Praise for Trading from Your Gut

Augmenting Intellect and Analysis
Nevertheless, even for intuitive whole-mind traders, software
can be a useful tool. It can help the intellect validate components of
the intuition’s trading ideas. Most real-time charting software can
also alert you to potential trades. It can help you filter the enormous
amounts of information contained in historical market price data.
Sophisticated backtesting software can test some less complex
methods, and it can test pieces of intuitive trading concepts. 
For example, you might not be able to program backtesting soft-
ware to exactly recognize support and resistance, but you could test
an approximation of parts of this idea to explore the profitability of
the rebound swing method. Because testing software can’t exactly
capture the concept of support and resistance, the results from his-
torical testing won’t match what you might have achieved using your
intuition. Nevertheless, these sorts of tests are useful because they
often help you find weaknesses in a particular method that might
not have been obvious from looking only at the charts.
For fuzzy concepts that are hard to capture exactly, I use histor-
ical testing tools to test ideas that are approximations of the fuzzy
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concept. I try as many approximate rule sets as I can come up with.
If they all test well and in similar ways, this is a good sign that the
fuzzy intuitive concept itself is valid. If you try several different rule-
based approximations for particular intuitive-entry concepts, and
each of these approximations appears to demonstrate a significant
trading edge, then you can have a lot more intellectual faith in your
approach. So even though the concepts might be fuzzy and based on
right-brain visual perception, you can use technology to explore the
profitability of the ideas. 
One of the best ways to do this test of parts is to separate the
entry criteria from the rest of the method steps. I like to run tests
that examine the amount the price moves in the trade’s favor, as
compared with how much it moves against the trade within a certain
number of days after entry. In technical terms, I look for the maxi-
mum favorable excursion (MFE) adjusted for volatility, divided by
the maximum adverse excursion (MAE) adjusted for volatility. I call
this measure the edge ratio. After a test, this measure might indi-
cate that within five days of the entry, a stock moves an average of
two times as far in the desirable direction as it does in the undesir-
able direction. This measure gives you a pretty good feel for the
opportunity for significant profit potential. If a stock moves signifi-
cantly more in the desired direction after you enter than it does in
the opposite direction for the first several days, this is a positive sign
for a swing-trading system.
Another approach that works is to test entry ideas using a very
simple exit strategy such as the one I suggested for the rebound
swing method. Then you can examine the profitability of the trades
using the approximate entry criteria. If these trades are profitable,
this should give you greater intellectual confidence in the fuzzy
method that the entry rules attempt to approximate.
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An additional valuable technique is to visually examine all the
trades that meet the approximate conditions. This enables you to
see how well your approximate rules match the fuzzy idea you are
trying to model. When you can see the trades themselves, you can
get a more intuitive feel for how the concept you are analyzing
works. This procedure might also give you ideas for how you can
improve the approximation. Sometimes it also suggests ways to
improve the overall method.
This is one of the ways intellect and analysis can validate intu-
ition. If you can use software tools to help your analysis, that’s even
better. Just remember, if it is too easy a concept to program into the
computer, other people likely will have found the idea, making it
potentially less profitable.