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 = OptionPrice(distribution, option)
price2 = OptionPrice(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 run3():
# Define Events
event1 = TakeoutEvent('CLVS', 1)
event2 = SysEvt_PresElection('CLVS', .02)
event3 = SystematicEvent('CLVS', .1, 'Ph3_Data')
event4 = SystematicEvent('CLVS', .05, 'Investor_Day')
event5 = SystematicEvent('CLVS', .3, 'FDA_Approval')
event6 = SystematicEvent('CLVS', .05, 'Q1_Earnings')
event7 = SystematicEvent('CLVS', .05, 'Q2_Earnings')
expiry = dt.date(2018, 5, 1)
events = [event2, event3, event4]
added_distribution = event1.get_distribution(expiry)
for event in events:
added_distribution += event.get_distribution()
rprint(added_distribution.mean_move)
def run2():
expiry = dt.date(2018, 5, 1)
event1 = TakeoutEvent('CLVS', 1)
event2 = SysEvt_PresElection('CLVS', .02)
event3 = SystematicEvent('CLVS', .1, 'Ph3_Data')
event4 = SystematicEvent('CLVS', .05, 'Investor_Day')
event5 = SystematicEvent('CLVS', .3, 'FDA Approval')
distribution1 = event1.get_distribution(expiry)
distribution2 = event2.get_distribution()
distribution3 = event3.get_distribution()
distribution4 = event4.get_distribution()
distribution5 = event5.get_distribution()
added_distribution = distribution1 + distribution2 + distribution3 + distribution4 + distribution5
print(added_distribution)
print(added_distribution.distribution_df)
rprint(distribution1.mean_move, distribution2.mean_move, distribution3.mean_move, distribution4.mean_move, distribution5.mean_move, added_distribution.mean_move)