Hi Sam,

Your code looks great and you happened to run into a rough edge of the platform. When using order_target functions, they don't open orders into consideration when making their calculation.

For example, let's say you own 100 shares of ABC and run the command "order_target(symbol('ABC'), 0)" to close the position. This sends a sell order of 100 shares. However, ABC might be an semi-liquid stock, so only 40 shares are sold in the next bar. This leaves 60 shares existing in your portfolio. In the next bar, your handle_data() runs again, and your algo submits the same command, order_target to 0, which is a sell order of 60 shares. However, it still had an open order of selling 100 shares from earlier! This will cause you to over-sell, and inadvertently take a short position.

To prevent this, you should check for open orders before you send new orders (on line 27). Like so:

if get_open_orders:  
   continue  

Here's another thread with more info: https://www.quantopian.com/posts/order-target-percent-ordering-too-much

Excellent, thank you for the help.

One more question, and this one is a bit more out of left field. Say i have a set of moving averages VMAS and VMAL:

def initialize(context):
context.stocks = symbols('SPY')

context.security = symbol('SPY')  

def handle_data(context, data):
VMAS = data[context.security].mavg(2)
VMAL= data[context.security].mavg(30)

Is it possible to get a moving average and std.dev of a ratio of moving averages? IE:
Mavgception = (VMAS / VMAL).mavg(30)
Std.devception = (VMAS/VMAL).stddev(30)

The .mavg() and .stddev() built-ins only apply to securities in our database, and can't be run on custom variables. Instead, you can use the pandas library to calculate those values. Take a look at: http://pandas.pydata.org/pandas-docs/stable/basics.html