macrosynergy.panel.make_relative_value#

Implementation of make_relative_value() function as a module. The function is used to calculate values for indicators relative to a basket of cross-sections.

make_relative_value(df, xcats, cids=None, start=None, end=None, blacklist=None, basket=None, complete_cross=False, rel_meth='subtract', rel_xcats=None, postfix='R')[source]#

Returns panel of relative values versus an average of cross-sections.

Parameters:

  • df (DataFrame) – standardized JPMaQS DataFrame with the necessary columns: ‘cid’, ‘xcat’, ‘real_date’ and ‘value’.

  • xcats (List[str]) – all extended categories for which relative values are to be calculated.

  • cids (List[str]) – cross-sections for which relative values are calculated. Default is all cross-section available for the respective category.

  • start (str) – earliest date in ISO format. Default is None and earliest date for which the respective category is available is used.

  • end (str) – latest date in ISO format. Default is None and latest date for which the respective category is available is used.

  • blacklist (dict) – cross-sections with date ranges that should be excluded from the output.

  • basket (List[str]) – cross-sections to be used for the relative value benchmark. The default is every cross-section in the chosen list that is available in the DataFrame over the respective time-period. However, the basket can be reduced to a valid subset of the available cross-sections.

  • complete_cross (bool) – boolean parameter that outlines whether each category is required to have the full set of cross-sections held by the basket parameter for a relative value calculation to occur. If set to True, the category will be excluded from the output if cross-sections are missing. Default is False. If False, the mean, for the relative value, will use the subset that is available for that category. For instance, if basket = [‘AUD’, ‘CAD’, ‘GBP’, ‘NZD’] but available cids = [‘GBP’, ‘NZD’], the basket will be implicitly updated to basket = [‘GBP’, ‘NZD’] for that respective category.

  • rel_meth (str) – method for calculating relative value. Default is ‘subtract’. Alternative is ‘divide’.

  • rel_xcats (List[str]) – extended category name of the relative values. Will displace the original category names: xcat + postfix. The order should reflect the order of the passed categories.

  • postfix (str) – acronym to be appended to ‘xcat’ string to give the name for relative value category. Only applies if rel_xcats is None. Default is ‘R’

Return <pd.DataFrame>:

standardized DataFrame with the relative values, featuring the categories: ‘cid’, ‘xcat’, ‘real_date’ and ‘value’.