Ultimate Algorithmic Trading System

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One last bit of code that shows off the power of Python follows. After this, I will
demonstrate how to pull all this together and test a trading algorithm.
for i in range(0,len(masterDateList)):
cumuVal = 0
for j in range(0,len(self.systemMarkets)):
skipDay = 0
try:
idx = self.systemMarkets[j].equity.equityDate.
index(masterDateList[i])
except ValueError:
skipDay = 1
if skipDay == 0:
cumuVal += self.systemMarkets[j].equity.
dailyEquityVal[idx]
combinedEquity.append(cumuVal)
This snippet of code is important because two very important concepts are
covered. If you review the code, you will see the keyword try: The code controlled
by try is simply finding if and where the last day of a month is located in a
systemMarket’s equityDate stream. Let’s say we are trying to see if July 31,
2012, is in an equityDate list. If it is, then the variable idx returns the location
in the list. If it’s not located in the list, then an error is returned. This is where
except comes into play. The code controlled by except is only executed if the
method index returns an error. Back to the Python Shell!
Type the following and hit enter after the last line:
>>> a = list()
>>> a = [100,300,200,800]
>>> a.index(300)
1
This example returns the location of the number 300 in the a list. Remember Python
is zero based. The first element is number 0.
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USING PYTHON TO BACKTEST YOUR ALGORITHM
■ Getting Down to Business
Okay, we now have somewhat of an understanding of how the PSB works. I designed
it to be like one of those calculators or watches that is encased in see-through plastic.
Everything is there if you just look for it. However, just like the watch or calculator,
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