schedule function to run specific code at specific times. Place any
schedule functions in the
initialize portion of one's algo. Check out the docs https://www.quantopian.com/docs/api-reference/algorithm-api-reference#quantopian.algorithm.schedule_function.
So, in this case, to run a function to cancel all orders at market close do something like this
Initialize constants, create pipeline, and schedule functions
# Cancel any open orders
# Do this at market close to suppress partial fill warnings
def cancel_all_open_orders(context, data):
Cancels all open orders
for security, open_orders in get_open_orders().items():
for order_object in open_orders:
While the 'failed to fill by the end of day' logging may be annoying, it is VERY informative. One should really modify their algo logic to mitigate this warning rather than ignore it. If an order fails to fill it implies your algo isn't in control. Ideally, one's algo should specify exactly how much of each stock to buy or sell. The backtester will then simulate what price the order fills at. If orders are being canceled, it means the backtester is essentially taking over the order quantity logic. Moreover, in live trading, there is the real potential that these orders will fill. The backtest results could therefore differ dramatically from actual results if there are a lot of these 'unfilled orders'. I would strongly recommend addressing any underlying issues in one's algorithm and ensure orders do all fill by the end of the day.
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