Hi Bryan, welcome! Below are several moving average strategies that people have shared in the community. You could use these to get a head start on your algorithm. If you have any questions, you can always ask for help in the forum.
As a tip, you should use pandas' mean function with history to get the moving average, rather than the IDE built-in mavg() function. You can see the full explanation in this thread here. This is a simple, contrived example to get the 20 min moving average.
# Get a trailing window of the last 20 min price data and create moving average
prices = history(20, '1m', 'price')
mavg = prices.mean()
if mavg[stock] < data[stock].price:
# hold 100 shares of the stock
order_target(stock, 100)
Examples using moving averages:
https://www.quantopian.com/posts/simple-moving-average-ratio-strategy
https://www.quantopian.com/posts/spy-200ma-backtest-w-slash-short
https://www.quantopian.com/posts/moving-strategy-on-3d-printing-companies
https://www.quantopian.com/posts/200ma-spy-backtest
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