Ultimate Algorithmic Trading System

function modules and some are a little more sophisticated and are programmed as
a class structure. I said you would be exposed to procedural (functions) and objectoriented
(classes) programming. Let’s start slowly with a simple indicator function.
sAverage
def sAverage(prices,lookBack,curBar,offset):
result = 0.0
for index in range((curBar - offset) - (lookBack-1),
curBar - offset +1):
result = result + prices[index]
result = result/float(lookBack)
return result
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USING PYTHON TO BACKTEST YOUR ALGORITHM
This looks pretty palatable! All functions or, if you like, subprograms, use the
key word def to let the interpreter know a function is about to be defined. The
function has to have a name, and in this case it is sAverage (simple moving average).
Remember how we called functions in AFL and VBA? You do it exactly the same way
in Python. The list of arguments or parameters that are included in the parentheses
after the function name are known as the formal argument list. These parameters are
called formal because they’re included in the function definition. Since we are using
Python you don’t need to employ function prototyping or forward declaration.
In other words, you don’t need to tell the interpreter the types of the arguments
before-hand. The sAverage function requires four parameters:
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prices. This is a list of price data (open, high, low, close, volume, or open
interest). In this application of Python, we will be using the word list instead of
array, but know they mean basically the same thing. The Python list structure is
very powerful as you will find out.
lookback. The number of days in the calculation of the indicator. This would
equate to 20 in a 20-day moving average.
curBar. Simply the historic bar being evaluated.
offset. Just like the ESB, this number will usually be set to one. The indicator
value from the prior day. You can go offset with a more positive number. If you
use two, then it will return the indicator value form two days prior.
Notice the colon (:) at the end of the function definition. The colon tells the
interpreter that the indented code (four spaces) below is controlled by the current
line. So everything that is indented below the function definition header is included
in the function. Indentation is very important in Python. Don’t use tabs to indent;
simply hit the spacebar four times. Don’t forget this—spacebar four times. Things
will become much clearer very quickly.
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