bondret

Retrieve and process data from WRDS Bond Returns File

Since this is a proprietary dataset, in the documentation below, I can not show any of the data that is being retrieved/generated (will show only column names).

from __future__ import annotations
from typing import List

import pandas as pd
import numpy as np

import pandasmore as pdm
from finsets.wrds import wrds_api

PROVIDER = 'Wharton Research Data Services (WRDS)'
URL = 'https://wrds-www.wharton.upenn.edu/pages/get-data/wrds-bond-returns/'
LIBRARY = 'wrdsapps'
TABLE = 'bondret'
LINK_TABLE = 'bondcrsp_link'
FREQ = 'M'
MIN_YEAR = 2002
MAX_YEAR = None
ENTITY_ID_IN_RAW_DSET = 'permno'
ENTITY_ID_IN_CLEAN_DSET = 'permno'
TIME_VAR_IN_RAW_DSET = 'date'
TIME_VAR_IN_CLEAN_DSET = f'{FREQ}date'

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list_all_vars

 list_all_vars ()

Collects names of all available variables from WRDS f{LIBRARY}.{TABLE}.

all_vars = list_all_vars()

all_vars.head()

	name	type	wrds_library	wrds_table
0	date	DATE	wrdsapps	bondret
1	issue_id	DOUBLE_PRECISION	wrdsapps	bondret
2	cusip	VARCHAR(9)	wrdsapps	bondret
3	bond_sym_id	VARCHAR(14)	wrdsapps	bondret
4	bsym	VARCHAR(12)	wrdsapps	bondret

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parse_varlist

 parse_varlist (vars:List[str]=None, required_vars=[])

Validates that vars are available in {LIBRARY}.{TABLE} table and adds a. prefixes to variable names to feed into an SQL query

parse_varlist()

'a.date,a.issue_id,a.cusip,a.bond_sym_id,a.bsym,a.isin,a.company_symbol,a.bond_type,a.security_level,a.conv,a.offering_date,a.offering_amt,a.offering_price,a.principal_amt,a.maturity,a.treasury_maturity,a.coupon,a.day_count_basis,a.dated_date,a.first_interest_date,a.last_interest_date,a.ncoups,a.amount_outstanding,a.r_sp,a.r_mr,a.r_fr,a.n_sp,a.n_mr,a.n_fr,a.rating_num,a.rating_cat,a.rating_class,a.t_date,a.t_volume,a.t_dvolume,a.t_spread,a.t_yld_pt,a.yield,a.price_eom,a.price_ldm,a.price_l5m,a.gap,a.coupmonth,a.nextcoup,a.coupamt,a.coupacc,a.multicoups,a.ret_eom,a.ret_ldm,a.ret_l5m,a.tmt,a.remcoups,a.duration,a.defaulted,a.default_date,a.default_type,a.reinstated,a.reinstated_date'

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get_raw_data

 get_raw_data (vars:List[str]='*', required_vars:List[str]=['cusip',
               'date'], nrows:int=None, start_date:str=None,
               end_date:str=None)

Downloads vars from start_date to end_date from WRDS {LIBRARY}.{TABLE} library and adds PERMNO and PERMCO

	Type	Default	Details
vars	List[str]	*	Downloads all available variables by defaul
required_vars	List[str]	[‘cusip’, ‘date’]	list of variables that will get downloaded, even if not in vars
nrows	int	None	Number of rows to download. If None, full dataset will be downloaded
start_date	str	None	Start date in MM/DD/YYYY format
end_date	str	None	End date in MM/DD/YYYY format
Returns	pd.DataFrame

raw = get_raw_data(nrows=1000)

raw.head(0)

	permno	permco	date	issue_id	cusip	bond_sym_id	bsym	isin	company_symbol	bond_type	...	ret_ldm	ret_l5m	tmt	remcoups	duration	defaulted	default_date	default_type	reinstated	reinstated_date

0 rows × 60 columns

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process_raw_data

 process_raw_data (df:pandas.core.frame.DataFrame=None,
                   clean_kwargs:dict={})

Applies pandasmore.setup_panel to df

	Type	Default	Details
df	pd.DataFrame	None	Must contain permno and datadate columns
clean_kwargs	dict	{}	Params to pass to pdm.setup_panel other than panel_ids, time_var, and freq
Returns	pd.DataFrame

df_clean = process_raw_data(raw)

df_clean.head()

		date	dtdate	permco	issue_id	cusip	bond_sym_id	bsym	isin	company_symbol	bond_type	...	ret_ldm	ret_l5m	tmt	remcoups	duration	defaulted	default_date	default_type	reinstated	reinstated_date
permno	Mdate
26403	2002-07	2002-07-31	2002-07-31	20587	383238.0	00072AAA8	DIS.GA	None	US00072AAA88	DIS	CDEB	...	NaN	NaN	6.641667	14.0	4.797721	N	None	None	None	None
	2002-08	2002-08-31	2002-08-31	20587	383238.0	00072AAA8	DIS.GA	None	US00072AAA88	DIS	CDEB	...	NaN	0.015265	6.555556	13.0	4.928041	N	None	None	None	None
	2002-10	2002-10-31	2002-10-31	20587	383238.0	00072AAA8	DIS.GA	None	US00072AAA88	DIS	CDEB	...	NaN	NaN	6.386111	13.0	4.721617	N	None	None	None	None
	2002-11	2002-11-30	2002-11-30	20587	383238.0	00072AAA8	DIS.GA	None	US00072AAA88	DIS	CDEB	...	NaN	0.062946	6.302778	13.0	4.714069	N	None	None	None	None
	2003-02	2003-02-28	2003-02-28	20587	383238.0	00072AAA8	DIS.GA	None	US00072AAA88	DIS	CDEB	...	NaN	NaN	6.052778	12.0	4.673783	N	None	None	None	None

5 rows × 60 columns