Ultimate Algorithmic Trading System

TABLE 8.8
Distribution Statistics from Monte Carlo Simulations
Final Equity Annual Return Max. Drawdown $ Max. Drawdown % Lowest Eq.
1% 5706 −7.37% 1302 7.23% 3618
5% 7987 −3.02% 1549 9.76% 5853
10% 9706 −0.41% 1726 11.32% 6690
25% 12851 3.48% 2136 14.38% 8107
50% 16174 6.78% 2747 19.77% 9135
75% 19632 9.64% 3563 27.63% 9640
90% 23258 12.21% 4626 38.48% 9922
95% 25269 13.48% 5292 45.47% 10000
99% 29139 15.71% 7685 63.82% 10000
■ Start Trade Drawdown
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GENETIC OPTIMIZATION, WALK FORWARD
The maximum drawdown metric that is derived from backtesting is a key component
used to help a trader judge the capitalization requirements of a particular trading
algorithm. If an algorithm suffers a $50,000 drawdown, it logically follows that this
event could occur again in the future. And accordingly the trader should allocate
at least $50,000 to his trading account. What if the algorithm is very good and
this one event doesn’t cast it in a good light? What if the drawdown follows a
large runup? In this case, the drawdown is somewhat a function of the system’s
success. Another drawdown metric, start trade drawdown, can help shed light on
an algorithm’s drawdown structure. A trader is most sensitive to drawdown when
she initially starts to trade a new algorithm. A $50,000 drawdown that decimates a
trader’s account right off the bat is completely different than a $50,000 drawdown
that occurs after a $200,000 runup. Wouldn’t it be nice to know the probability of
having a huge drawdown at the beginning of trading? Also wouldn’t it be nice to
know the probability of the maximum drawdown occurring again in the future for
capitalization purposes? This concept of Start Trade drawdown can be attributed to
Keith Fitschen. He describes it on his website, www.keithstrading.com, and in his
book, Building Reliable Trading Systems (Wiley, 2013, New Jersey). Let’s assume you
have a trading algorithm that trades 100 times. Would a trader starting at trade #1
have a different drawdown than a trader starting at trade #50? This is a very good
question and I guess Mr. Fitschen asked himself this exact same question. You could
simply analyze the drawdowns that occur after trade #1 and the drawdowns that
occur after trade #50 and answer the question. What if there was an analysis that
could provide the probabilities of different drawdown magnitudes derived from the
historical results of a trading algorithm? This could definitely help a person decide if
a system is worth the risk, and at the same time know how much capital would be
required to fund it. Well, thanks to Keith Fitschen, we have this analysis.
www.rasabourse.com