def get_ytw_from_date(fromdate, srcfile=r'src/YTW-All-Values.xlsx'):
'''
load data from source file into dataframe
columns:
Corp - corporate bond rate
TB - treasury bond rate
CS - credit spread
Econ - economic data
'''
import nb_credit_spread as cslibrary
cslib = cslibrary.creditspread()
return cslib.get_ytw_from_date_delta(srcfile=srcfile)
import pandas as pd
import cs_logger as cslog
source_file = srcfile
src_file = pd.read_excel(source_file,
sheet_name='data',
header=0,
index_col='Date')
ytw_df = pd.DataFrame(src_file)
ytw_df = ytw_df.asfreq(pd.infer_freq(
ytw_df.index)) # infer data frequency; monthly
start_date = pd.to_datetime(fromdate)
ytw_df = ytw_df[start_date:] # filter records by date
cslog.debug(f"df: {ytw_df.head()}")
return ytw_df
def __run_adf_stat_p_value(logDest):
import datetime
import cs_data_analysis as cs
import cs_logger as cslog
log = setlogfile(logDest)
try:
now = datetime.datetime.now()
log.info(f"{'-'*10} start {now:%Y-%m-%d %H:%M} {'-'*10}")
import nb_credit_spread as cslibrary
cslib = cslibrary.creditspread()
srcfile = r'src/YTW-All-Values.xlsx'
df = cslib.get_ytw_from_date_delta(srcfile=srcfile, start='2009-01-31')
cs.adf_stat_p_value(df)
log.info(f"{'-'*10} done {'-'*10}")
assert True
except:
import sys
message = f"Unexpected error: {sys.exc_info()[0]} {sys.exc_info()[1]}"
log_error = setlogfile(logDest, logging.ERROR)
log_error.error(message)
raise
def test_arima_model():
'''
unit test for arima
'''
import cs_data_analysis as cs
import cs_logger as cslog
import logging
log = setlogfile(cslog.arima_model_log)
try:
import nb_credit_spread as cslibrary
cslib = cslibrary.creditspread()
srcfile = r'src/YTW-All-Values.xlsx'
df = cslib.get_ytw_from_date_delta(srcfile=srcfile, start='2009-01-31')
return
log.info('**** AR(1) ****')
cs.print_full(cs.arima_model(df), log)
log.info('**** AR(1) diff period 1 ****')
cs_df = cs.get_ytw_from_date(
'1989-12-31') # fetch month before 31 Jan 1990
cs_df = cs_df.diff(periods=1) # diff with previous period
cs_df = cs_df[
'1990-01-31':] # get only records from 31 Jan 1990; this avoids NaN in first row
cs.print_full(cs.arima_model(cs_df), log) # get AR(1) coefficients
assert True
except:
import sys
message = f"Unexpected error: {sys.exc_info()[0]} {sys.exc_info()[1]}"
log.error(message)
raise
def test_lag_selection():
import cs_logger as cslog
log = setlogfile(cslog.lag_selection_log)
try:
import cs_data_analysis as cs
import cs_lag_selection as lag
import datetime
now = datetime.datetime.now()
log.info(f"{'-'*10} start lag selection {now:%Y-%m-%d %H:%M} {'-'*10}")
import nb_credit_spread as cslibrary
cslib = cslibrary.creditspread()
srcfile = r'src/YTW-All-Values.xlsx'
ytw = cslib.get_ytw_from_date_delta(srcfile=srcfile,
start='2009-01-31')
cs = [
'CS-Aaa', 'CS-Aa', 'CS-A', 'CS-Baa', 'CS-DCF-Aaa', 'CS-DCF-Aa',
'CS-DCF-A', 'CS-DCF-Baa'
]
tb = ['3MO', '1YR', '5YR']
for i in cs:
for j in tb:
lag.call_lag_selection(ytw, f"{i}-{j}", f"TB-{j}-TY")
lag.call_lag_selection(ytw, f"{i}-{j}-diff", f"TB-{j}-TY")
return
except:
import sys
log.error(f"Unexpected error:", sys.exc_info()[0], sys.exc_info()[1])
raise
def test_summary_stats_full():
'''
unit test for summary stats
'''
import cs_data_analysis as cs
import cs_logger as cslog
import logging
log = setlogfile(cslog.summary_stats_full_log)
try:
import nb_credit_spread as cslibrary
cslib = cslibrary.creditspread()
srcfile = r'src/YTW-All-Values.xlsx'
ytw_df = cslib.get_ytw_from_date_delta(srcfile=srcfile,
start='2014-01-31')
cs_stats, cs_stats_p1 = cs.summary_stats_full(ytw_df)
log.info('**** cs stats ****')
cs.print_full(cs_stats, log)
log.info('**** cs stats p1 diff ****')
cs.print_full(cs_stats_p1, log)
assert True
except:
import sys
log.error(f"Unexpected error:", sys.exc_info()[0], sys.exc_info()[1])
raise
def get_ytw_test():
import os
print(os.getcwd())
import nb_credit_spread as cslibrary
import logging
cslib = cslibrary.creditspread()
srcfile = 'src/YTW-All-Values.xlsx'
srcfile = 'YTW-All-Values.xlsx'
srcfile = f"{os.getcwd()}/src/YTW-All-Values.xlsx"
start_date = '2009-01-31'
return cslib.get_ytw_from_date_delta(srcfile=srcfile, start=start_date)
def test_summary_stats():
'''
unit test for summary stats
'''
import cs_data_analysis as cs
import cs_logger as cslog
import logging
import nb_credit_spread as cslibrary
cslib = cslibrary.creditspread()
srcfile = r'src/YTW-All-Values.xlsx'
ytw_df = cslib.get_ytw_from_date_delta(srcfile=srcfile, start='2014-01-31')
cs.print_full(cs.summary_stats(ytw_df),
setlogfile(cslog.summary_stats_log))
assert True
def test_causation():
'''
'''
import cs_data_analysis as cs
import cs_logger as cslog
log = setlogfile(cslog.causation_log)
try:
import nb_credit_spread as cslibrary
cslib = cslibrary.creditspread()
srcfile = r'src/YTW-All-Values.xlsx'
ytw_df = cslib.get_ytw_from_date_delta(srcfile=srcfile,
start='2009-01-31')
cs.print_full(cs.causation(ytw_df), log)
assert True
except:
import sys
log.error(f"Unexpected error:", sys.exc_info()[0], sys.exc_info()[1])
raise
def test_get_model_results():
from statsmodels.tsa.arima.model import ARIMA
import nb_credit_spread as cslibrary
cslib = cslibrary.creditspread()
start_date = '2009-01-31' #'1990-01-31' # '2009-01-31'
ytw_delta = cslib.get_ytw_from_date_delta(
start=start_date, srcfile='src/YTW-All-Values.xlsx')
endog_col = 'CS-Aaa-3MO-DCF'
order = (1, 1, 0)
endog, exog = ytw_delta[endog_col], None
model = ARIMA(endog=endog, exog=exog, order=order, trend='ct')
model_fit = model.fit()
import logging
# log = setlogging('test_get_model_results', logging.INFO)
log = old_setlogger('test_get_model_results', logging.INFO)
# logging.getLogger('test_get_model_results').info('test')
log.info(model_fit.summary())
if (log.hasHandlers()):
log.handlers.clear()
def test_causation_cs_pce():
import cs_data_analysis as cs
import cs_logger as cslog
log = setlogfile(cslog.causation_log)
try:
import nb_credit_spread as cslibrary
cslib = cslibrary.creditspread()
srcfile = r'src/YTW-All-Values.xlsx'
ytw_df = cslib.get_ytw_from_date_delta(srcfile=srcfile,
start='2009-01-31')
df = ytw_df[['CS-Aaa-3MO', 'Econ-PCE']]
from cs_causation import grangers_causation
r = grangers_causation(df)
# print(r)
cs.print_full(r, log)
assert True
except:
import sys
log.error(f"Unexpected error:", sys.exc_info()[0], sys.exc_info()[1])
raise
