market, but if you
apply that timing to a fund that does something other than the
market, your results will be better or worse than what you might
expect. This is a reason to use funds that correlate well you’re
your system.
The bottom line for me is that timing is very challenging. I
believe that for most investors, the best route to success is to
have somebody else make the actual timing moves for you. You can
have it done by a professional. Or you can have a colleague,
friend or family member actually make the trades for you. That
way your emotions won’t stop you from following the discipline.
You’ll be able to go on vacation knowing your system will be
followed. Most important, you’ll be one step removed from the
emotional hurdles of getting in and out of the market.
Copyright,
Robert van Delden
Robert van Delden has been managing the FundSpectrum Group since 1998, whose objective it is to help individual investors to increase their investment returns using low risk Market Timing strategies.. More details can be found on our membership web site:
http://www.fundspectrum.com
