def __init__(self, fx_vol_surface=None, premium_output=market_constants.fx_options_premium_output,
delta_output=market_constants.fx_options_delta_output):
self._calendar = Calendar()
self._fx_vol_surface = fx_vol_surface
self._fx_forwards_pricer = FXForwardsPricer()
self._premium_output = premium_output
self._delta_output = delta_output
cross = 'AUDUSD'
fx_forwards_tenors = ['1W', '2W', '3W', '1M']
fx_forwards_to_print = ['1W', '2W']
# Get AUDUSD data for spot, forwards + depos
md_request = MarketDataRequest(start_date='01 Jan 2020', finish_date='01 Feb 2020',
data_source='bloomberg', cut='NYC', category='fx-forwards-market',
tickers=cross,
cache_algo='cache_algo_return', fx_forwards_tenor=fx_forwards_tenors,
base_depos_currencies=[cross[0:3], cross[3:6]])
market_df = market.fetch_market(md_request=md_request)
fx_forwards_price = FXForwardsPricer()
delivery_dates = Calendar().get_delivery_date_from_horizon_date(market_df.index, "8D", cal=cross)
interpolated_forwards_df = fx_forwards_price.price_instrument(cross, market_df.index, delivery_dates,
market_df=market_df, fx_forwards_tenor_for_interpolation =['1W', '2W'])
interpolated_forwards_df[cross + ".delivery"] = delivery_dates.values
print(interpolated_forwards_df)
market_cols = [cross + ".close"]
for f in fx_forwards_to_print:
market_cols.append(cross + f + '.close')
print(market_df[market_cols])
class FXOptionsPricer(AbstractPricer):
"""Prices various vanilla FX options, using FinancePy underneath.
"""
def __init__(self,
fx_vol_surface=None,
premium_output=market_constants.fx_options_premium_output,
delta_output=market_constants.fx_options_delta_output):
self._calendar = Calendar()
self._fx_vol_surface = fx_vol_surface
self._fx_forwards_pricer = FXForwardsPricer()
self._premium_output = premium_output
self._delta_output = delta_output
def price_instrument(self,
cross,
horizon_date,
strike,
expiry_date=None,
vol=None,
notional=1000000,
contract_type='european-call',
tenor=None,
fx_vol_surface=None,
premium_output=None,
delta_output=None,
depo_tenor=None,
return_as_df=True):
"""Prices FX options for horizon dates/expiry dates given by the user from FX spot rates, FX volatility surface
and deposit rates.
Parameters
----------
cross : str
Currency pair
horizon_date : DateTimeIndex
Horizon dates for options
expiry_date : DateTimeIndex
expiry dates for options
market_df : DataFrame
Contains FX spot, FX vol surface quotes, FX forwards and base depos
Returns
-------
DataFrame
"""
# if market_df is None: market_df = self._market_df
if fx_vol_surface is None: fx_vol_surface = self._fx_vol_surface
if premium_output is None: premium_output = self._premium_output
if delta_output is None: delta_output = self._delta_output
logger = LoggerManager().getLogger(__name__)
field = fx_vol_surface._field
# Make horizon date and expiry date pandas DatetimeIndex
if isinstance(horizon_date, pd.Timestamp):
horizon_date = pd.DatetimeIndex([horizon_date])
else:
horizon_date = pd.DatetimeIndex(horizon_date)
if expiry_date is not None:
if isinstance(expiry_date, pd.Timestamp):
expiry_date = pd.DatetimeIndex([expiry_date])
else:
expiry_date = pd.DatetimeIndex(expiry_date)
else:
expiry_date = self._calendar.get_expiry_date_from_horizon_date(
horizon_date, tenor, cal=cross)
# If the strike hasn't been supplied need to work this out
if not (isinstance(strike, np.ndarray)):
old_strike = strike
if isinstance(strike, str):
strike = np.empty(len(horizon_date), dtype=object)
else:
strike = np.empty(len(horizon_date))
strike.fill(old_strike)
# If the vol hasn't been supplied need to work this out
if not (isinstance(vol, np.ndarray)):
if vol is None:
vol = np.nan
old_vol = vol
vol = np.empty(len(horizon_date))
vol.fill(old_vol)
option_values = np.zeros(len(horizon_date))
spot = np.zeros(len(horizon_date))
delta = np.zeros(len(horizon_date))
intrinsic_values = np.zeros(len(horizon_date))
def _price_option(contract_type_, contract_type_fin_):
for i in range(len(expiry_date)):
built_vol_surface = False
# If we have a "key strike" need to fit the vol surface
if isinstance(strike[i], str):
if not (built_vol_surface):
fx_vol_surface.build_vol_surface(horizon_date[i])
fx_vol_surface.extract_vol_surface(
num_strike_intervals=None)
built_vol_surface = True
# Delta neutral strike/or whatever strike is quoted as ATM
# usually this is ATM delta neutral strike, but can sometimes be ATMF for some Latam
# Take the vol directly quoted, rather than getting it from building vol surface
if strike[i] == 'atm':
strike[i] = fx_vol_surface.get_atm_strike(tenor)
vol[i] = fx_vol_surface.get_atm_quoted_vol(
tenor) / 100.0
# vol[i] = fx_vol_surface.get_atm_vol(tenor) / 100.0 # interpolated
elif strike[i] == 'atms':
strike[i] = fx_vol_surface.get_spot(
) # Interpolate vol later
elif strike[i] == 'atmf':
# Quoted tenor, no need to interpolate
strike[i] = float(fx_vol_surface.get_all_market_data()[cross + ".close"][horizon_date[i]]) \
+ (float(fx_vol_surface.get_all_market_data()[cross + tenor + ".close"][horizon_date[i]]) \
/ self._fx_forwards_pricer.get_forwards_divisor(cross[3:6]))
# Interpolate vol later
elif strike[i] == '25d-otm':
if 'call' in contract_type_:
strike[i] = fx_vol_surface.get_25d_call_strike(
tenor)
vol[i] = fx_vol_surface.get_25d_call_vol(
tenor) / 100.0
elif 'put' in contract_type_:
strike[i] = fx_vol_surface.get_25d_put_strike(
tenor)
vol[i] = fx_vol_surface.get_25d_put_vol(
tenor) / 100.0
elif strike[i] == '10d-otm':
if 'call' in contract_type_:
strike[i] = fx_vol_surface.get_10d_call_strike(
tenor)
vol[i] = fx_vol_surface.get_10d_call_vol(
tenor) / 100.0
elif 'put' in contract_type_:
strike[i] = fx_vol_surface.get_10d_put_strike(
tenor)
vol[i] = fx_vol_surface.get_10d_put_vol(
tenor) / 100.0
if not (built_vol_surface):
try:
fx_vol_surface.build_vol_surface(horizon_date[i])
except:
logger.warn("Failed to build vol surface for " +
str(horizon_date) +
", won't be able to interpolate vol")
# fx_vol_surface.extract_vol_surface(num_strike_intervals=None)
# If an implied vol hasn't been provided, interpolate that one, fit the vol surface (if hasn't already been
# done)
if np.isnan(vol[i]):
if tenor is None:
vol[i] = fx_vol_surface.calculate_vol_for_strike_expiry(
strike[i], expiry_date=expiry_date[i], tenor=None)
else:
vol[i] = fx_vol_surface.calculate_vol_for_strike_expiry(
strike[i], expiry_date=None, tenor=tenor)
model = FinModelBlackScholes(float(vol[i]))
logger.info("Pricing " + contract_type_ +
" option, horizon date = " + str(horizon_date[i]) +
", expiry date = " + str(expiry_date[i]))
option = FinFXVanillaOption(self._findate(expiry_date[i]),
strike[i], cross,
contract_type_fin_, notional,
cross[0:3])
spot[i] = fx_vol_surface.get_spot()
""" FinancePy will return the value in the following dictionary for values
{'v': vdf,
"cash_dom": cash_dom,
"cash_for": cash_for,
"pips_dom": pips_dom,
"pips_for": pips_for,
"pct_dom": pct_dom,
"pct_for": pct_for,
"not_dom": notional_dom,
"not_for": notional_for,
"ccy_dom": self._domName,
"ccy_for": self._forName}
"""
option_values[i] = option_values[i] + option.value(
self._findate(horizon_date[i]), spot[i],
fx_vol_surface.get_dom_discount_curve(),
fx_vol_surface.get_for_discount_curve(),
model)[premium_output.replace('-', '_')]
intrinsic_values[i] = intrinsic_values[i] + option.value(
self._findate(expiry_date[i]), spot[i],
fx_vol_surface.get_dom_discount_curve(),
fx_vol_surface.get_for_discount_curve(),
model)[premium_output.replace('-', '_')]
"""FinancePy returns this dictionary for deltas
{"pips_spot_delta": pips_spot_delta,
"pips_fwd_delta": pips_fwd_delta,
"pct_spot_delta_prem_adj": pct_spot_delta_prem_adj,
"pct_fwd_delta_prem_adj": pct_fwd_delta_prem_adj}
"""
delta[i] = delta[i] + option.delta(
self._findate(horizon_date[i]), spot[i],
fx_vol_surface.get_dom_discount_curve(),
fx_vol_surface.get_for_discount_curve(),
model)[delta_output.replace('-', '_')]
if contract_type == 'european-call':
contract_type_fin = FinOptionTypes.EUROPEAN_CALL
_price_option(contract_type, contract_type_fin)
elif contract_type == 'european-put':
contract_type_fin = FinOptionTypes.EUROPEAN_PUT
_price_option(contract_type, contract_type_fin)
elif contract_type == 'european-straddle' or contract_type == 'european-strangle':
contract_type = 'european-call'
contract_type_fin = FinOptionTypes.EUROPEAN_CALL
_price_option(contract_type, contract_type_fin)
contract_type = 'european-put'
contract_type_fin = FinOptionTypes.EUROPEAN_PUT
_price_option(contract_type, contract_type_fin)
if return_as_df:
option_prices_df = pd.DataFrame(index=horizon_date)
option_prices_df[cross + '-option-price.' + field] = option_values
option_prices_df[cross + '.' + field] = spot
option_prices_df[cross + '-strike.' + field] = strike
option_prices_df[cross + '-vol.' + field] = vol
option_prices_df[cross + '-delta.' + field] = delta
option_prices_df[cross + '.expiry-date'] = expiry_date
option_prices_df[cross + '-intrinsic-value.' +
field] = intrinsic_values
return option_prices_df
return option_values, spot, strike, vol, delta, expiry_date, intrinsic_values
def get_day_count_conv(self, currency):
if currency in market_constants.currencies_with_365_basis:
return 365.0
return 360.0
def _findate(self, timestamp):
return FinDate(timestamp.day,
timestamp.month,
timestamp.year,
hh=timestamp.hour,
mm=timestamp.minute,
ss=timestamp.second)
def construct_total_return_index(self, cross_fx, forwards_market_df,
fx_forwards_trading_tenor=None,
roll_days_before=None,
roll_event=None,
roll_months=None,
fx_forwards_tenor_for_interpolation=None,
cum_index=None,
output_calculation_fields=False):
if not (isinstance(cross_fx, list)):
cross_fx = [cross_fx]
if fx_forwards_trading_tenor is None: fx_forwards_trading_tenor = self._fx_forwards_trading_tenor
if roll_days_before is None: roll_days_before = self._roll_days_before
if roll_event is None: roll_event = self._roll_event
if roll_months is None: roll_months = self._roll_months
if fx_forwards_tenor_for_interpolation is None: fx_forwards_tenor_for_interpolation = self._fx_forwards_tenor_for_interpolation
if cum_index is None: cum_index = self._cum_index
total_return_index_df_agg = []
# Remove columns where there is no data (because these points typically aren't quoted)
forwards_market_df = forwards_market_df.dropna(how='all', axis=1)
fx_forwards_pricer = FXForwardsPricer()
def get_roll_date(horizon_d, delivery_d, asset_hols, month_adj=1):
if roll_event == 'month-end':
roll_d = horizon_d + CustomBusinessMonthEnd(roll_months + month_adj, holidays=asset_hols)
elif roll_event == 'delivery-date':
roll_d = delivery_d
return (roll_d - CustomBusinessDay(n=roll_days_before, holidays=asset_hols))
for cross in cross_fx:
# Eg. if we specify USDUSD
if cross[0:3] == cross[3:6]:
total_return_index_df_agg.append(
pd.DataFrame(100, index=forwards_market_df.index, columns=[cross + "-forward-tot.close"]))
else:
# Is the FX cross in the correct convention
old_cross = cross
cross = FXConv().correct_notation(cross)
horizon_date = forwards_market_df.index
delivery_date = []
roll_date = []
new_trade = np.full(len(horizon_date), False, dtype=bool)
asset_holidays = self._calendar.get_holidays(cal=cross)
# Get first delivery date
delivery_date.append(
self._calendar.get_delivery_date_from_horizon_date(horizon_date[0],
fx_forwards_trading_tenor, cal=cross, asset_class='fx')[0])
# For first month want it to expire within that month (for consistency), hence month_adj=0 ONLY here
roll_date.append(get_roll_date(horizon_date[0], delivery_date[0], asset_holidays, month_adj=0))
# New trade => entry at beginning AND on every roll
new_trade[0] = True
# Get all the delivery dates and roll dates
# At each "roll/trade" day we need to reset them for the new contract
for i in range(1, len(horizon_date)):
# If the horizon date has reached the roll date (from yesterday), we're done, and we have a
# new roll/trade
if (horizon_date[i] - roll_date[i-1]).days == 0:
new_trade[i] = True
# else:
# new_trade[i] = False
# If we're entering a new trade/contract, we need to get new delivery and roll dates
if new_trade[i]:
delivery_date.append(self._calendar.get_delivery_date_from_horizon_date(horizon_date[i],
fx_forwards_trading_tenor, cal=cross, asset_class='fx')[0])
roll_date.append(get_roll_date(horizon_date[i], delivery_date[i], asset_holidays))
else:
# Otherwise use previous delivery and roll dates, because we're still holding same contract
delivery_date.append(delivery_date[i-1])
roll_date.append(roll_date[i-1])
interpolated_forward = fx_forwards_pricer.price_instrument(cross, horizon_date, delivery_date, market_df=forwards_market_df,
fx_forwards_tenor_for_interpolation=fx_forwards_tenor_for_interpolation)[cross + '-interpolated-outright-forward.close'].values
# To record MTM prices
mtm = np.copy(interpolated_forward)
# Note: may need to add discount factor when marking to market forwards?
# Special case: for very first trading day
# mtm[0] = interpolated_forward[0]
# On rolling dates, MTM will be the previous forward contract (interpolated)
# otherwise it will be the current forward contract
for i in range(1, len(horizon_date)):
if new_trade[i]:
mtm[i] = fx_forwards_pricer.price_instrument(cross, horizon_date[i], delivery_date[i-1],
market_df=forwards_market_df,
fx_forwards_tenor_for_interpolation=fx_forwards_tenor_for_interpolation) \
[cross + '-interpolated-outright-forward.close'].values
# else:
# mtm[i] = interpolated_forward[i]
# Eg. if we asked for USDEUR, we first constructed spot/forwards for EURUSD
# and then need to invert it
if old_cross != cross:
mtm = 1.0 / mtm
interpolated_forward = 1.0 / interpolated_forward
forward_rets = mtm / np.roll(interpolated_forward, 1) - 1.0
forward_rets[0] = 0
if cum_index == 'mult':
cum_rets = 100 * np.cumprod(1.0 + forward_rets)
elif cum_index == 'add':
cum_rets = 100 + 100 * np.cumsum(forward_rets)
total_return_index_df = pd.DataFrame(index=horizon_date, columns=[cross + "-forward-tot.close"])
total_return_index_df[cross + "-forward-tot.close"] = cum_rets
if output_calculation_fields:
total_return_index_df[cross + '-interpolated-outright-forward.close'] = interpolated_forward
total_return_index_df[cross + '-mtm.close'] = mtm
total_return_index_df[cross + '-roll.close'] = new_trade
total_return_index_df[cross + '.roll-date'] = roll_date
total_return_index_df[cross + '.delivery-date'] = delivery_date
total_return_index_df[cross + '-forward-return.close'] = forward_rets
total_return_index_df_agg.append(total_return_index_df)
return self._calculations.pandas_outer_join(total_return_index_df_agg)
non_usd = 'BRL'
# Download the whole all market data for USDBRL for pricing options (vol surface)
md_request = MarketDataRequest(start_date=horizon_date,
finish_date=horizon_date,
data_source='bloomberg',
cut='NYC',
category='fx-vol-market',
tickers=cross,
base_depos_currencies=[cross[0:3]],
cache_algo='cache_algo_return')
df = market.fetch_market(md_request)
# Compute implied deposit BRL 1M from USDBRL forwards (and USD 1M depo)
fx_forwards_price = FXForwardsPricer()
implied_depo_df = fx_forwards_price.calculate_implied_depo(
cross,
non_usd,
market_df=df,
fx_forwards_tenor=['1W', '1M'],
depo_tenor=['1W', '1M'])
implied_depo_df.columns = [
x.replace('-implied-depo', '') for x in implied_depo_df.columns
]
df = df.join(implied_depo_df, how='left')
# USDBRL quoted ATMF implied vol (as opposed to delta neutral) hence 'fwd' parameter
fx_op = FXOptionsPricer(fx_vol_surface=FXVolSurface(