0.2) or 30 percent (3 / 10 0.3), which is a difference of 50 percent (20 / 30 1
0.5). Should you change in the middle of a trade?
Furthermore, assuming there is something to the logic behind this method,
still not everything is what it seems to be. Just because a stock seems to have been
priced around $5 way back when, that most likely wasn’t the case at the time. Take
Microsoft, for example. Looking at any chart updated today it seems as if the stock
traded at $5 in 1993 to 1994. But the only reason why that seems to be the case is
because the stock has been split several times, and the historical price has been
adjusted down. In real life, in 1993 to 1994, Microsoft traded around $80. And
even though the price has been adjusted down, the behavior is still baked into the
historical bars. This reasoning is also closely related to what we said about split-
adjusted prices in Chapter 2.
Also, in the case of Microsoft and other highly liquid and highly traded
stocks, I doubt the behavior will change that much, no matter the actual price.
Consequently, the best you can do when back testing a system is to treat every
stock the same all the time and exactly as all other stocks, no matter the price. This
method doesn’t do that, and even though it might have its merits, it is not the best
way to go for back testing robust trading systems.
Wrong method No. 2 takes less explanation to dismiss. This method states
that you should never risk more than a specified amount of your trading capital in
any trade. For example, in the commodity futures markets, many system vendors
recommend that you should not risk more than $2,000 on any trade. What is that
all about? While it is prudent not to risk too much, the market doesn’t give a hoot
if you can’t afford to risk more than a specified amount on each trade. Instead, the
market will do what the market will do, and if you can’t adjust your maximum
allowed loss to the conditions that the market gives you, then the prudent thing to
do is not to trade. Period.
As already mentioned in Chapter 1, depending on the market value of the
market and the long-term trend, the effect of such a stop is that it will have you
stopped out time and time again on a high-priced market, but hardly ever on a low-
priced market. It will be too tight for the high-priced market, but too wide for the
low-priced market, in relation to the respective markets’ normal price swings.
Therefore, this system design blunder also can result in two opposite types
of drawdowns (or at least unwanted system characteristics), both of them very
hard to detect because they’re masking each other. In the case of the low-priced
market, a larger than necessary drawdown can be a result of a few but larger than
necessary losers, while in the case of the high-priced market, a larger than nec-
essary drawdown can be a result of a large amount of unnecessary small losers.
Not knowing this, you might only worsen the effects from one type of drawdown
while addressing the other. Stick to a strategy like this and you will be broke
before you can say honorificabilitudinitatibus (the longest word ever used by
Shakespeare).208 PART 3 Stops, Filters, and Exits