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)
