I have a dataframe created by pipeline with daily data and I would like to merge it with minute pricing data like so:
# Get asset forward returns and quantile classification
# based on sentiment scores
factor_data = al.utils.get_clean_factor_and_forward_returns(
factor=earnings,
prices=asset_prices,
quantiles=5,
periods=(1,5,10),
)
factor_data.head()
This produces an error obviously, since the timing does not match:
ValueError: Factor and prices indices don't match: make sure they have the same convention in terms of datetimes and symbol-names
Is there a way to convert the pipeline to minute frequency?
This is how I create asset_prices::
Get list of unique assets from the pipeline output
asset_list = earnings.index.levels[1].unique()
Query pricing data for all assets present during
evaluation period
asset_prices = prices(
asset_list,
start=period_start,
end=period_end,
frequency='minute'
)
asset_prices.head()
