Matthew,

One approach would be to average open and close prices for a minute bar (i.e. add them and divide by two).

Grant

I had tried averaging the opening and closing prices but those were prices for the day. I am not sure how to use a minute bar in this average though but that sounds like something that might work.

You have to run the backtest in minutely mode. --Grant

Thanks so much! I am still not sure: will an average of open_price and close_price in minute mode use prices in that minute or will they use the price for when the market opened and closed that day still?

Hello Matthew,

When running in minute mode, the bars are minutely, so 'open' refers to the opening price of the bar (near the start of the minute), and 'close' is near the end (I'm reluctant to say exactly at the start and end points in time, since I don't know precisely how the bars are computed by Quantopian). Here's something to tinker with:

def initialize(context):  
    context.stocks = [sid(8554),sid(33652)]  
    context.averages = {}  
    for stock in context.stocks:  
        context.averages[stock] = []  
def handle_data(context, data):

    for stock in context.stocks:  
        o = data[stock].open_price  
        c = data[stock].close_price  
        context.averages[stock].append((o+c)/2)  
        print context.averages[stock]  

Not the best example of coding (likely inefficient, and may eventually hit a memory limit), but it hopefully illustrates the point.

Grant

Great, thank you so much!