I don't know how many of you are involved in the Watts Yahoo group
but for those that aren't please read this post that was there this
week, to me this expains what is wrong with so many system DTME
is at the head of the list... read this through and I think you'll see why.
*********MUST READING BELOW *************************
At investment conferences, the hottest speakers are those who
provide information about high probability entry techniques. If you
say, "Trade with the odds on your side" and show someone a technique
that is right 75% of the time, you'll get a large audience. Yet most
techniques of this nature usually have big losers and may not even
have a positive expectancy. Nevertheless, being right 75% of the
time is all is takes to get people to trade them.
(Sound like any "teacher" you know of?)
How important is it for you to be right? Let's say I could guarantee
that you would make money by the end of the year lots of money but
you would probably lose money on 90% of your trades. Would you like
that? Could you tolerate that? Would you accept that? Most people
would probably answer "no" to all three questions. And if that is
you, you probably are denying yourself the opportunity to make money
simply because being right is more important than making money.
Some of you might be saying, "How could you be wrong 90% of the time
and still make money?" The solution goes back to the golden rule of
trading, "Cut your losses short and let your profits run." Let's say
that 90% of your trades lose money and that your average loss is
$100. On the year you make 100 trades so you end up losing 90 of
them for a total loss of $9,000. However, let's also say that your
average winning trade is a big R-multiple. It's an R-multiple of 100
or a $10,000 winner. You have ten of those in a year, so you end up
making $100,000 on your winning trades. If you subtract your
winnings from your losses, you'd end up with a profit of $91,000 at
the end of the year. You make $91,000, yet 90% of your trades are
losers.
My guess is that 99% of the trading population could not trade a
system that would produce those kind of results. The reason is
because they don't get to be right enough. They have too many losing
streaks. They have losing streaks that are longer than five in a
row. Most people cannot tolerate long losing streaks. When they
occur, they totally abandon what they are doing. In such a system
you could easily have 25 consecutive losses. At that point you
become certain that your system is broken, and you try something
else.
Let's look at the opposite end. Suppose you got to be right 90% of
the time. Suppose your average win was $100 and that your average
loss was $2,000. This means that you'd have a total of $9,000 in
winnings and $20,000 in losses. You would lose $11,000. Would people
trade that system? Yes, they would. They would probably trade it for
a number of years until they went bankrupt. Why? Because they get to
be right most of the time and that is very rewarding.
You might be saying, but how could people possibly tolerate losses
of $11,000 after 100 trades? It is easy; they turn the losing trade
into a long-term investment in their mind and say, "it's only a
paper loss." For example, I've had workshop attendees who were
probably way above average in terms of sophistication. However, I
asked them to raise their hands if they had an investment in their
portfolio that was only worth 50% or less of what they paid for it.
Eleven people raised their handsover a fourth of the class. And my
guess is that among the overall population of investors, most people
are sitting on a number of big losers, hoping they will come back.
Why? Because they cannot stand to be wrong on an investment and they
are waiting to be right on those losing trades.
What is the cost of having losing investments in your portfolio?
It's major. First, you are using valuable capital up with
nonproductive investments. Second, you are missing many good
opportunities.
Why Being Right Seems So Important
There are two primary reasons why we focus on being right. First, we
are conditioned to be right by the school system. Second, everyone
in the trading industry gives people what they wantways to be right
which tends to perpetuate the myth. Let's take a closer look at
these two reasons.
First, we are conditioned by the school system to the importance of
being right. In school you are taught that there are right answers
and wrong answers. What is a right answer? If you learned how to
survive in the system, you learned that a "right" answer is whatever
the teacher wanted.
Your performance is measured periodically through tests in which you
are asked to pick the right answer. If you cannot get more than 70%
right on the test, you are labeled a failure and ostracized. Your
humiliation might even be in public in front on all your friends.
And if your humiliation isn't public, it certainly is semipublic.
Your "poor" performance goes home in the form of a grade with a
comment that "Johnny is a little slow or Johnny is bright, but he
just doesn't try." Usually, at this point, the most important people
in your young life get involvedyour parents.
Even if you understand the system and work hard to know the right
answers, you still might be taught that your performance is not good
enough. It usually takes 94% right to get an excellent grade. But
how many children go home and show their 94% test to dad only to get
the response, "Why didn't you get 100%?"
Thus, it is no wonder that traders want to be right all the time.
And being right usually costs them dearly in terms of profits.
Whether you've been through 20 years of schooling and have a
graduate degree or less than 10 years of schooling, you still have
the same conditioning about being right.
The second reason people want to be right is that service providers
for traders and investors feed the bias to be right. First, software
vendors tend to provide systems that can be highly optimized. Once
you've optimized your trading, you can lay a line over the prices
and see exactly where you should have bought and sold. It seems
obvious. However, the same optimized system does very poorly when
applied to the real world.