Ultimate Algorithmic Trading System

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[Trade #]
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FIGURE 8.10 Monte Carlo Straw Broom chart of multiple randomized equity curves.
ahead and accept the default settings and click OK. AmiBroker creates a couple of
charts/reports that will illustrate the usefulness of this form of simulation. The first
chart is called a Straw Broom chart because of the way it looks (see Figure 8.10).
This is a representation of all of the alternate trade histories that were created
by using the random number generator. As you can see, most of the histories end
at different equity values and this is due to sampling with replacement. Had we not
allowed replacement, then all of the equity curves would end at the exact same spot.
The accumulation of all of the trades, irrespective of order, follows the commutative
law. You can easily see the boundary (top and bottom) histories that represent the
best and worst performance. The rest of the histories congregate in the middle
and create a cloud. This cloud is what you want to see from your own algorithm
simulation; many of the random histories created similar outcomes. AmiBroker also
creates the following table that provides the statistics derived from the distribution
of the simulation results (Table 8.8).
The first column shows the percentile level that certain observations fell. In
the first row 1% of all observations had profit levels below $5,706 and maximum
drawdowns below $1,302. These two events, based off of their probabilities, are
unlikely to happen again. Fifty percent of the time you could expect profits to be
less than or equal to $16,174 and maximum drawdown to be less than or equal
to $2,747. Ninety-nine percent of the time you could expect drawdowns below
$7,685. Keep in mind what we expect and what really happens doesn’t always jive.
We are basing all of our expectations on historical results, results that have a certain
level of built-in hindsight bias.
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