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 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 get_bid_ask_sheet(event_groupings, event_grouping_names, expiry, metric = 'IV', mc_iterations = 10**5):
#labels = ['Bid - {}'.format(metric), 'Mid - {}'.format(metric), 'Ask - {}'.format(metric), 'New - {}'.format(metric)]
event_grouping_names = ['{} - {}'.format(label, metric) for label in event_grouping_names]
mc_distributions = list(map(lambda events: get_total_mc_distribution(events, expiry, mc_iterations=mc_iterations), event_groupings))
implied_vols = list(map(lambda dist: get_option_sheet_from_mc_distribution(dist, expiry).loc[:, [(expiry, metric)]], mc_distributions))
show_mc_distributions_as_line_chart(mc_distributions, labels = event_grouping_names)
return reduce(lambda x,y: pd.merge(x, y, left_index=True, right_index=True), implied_vols)
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 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 term_structure(events, expiries):
mc_distributions = list(
map(lambda expiry: get_total_mc_distribution(events, expiry),
expiries))
implied_vols = list(
map(
lambda dist, expiry: get_option_sheet_from_mc_distribution(
dist, expiry).loc[:, ['IV']], mc_distributions, expiries))
show_mc_distributions_as_line_chart(mc_distributions)
return reduce(
lambda x, y: pd.merge(x, y, left_index=True, right_index=True),
implied_vols)
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 bid_ask(events_bid,
events,
events_ask,
expiry,
metric='IV',
mc_iterations=10**5):
mc_distributions = list(
map(
lambda events: get_total_mc_distribution(
events, expiry, mc_iterations=mc_iterations),
[events_bid, events, events_ask]))
implied_vols = list(
map(
lambda dist: get_option_sheet_from_mc_distribution(dist, expiry).
loc[:, [(expiry, metric)]], mc_distributions))
show_mc_distributions_as_line_chart(mc_distributions,
labels=[
'Bid - {}'.format(metric),
'Mid - {}'.format(metric),
'Ask - {}'.format(metric)
])
return reduce(
lambda x, y: pd.merge(x, y, left_index=True, right_index=True),
implied_vols)
