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.