def run_takeout_by_expiry():
event = TakeoutEvent('NBIX', 1)
option_type = 'Call'
option_type_2 = 'Put'
strike = 1.0
expiries = [
dt.date(2018, 4, 20),
dt.date(2018, 7, 20),
dt.date(2018, 10, 20),
dt.date(2019, 1, 20),
dt.date(2019, 4, 20)
]
# Preliminary Print Statements
print("Ann. Takeout Prob: {:.1f}%, Premium: {:.1f}%".format(
event.takeout_prob * 100, event.takeout_premium * 100))
for expiry in expiries:
option = Option(option_type, strike, expiry)
option2 = Option(option_type_2, strike, expiry)
distribution = event.get_distribution(expiry)
price = OptionPriceDist(distribution, option)
price2 = OptionPriceDist(distribution, option2)
straddle = price + price2
print(
"T.O. by {:%m/%d/%Y}: {:.1f}%".format(
expiry,
distribution.distribution_df.loc["Takeout", "Prob"] * 100),
"\n" * 0)
print("Mean Move: {:.1f}%".format(distribution.mean_move * 100))
print("Straddle: {:.1f}%".format(straddle * 100), "\n" * 1)
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 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 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))
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
option1 = Option('Call', 1.00, dt.date(2018, 10, 1))
option2 = Option('Call', 1.05, dt.date(2018, 10, 1))
option3 = Option('Call', 1.02, dt.date(2018, 10, 1))
option4 = Option('Call', 1.03, dt.date(2018, 10, 1))
option5 = Option('Call', 1.04, dt.date(2018, 10, 1))
option6 = Option('Call', 1.05, dt.date(2018, 10, 1))
options = [option1, option2, option3, option4, option5, option6]
quantities = [1, 1, 1, 1, 1, 1]
options = [option1, option2]
quantities = [-1, 1]
spread_price = spread_pricing(options, quantities, events, events_bid,
events_ask)
print(spread_price)
def establish_call_options(expiry, strikes):
return [Option('Call', strike, expiry) for strike in strikes]
Option_Map = lambda strike: Option('Call', strike, expiry)
return strikes.apply(Option_Map)
def spread_pricing_bid_ask(options: 'list of options', quantities: 'list of quantities', event_groupings, event_grouping_names, mc_iterations=10**6):
spread_prices = []
for i in range(len(event_groupings)):
spread_price = spread_pricing(options, quantities, event_groupings[i], event_grouping_names[i], mc_iterations)
spread_prices.append(spread_price)
info = {'Level': event_grouping_names,
'Spread': spread_prices}
info = pd.DataFrame(info).set_index('Level')
return info
option_type = 'Put'
expiry = dt.date(2018, 8, 1)
option1 = Option(option_type, .975, expiry)
option2 = Option(option_type, .925, expiry)
option3 = Option(option_type, .95, expiry)
options = [option1, option2, option3]
quantities = [1, -1, 0]
spread_prices = spread_pricing_bid_ask(options, quantities, event_groupings, event_grouping_names, mc_iterations = 10**6)
print(spread_prices.round(3))
print(events_bid, events, events_ask, end = "\n")
sorted_events = sorted(events, key=lambda evt: Timing(evt.timing_descriptor).center_date)
pprint(sorted_events)
timing_descriptors = [evt.timing_descriptor for evt in events]
pprint(timing_descriptors)
def establish_call_options(expiry, strikes):
"""For a given expiry and list of strikes, establish a list of Call Options"""
return [Option('Call', strike, expiry) for strike in strikes]
spread_prices = []
for i in range(len(event_groupings)):
spread_price = spread_pricing(options, quantities, event_groupings[i],
event_grouping_names[i], mc_iterations)
spread_prices.append(spread_price)
info = {'Level': event_grouping_names, 'Spread': spread_prices}
info = pd.DataFrame(info).set_index('Level')
return info
option_type = 'Call'
expiry = dt.date(2018, 8, 1)
option1 = Option(option_type, 1.10, expiry)
option2 = Option(option_type, 1.10, expiry)
option3 = Option(option_type, 1.10, expiry)
options = [option1, option2, option3]
quantities = [1, 1, 1]
event_groupings = [events_bid, events, events_ask]
event_grouping_names = ['Bid', 'Mid', 'Ask']
spread_prices = spread_pricing_bid_ask(options,
quantities,
event_groupings,
event_grouping_names,
mc_iterations=10**6)
print(spread_prices.round(3))
def establish_call_options(expiry, strikes):
"""For a given expiry and list of strikes, establish a list of Call Options"""
return [Option('Call', strike, expiry) for strike in strikes]
create_call_option = lambda strike: Option('Call', strike, expiry)
return strikes.apply(create_call_option)
spread_prices = []
for i in range(len(event_groupings)):
spread_price = spread_pricing(options, quantities, event_groupings[i],
event_grouping_names[i], mc_iterations)
spread_prices.append(spread_price)
info = {'Level': event_grouping_names, 'Spread': spread_prices}
info = pd.DataFrame(info).set_index('Level')
return info
option_type = 'Call'
expiry = dt.date(2018, 6, 1)
option1 = Option(option_type, 1.00, expiry)
option2 = Option('Call', 1.10, expiry)
option3 = Option('Put', .9, expiry)
option4 = Option(option_type, 1.10, expiry)
option5 = Option(option_type, 1.10, expiry)
option6 = Option(option_type, 1.10, expiry)
options = [option1, option2, option3, option4, option5, option6]
quantities = [1, 1, 1, 1, 1, 1]
options = [option1, option2, option3]
quantities = [1, 1, 1]
event_groupings = [events_bid, events, events_ask]
event_grouping_names = ['Bid', 'Mid', 'Ask']
spread_prices = spread_pricing_bid_ask(options,
