the possible outcomes of those steps, and
so on, right down to when you would want
to close out the trade. Despite the name,
decision trees take the decisions out of the
In game-theory geek-speak, the sequences of steps are called “nodes.” After
building a decision tree, you play the game
in reverse. You know the endpoint (end
node) of each path in the sequence, so you
could let the game play itself. It’s like a
chess master who looks at the board and
knows the best response to an opponent’s
any move. That’s because the chess master
has played the game in reverse, all the way
back to that current spot in the game, from
each possible node.
On the bright side, your trade’s life
cycle won’t have as many possible paths
as a chessboard. Your tree won’t involve
thousands of nodes—just a few. Yet, the
concept is the same: Build the scenarios
and possibilities, and let things run their
course. When decision time comes, con-
sult the tree.
e’ve all been
got the best-laid
plans for your
trades. Yet, you
know in your
heart you can’t
win ’em all. Some-
times even your most solid ideas go south.
But you also know the importance of an
exit strategy. When you get in, what are
your chances of getting out with a profit?
And if the trade goes against you, what’s
your pain point on the downside? Do you
have a time limit, a dollar limit, or both?
Game theory might conjure images of
math PhDs crunching complex equations.
But at a basic level, it’s just codifying what
you do every trading day—infusing your
decisions with logic, reasoning, and yep, a
bit of math. It all starts with the “decision
tree”—a map of a trade’s possible outcomes. This includes steps you might take,
BUILDING THE TREE
Let’s say you put on a trade in hopes of making a profit. Although dealing with profit is
a part of any trade’s decision tree, let’s focus
for now on losing positions—decisions that
must be made when a trade goes against
those profitable expectations. Or as a famous boxing champ once quipped, “
Everybody has a plan until they get punched in
the mouth.” Here’s how to build a decision
tree for a trade that gut punches you.
Say you just bought a stock. Perhaps you
spotted a nice trend setup and decided it
was time to jump on it. Turns out you were
wrong. You entered too early and find yourself in a losing position. Now what?
Because losses typically come in two
varieties—either you lose a little, or you lose
a lot—those become the first two nodes of
With the first set of nodes in place,
you could build the next layer. For each
of the two loss scenarios, consider these
questions. First, how quickly did the stock
move? Was it swift and severe or a slow
SMALL LOSS BIG LOSS
REASON FOR LOSS?
If your objective changes, close position; otherwise check vol.
HIGH VOL? LOW VOL? HIGH VOL? LOW VOL?
OR SELL CALL SELL CALL HOLD BUY PUT
OF A TRADE
USING A DECISION TREE.
For illustrative purposes only.