def spread_pricing(options: 'list of options', quantities: 'list of quantities', events, events_bid, events_ask, mc_iterations=10**6):
mc_distribution = get_total_mc_distribution(events, options[0].Expiry, mc_iterations=mc_iterations)
mc_distribution_bid = get_total_mc_distribution(events_bid, options[0].Expiry, mc_iterations=mc_iterations)
mc_distribution_ask = get_total_mc_distribution(events_ask, options[0].Expiry, mc_iterations=mc_iterations)
option_prices = []
for i in range(len(options)):
#mc_distribution = get_total_mc_distribution(events, option.Expiry, mc_iterations=mc_iterations)
if quantities[i] > 0:
option_price = OptionPriceMC(options[i], mc_distribution_bid)
side = 'Bid'
else:
option_price = OptionPriceMC(options[i], mc_distribution_ask)
side = 'Ask'
print("Strike: {:.3f}, {} Price: {:.3f}".format(options[i].Strike, side, option_price))
"""
try:
call_spread = option_prices[-1] - option_price
print("Call Spread: {:2f}".format(call_spread))
except Exception:
pass
"""
option_prices.append(option_price)
spread_price = sum([option_price*quantity for option_price, quantity in zip(option_prices, quantities)])
print("Spread Price: {:.3f}".format(spread_price))
return spread_price
def get_option_prices_from_mc_distribution(mc_distribution, strikes=None):
if strikes is None:
strikes = np.arange(.5, 1.55, .05)
option_prices = []
implied_vols = []
for strike in strikes:
if strike >= 1.0:
option_type = 'Call'
else:
option_type = 'Put'
option = Option(option_type, strike, expiry)
option_price = OptionPriceMC(option, mc_distribution)
option_prices.append(option_price)
implied_vol = get_implied_volatility(option, 1.0, option_price)
implied_vols.append(implied_vol)
prices_info = {
'Strikes': strikes,
'Prices': option_prices,
'IVs': implied_vols
}
prices_df = pd.DataFrame(prices_info).round(3)
prices_df.set_index('Strikes', inplace=True)
return prices_df
def get_vol_surface_from_mc_distribution(mc_distribution,
expiry=None,
strikes=None):
if strikes is None:
strikes = np.arange(.5, 1.5, .01)
#strikes = np.arange(.5, 1.5, .005)
call_options = [Option('Call', strike, expiry) for strike in strikes]
call_prices = list(
map(lambda option: OptionPriceMC(option, mc_distribution),
call_options))
call_IVs = list(
map(
lambda option, option_price: get_implied_volatility(
option, option_price), call_options, call_prices))
option_sheet_info = list(call_IVs)
index_r = pd.Index(strikes, name='Strike')
iterables_c = [[expiry], ['IV']]
index_c = pd.MultiIndex.from_product(iterables_c,
names=['Expiry', 'Option_Info'])
option_sheet = pd.DataFrame(option_sheet_info,
index=index_r,
columns=index_c)
return option_sheet
def spread_pricing(options: 'list of options',
quantities: 'list of quantities',
events,
mc_iterations=10**6):
mc_distribution = get_total_mc_distribution(events,
options[0].Expiry,
mc_iterations=mc_iterations)
option_prices = []
for option in options:
#mc_distribution = get_total_mc_distribution(events, option.Expiry, mc_iterations=mc_iterations)
option_price = OptionPriceMC(option, mc_distribution)
print("Strike: {:.3f}, Price: {:.3f}".format(option.Strike,
option_price))
"""
try:
call_spread = option_prices[-1] - option_price
print("Call Spread: {:2f}".format(call_spread))
except Exception:
pass
"""
option_prices.append(option_price)
spread_price = sum([
option_price * quantity
for option_price, quantity in zip(option_prices, quantities)
])
print("Spread Price: {:.3f}".format(spread_price))
return spread_price
def option_pricing():
option_type = 'Call'
strike = 1.0
expiry = dt.date(2018, 10, 10)
option = Option(option_type, strike, expiry)
mc_distribution = get_total_mc_distribution(events, expiry, mc_iterations=10**6)
option_price = OptionPriceMC(option, mc_distribution)
print("Expiry: {}, Price: {}".format(expiry, option_price))
def get_option_sheet_from_mc_distribution(mc_distribution,
expiry=None,
strikes=None):
if strikes is None:
strikes = np.arange(.5, 2, .005)
call_options = [Option('Call', strike, expiry) for strike in strikes]
call_prices = list(
map(lambda option: OptionPriceMC(option, mc_distribution),
call_options))
call_IVs = list(
map(
lambda option, option_price: get_implied_volatility(
option, option_price), call_options, call_prices))
put_options = [Option('Put', strike, expiry) for strike in strikes]
put_prices = list(
map(lambda option: OptionPriceMC(option, mc_distribution),
put_options))
put_IVs = list(
map(
lambda option, option_price: get_implied_volatility(
option, option_price), put_options, put_prices))
option_premiums = [
min(call_price, put_price)
for call_price, put_price in zip(call_prices, put_prices)
]
"""
option_sheet_info = {'Strike': strikes, 'Price': option_premiums, 'IV': call_IVs}
option_sheet = pd.DataFrame(option_sheet_info).set_index('Strike').loc[:, ['Price', 'IV']].round(2)
"""
option_sheet_info = list(zip(option_premiums, call_IVs))
index_r = pd.Index(strikes, name='Strike')
iterables_c = [[expiry], ['Premium', 'IV']]
index_c = pd.MultiIndex.from_product(iterables_c,
names=['Expiry', 'Option_Info'])
option_sheet = pd.DataFrame(option_sheet_info,
index=index_r,
columns=index_c)
return option_sheet
def get_option_sheet_from_mc_distribution(mc_distribution,
expiry=None,
strikes=None):
if strikes is None:
strikes = np.arange(.75, 1.25, .05)
call_options = [Option('Call', strike, expiry) for strike in strikes]
call_prices = list(
map(lambda option: OptionPriceMC(option, mc_distribution),
call_options))
call_IVs = list(
map(
lambda option, option_price: get_implied_volatility(
option, option_price), call_options, call_prices))
put_options = [Option('Put', strike, expiry) for strike in strikes]
put_prices = list(
map(lambda option: OptionPriceMC(option, mc_distribution),
put_options))
put_IVs = list(
map(
lambda option, option_price: get_implied_volatility(
option, option_price), put_options, put_prices))
option_premiums = [
min(call_price, put_price)
for call_price, put_price in zip(call_prices, put_prices)
]
option_sheet_info = {
'Strike': strikes,
'Price': option_premiums,
'IV': call_IVs
}
option_sheet = pd.DataFrame(option_sheet_info).set_index(
'Strike').loc[:, ['Price', 'IV']].round(2)
#iterables = [['Price', 'IV'], ['Group 1']]
#index = pd.MultiIndex.from_product(iterables, names=['Option Info', 'Event Grouping'])
#option_sheet.rename(columns=index)
#print(index)
return option_sheet
def spread_pricing(options: 'list of options', quantities: 'list of quantities', events, description = None, mc_iterations=10**6):
mc_distribution = get_total_mc_distribution(events, options[0].Expiry, mc_iterations=mc_iterations)
option_prices = []
for i in range(len(options)):
option_price = OptionPriceMC(options[i], mc_distribution)
option_prices.append(option_price)
logger.info("Strike: {:.3f}, {} Price: {:.3f}".format(options[i].Strike, description, option_price))
spread_price = sum([option_price*quantity for option_price, quantity in zip(option_prices, quantities)])
logger.info("Spread Price: {:.3f}".format(spread_price))
return spread_price
def individual_option_pricing():
option_type = 'Call'
strike = 1.0
expiry = dt.date(2018, 5, 10)
expiries = pd.date_range(pd.datetime.today(), periods=100).tolist()
expiries = [expiry]*100
print(isinstance(expiries[0], dt.datetime))
for expiry in expiries:
option = Option(option_type, strike, expiry)
mc_distribution = get_total_mc_distribution(events, expiry, mc_iterations=10**6)
option_price = OptionPriceMC(option, mc_distribution)
print((expiry, option_price))
def get_call_prices(call_options, mc_distribution):
return list(
map(lambda option: OptionPriceMC(option, mc_distribution),
call_options))
OptionPriceMC_Map = lambda option: OptionPriceMC(
option, mc_distribution)
def get_call_prices(call_options, mc_distribution):
"""For a list of call options (same expiry) and a MC Distribution, calculate the call prices"""
return [
OptionPriceMC(call_option, mc_distribution)
for call_option in call_options
]