source = inputs["source"]
""" Choose Pricing Source
"""
fx_name = "FX_Rate"
s_name = "Rate_History"
s_fx_name = "FX_Curve_History"
s_opt_name = "Vol_Surface"
sheet_name = "Pricer"
opt_source = "LIVE"
db_name = "Yield_Curve"
# Spot FX market
fx_spot = reader.read_FX_rates(fx_name)
# Libor rate market
cv_instrument = reader.read_instruments(s_name, 8)
# FX rate market
cv_fx_instrument = reader.read_instruments(s_fx_name, 8)
""" Start Pricing and Setting up pricing objects
"""
disc_cv_details = {"type": "LIBOR", "spread": 0}
reader.close() # Reslease workbook
Pricer = Pricer.FXer(cv_instrument, cv_fx_instrument, fx_spot, "")
inst = Pricer.gen_fx_instruments(inputs)
NPV = Pricer.get_ans(inst, val_date, npv_date)
""" Start pricing and output to Pricer sheet
"""
# Writting to excel
}
convention = { instruemtns convention }
Day_Counter = function of year fraction
"""
from IO import Reader as reader
from curve import Day_Counter_func as Day_Counter
from curve import Boot_Strapping as B_S
from curve import Boot_Strap_Tools_Func as BS_TF
import pandas as pd
""" Get raw data
"""
f_name = "Raw_Inputs.xlsx"
s_name = "Data"
c_num, f_num, s_num = 5,7,100
reader = reader.excel_reader(f_name)
ccy, date, Cash, Future, Swap = reader.read_instruments(s_name)
instrument = {}
instrument["cash"] = [ Cash, c_num ]
instrument["future"] = [ Future, f_num ]
instrument["swap"] = [ Swap, s_num ]
""" Set up valuation date and currency
then generate the cure by bootstrapping
"""
value_date = date
currency = ccy
convention = convention_book[currency]
Day_Counter = Day_Counter.Day_Counter(convention["LIBOR_day_count"])
curve = B_S.boot_strapping_LIBOR( value_date,
convention,
instrument,
Day_Counter)
s_name = "Vol_Surface"
sdate = "2019-03-25"
schema_name = "Yield_Curve"
tb_opt = "vcub"
opt_source = "LIVE"
num = 4
Reader = Reader.excel_reader(f_name)
data = Reader.read_vol( s_name, num )
vol_s = Vol.Val_Surface( sdate,
schema_name,
tb_opt )
vol_s.get_raw_data( opt_source, data )
# Step two load option/swaption balance schedule
balance_name = "Schedule"
Reader.read( balance_name )
name, raw_data = Reader.get_raw_data()
cv_instrument = Reader.read_instruments("Rate_Live", 8)
disc_cv_details = { "type" : "LIBOR",
"spread" : 0 }
# Step three option/swaption pricing
OPT = OPT.OPTer( cv_instrument,
vol_s )
for nn in name:
if raw_data[nn]["itype"] in ("Floor","Cap"):
OPT.add( nn, raw_data[nn], disc_cv_details )
print(OPT.price_opt( nn, sdate ))