Ultimate Algorithmic Trading System

Risk of Ruin Calculation
Average Win $
$400 ≪--Input Here
Average Loss $
$200 ≪--Input Here
Percent Wins
35.0% ≪--Input Here
Initial Capital $
$35,000 ≪--Input Here
Amount of Pain % (% of Capital)
50.0% ≪--Input Here
Payoff Ratio 2
Percent Losers 65.0%
Average Win % 1.1%
Average Loss % 0.6%
Sum of Possible Events (SoPE) 0.00029
Sq.Root of Sum of Squares of (SoPE) 0.00818
‘‘P’’ 0.517460757
RoR 1.39814%
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COMPLETE TRADING ALGORITHMS
This trend-following system wins only 35% of the time but has a payoff ratio
of 2 (Average Win$ / Average Loss$). If your pain threshold is 50% of your
starting capital, then you run a risk of ruin of nearly 1.4%. With these algorithm
performance metrics and RoR you shouldn’t have a problem pulling the trigger
on this system. Before you start trading be sure to check the risk of ruin and see
if it fits your expectations. One more note before we resume the battle: Money
management will not be utilized so that we can see the raw capabilities of each
system.
Resume the Battle There will be a total of six popular trend-following
algorithms tested, the Turtle system and the five shown in Box 3.3. Each test will
consist of three subtests. The subtests will reflect three different parameter sets
that will cause the algorithms to trade in a shorter-term, intermediate-term, and
longer-term manner. For example, a simple moving average crossover algorithm
will be tested utilizing moving average lengths of 19, 39, and 100. These parameters
should cover the three time horizons—short, intermediate, and long. The parameter
lengths were chosen without the benefit of hindsight—in other words, they were
chosen based on my perceived applicability to obtain the three time horizons without
looking at prior test results. This isn’t really a true statement, because my experience
through testing systems over the years does introduce a slight hindsight bias. All
entries and exits will be executed on the closing price of the bar that generates the
trade signal.
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