Hi,
I'm kinda new to both quantopian and python, and was wondering how in research environment I can get the say 20-weeks high of a stock, but I don't want daily prices to be considered, but getting the 20-weeks high only from 20 end of the week prices, i.e. weekly frequency.
and am I right to think that the way to go about researching on this is different from when writing the actual algorithm, i.e. different API are used?
Thanks,
Try this in IDE.
# --------------------------------
STOCK = symbol('SPY'); WEEKS = 20;
# --------------------------------
def initialize(context):
schedule_function(indicator, date_rules.week_end(), time_rules.market_close())
def indicator(context, data):
days = (WEEKS + 1)*5
OHLC = data.history(STOCK, ['open', 'high', 'low', 'close'], days, '1d')
OHLC_W = OHLC.resample('1W-FRI').agg({'open': 'first', 'high': 'max', 'low': 'min', 'close': 'last'})
HH_20W = OHLC_W['high'][-WEEKS:].max() # highest high 1W-FRI
HC_20W = OHLC_W['close'][-WEEKS:].max() # highest close 1W-FRI
print (HH_20W, HC_20W)
record(HH_20W = HH_20W, HC_20W = HC_20W) 
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