There's a section in the Help & API Docs titled History (https://www.quantopian.com/help#ide-history) that discusses how to get historical low/high etc prices for securities. You can define the number of days you want to include in your history look up by setting "bar_count" as a parameter to the history function. This will return a pandas DataFrame to which you can apply the standard pandas transforms. e.g. calculating a 5-day moving average (from the docs where price_history.mean() gives you a 5-day rolling moving average):
def handle_data(context, data):
price_history = history(bar_count=5, frequency='1d', field='price')
In your case, you can change the field parameter from 'price' (which gives you closing prices) to 'low' or 'high'.