def run():
if __name__ == "__main__":
#-------------------PresElection Setup-----------------#
PresElectionParams = pd.read_csv(
"/Users/paulwainer/Environments/finance_env/PresElectionParams.csv"
)
PresElectionParams.set_index('Stock', inplace=True)
# Create PresElection Events Dict
PresElection_Evts = {}
for stock, move_input in PresElectionParams.itertuples():
PresElection_Evts[stock] = SysEvt_PresElection(stock, move_input)
#-------------------Takeout Setup-----------------#
TakeoutParams = pd.read_csv("TakeoutParams.csv")
TakeoutParams.set_index('Stock', inplace=True)
# Create Takeout Events Dict
Takeout_Evts = {}
for stock, bucket in TakeoutParams.itertuples():
Takeout_Evts[stock] = TakeoutEvent(stock, bucket)
takeout_dict = {}
for stock, event in Takeout_Evts.items():
takeout_dict[stock] = (event.takeout_prob, event.takeout_premium)
takeout_df = pd.DataFrame(takeout_dict).T.round(3)
takeout_df.rename(columns={0: 'Prob', 1: 'Premium'}, inplace=True)
takeout_df.rename_axis('Stock', inplace=True)
evt = SystematicEvent('ZFGN', .20)
evt2 = Event()
evt3 = SysEvt_PresElection('GM', .05)
evt4 = TakeoutEvent('NBIX', 1)
print("\n\n\nAll Events---\n", Event.instances, "\n")
print("Systematic Event---\n", SystematicEvent.instances, "\n")
print("Presidential Election---\n", SysEvt_PresElection.instances,
"\n")
print("Takeout Event---\n", TakeoutEvent.instances, "\n")
print(takeout_df.sort_values('Premium', ascending=False))
from functools import reduce
from biotech_class_run_9 import get_total_mc_distribution, get_option_sheet_from_mc_distribution
from option_model.Event_Module import IdiosyncraticVol, SysEvt_PresElection, Event, TakeoutEvent
from option_model.Distribution_Module import Distribution, Distribution_MultiIndex
from paul_resources import show_mc_distributions_as_line_chart
from option_model.Option_Module import Option, OptionPriceMC
# Define Events
event8_info = pd.read_excel('CLVS_RiskScenarios.xlsx',
header=[0],
index_col=[0, 1],
sheet_name='Sub_States')
event0 = IdiosyncraticVol('CLVS', .05)
event1 = SysEvt_PresElection('CLVS', .02, 'Q2_2018')
event2 = Event('CLVS', .05, 'Q2_2018', 'Q2_Earnings')
event3 = Event('CLVS', .05, 'Q3_2018', 'Q3_Earnings')
event4 = Event('CLVS', .075, 'Q3_2018', 'Investor_Day')
event5 = Event('CLVS', .1, 'Q2_2018', 'FDA_Approval')
event6 = TakeoutEvent('CLVS', 1)
event7 = Event('CLVS', Distribution(pd.read_csv('CLVS.csv')), 'Q2_2018',
'Ph3_Data')
event8 = Event('CLVS', Distribution_MultiIndex(event8_info), 'Q3_2018',
'Elagolix_Approval')
events = [
event0, event1, event2, event3, event4, event5, event6, event7, event8
]
#events = [event0, event8]
events = [
event0, event1, event2, event3, event4, event5, event6, event7, event8
]
expiries = [date for date in xticks if date > dt.date.today()]
term_struc = term_structure(events, expiries, metric = 'IV', mc_iterations = 10**5)
vols = term_struc.iloc[[term_struc.index.get_loc(1.00, method='nearest')], :].values.tolist()[0]
print(zip(expiries, vols))
ax1.plot(expiries,
vols,
#label = 'Term_Structure',
#color = 'black'
#marker='s',
#s = 250
)
ax1.set_yticks(np.arange(0, max(vols)+.05, .05))
"""
# Set High-Level Graph Parameters; Show Graph
#ax1.grid(True)
ax1.title.set_position([.525, 1.025])
fig.patch.set_facecolor('xkcd:off white')
ax1.patch.set_facecolor('xkcd:pale grey')
fig.tight_layout()
fig.set_size_inches(8, 5)
plt.legend(loc='best')
plt.show()
return fig, ax1
if __name__ == '__main__':
events = [Event('CRBP', .05, 'Q3_2018'), Earnings('CRBP', .075, 'Q3_2018')]
get_event_timeline(events)
def mc_simulation(expiry=None, mc_iterations=10**5):
# Define Events
event1 = TakeoutEvent('CLVS', 1)
event2 = SysEvt_PresElection('CLVS', .015)
event3 = Event('CLVS', Distribution(pd.read_csv('CLVS.csv')), 'Ph3_Data')
event4 = Event('CLVS', .025, 'Investor_Day')
event5 = Event('CLVS', .15, 'FDA_Approval')
event6 = Event('CLVS', .15, 'Q1_Earnings')
event7 = Event('CLVS', .05, 'Q2_Earnings')
events1 = [event6]
events2 = [event6, event7]
events3 = [event5, event6, event7]
events4 = [event1, event5, event6, event7]
events5 = [event1, event3, event5, event6, event7]
event_groupings = [events1, events2, events3, events4, events5]
@my_time_decorator
def get_total_mc_distribution(events,
expiry=None,
symbol=None,
mc_iterations=10**4):
"""Add together the MC Distributions of individual events. Return the Total MC Distribution."""
total_mc_distribution = np.zeros(mc_iterations)
for event in events:
distribution = event.get_distribution(expiry)
total_mc_distribution += distribution.mc_simulation(mc_iterations)
return total_mc_distribution
@my_time_decorator
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
@my_time_decorator
def event_groupings_df(event_groupings):
i = 0
for grouping in event_groupings:
mc_distribution = get_total_mc_distribution(grouping,
expiry=expiry)
prices = get_option_prices_from_mc_distribution(
mc_distribution,
strikes=np.arange(.5, 1.55, .05)).loc[:, ['Prices', 'IVs']]
if event_groupings.index(grouping) == 0:
prices_df = prices
else:
prices_df = pd.merge(prices_df,
prices,
left_index=True,
right_index=True)
get_mc_histogram(mc_distribution)
i += 1
return prices_df
event_df = event_groupings_df(event_groupings)
print(event_df)
def mc_simulation():
expiry = dt.date(2018, 12, 1)
mc_iterations = 10**5
# Define Events
event1 = TakeoutEvent('CLVS', 1)
event2 = SysEvt_PresElection('CLVS', .015)
event3 = Event('CLVS', Distribution(pd.read_csv('CLVS.csv')), 'Ph3_Data')
event4 = Event('CLVS', .025, 'Investor_Day')
event5 = Event('CLVS', .15, 'FDA_Approval')
event6 = Event('CLVS', .15, 'Q1_Earnings')
event7 = Event('CLVS', .05, 'Q2_Earnings')
events1 = [event6]
events2 = [event6, event7]
events3 = [event5, event6, event7]
events4 = [event1, event5, event6, event7]
events5 = [event1, event3, event5, event6, event7]
event_groupings = [events1, events2, events3, events4, events5]
@my_time_decorator
def get_total_distribution(events):
mc_simulation = np.zeros(mc_iterations)
for event in events:
distribution = event.get_distribution(expiry)
mc_simulation += distribution.mc_simulation(mc_iterations)
return mc_simulation
@my_time_decorator
def get_option_prices(mc_distribution):
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)
implied_vol = get_implied_volatility(option, 1.0, option_price)
option_prices.append(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)
#prices_df.rename_axis(name, inplace=True)
return prices_df
@my_time_decorator
def event_groupings_df(event_groupings):
i = 0
for grouping in event_groupings:
mc_distribution = get_total_distribution(grouping)
prices = get_option_prices(mc_distribution).loc[:, ['IVs']]
if event_groupings.index(grouping) == 0:
prices_df = prices
else:
prices_df = pd.merge(prices_df,
prices,
left_index=True,
right_index=True)
graph_MC_distribution(mc_distribution)
i += 1
return prices_df
event_df = event_groupings_df(event_groupings)
print(event_df)
expiries = [expiry1, expiry3, expiry5]
expiries = [expiry3]
# Define Events
event8_info = pd.read_excel('CLVS_RiskScenarios.xlsx',
header = [0],
index_col = [0,1],
sheet_name = 'Sub_States')
idio = IdiosyncraticVol('CLVS', .05)
takeout = TakeoutEvent('CLVS', 2)
pres_elec = SysEvt_PresElection('CLVS', .02)
earns_q2 = Earnings('CLVS', .05, 'Q2_2018', 'Q2_Earnings')
earns_q3 = Earnings('CLVS', .05, 'Q3_2018', 'Q3_Earnings')
earns_q4 = Earnings('CLVS', .05, 'Q4_2018', 'Q4_Earnings')
event5 = Event('CLVS', .1, 'Q2_2018', 'FDA_Approval')
data = Event('CLVS', Distribution(pd.read_csv('CLVS.csv')), 'Q2_2018', 'Ph3_Data')
elagolix = ComplexEvent('CLVS', Distribution_MultiIndex(event8_info), 'Q2_2018', 'Elagolix_Approval')
events = [idio, takeout, earns_q2, earns_q3, earns_q4, elagolix]
#events = [takeout]
#events = [idio, elagolix]
events_bid = [event.event_bid for event in events]
events_ask = [event.event_ask for event in events]
events_high_POS = [idio, elagolix.event_high_prob_success]
events_low_POS = [idio, elagolix.event_low_prob_success]
events_max_optionality = [idio, elagolix.event_max_optionality]
# Define Event Groupings
event_groupings = {}
for i in range(len(events)):
import pandas as pd
import datetime as dt
# Paul Modules
from option_model.Event_Module import Event, ComplexEvent
from option_model.Distribution_Module import Distribution, Distribution_MultiIndex
analyst_day = Event('NBIX', .075, dt.date(2018, 12, 1), 'Analyst Day')
ingrezza_info = pd.read_csv(
'/Users/paulwainer/Paulthon/Events/Parameters/CLVS.csv')
ingrezza_data = Event('NBIX', Distribution(ingrezza_info), 'Q4_2018',
'Ingrezza Data')
elagolix_info = pd.read_excel(
'/Users/paulwainer/Paulthon/Events/Parameters/CLVS_RiskScenarios2.xlsx',
header=[0],
index_col=[0, 1],
sheet_name='Sub_States')
elagolix_approval = ComplexEvent('NBIX',
Distribution_MultiIndex(elagolix_info),
dt.date(2018, 11, 15), 'Elagolix Approval')
all_other_events = [analyst_day, ingrezza_data, elagolix_approval]
expiries = [expiry1, expiry2, expiry3, expiry4, expiry5, expiry6]
expiries = [expiry1, expiry3, expiry5]
expiries = [expiry3]
# Define Events
event8_info = pd.read_excel('CLVS_RiskScenarios.xlsx',
header=[0],
index_col=[0, 1],
sheet_name='Sub_States')
idio = IdiosyncraticVol('CLVS', .15)
earns_q2 = SysEvt_PresElection('CLVS', .02, 'Q2_2018')
earns_q3 = Earnings('CLVS', .05, 'Q2_2018', 'Q2_Earnings')
earns_q4 = Earnings('CLVS', .05, 'Q3_2018', 'Q3_Earnings')
event4 = Earnings('CLVS', .05, 'Q4_2018', 'Q4_Earnings')
event5 = Event('CLVS', .1, 'Q2_2018', 'FDA_Approval')
takeout = TakeoutEvent('CLVS', 2)
event7 = Event('CLVS', Distribution(pd.read_csv('CLVS.csv')), 'Q2_2018',
'Ph3_Data')
event8 = Event('CLVS', Distribution_MultiIndex(event8_info), 'Q2_2018',
'Elagolix_Approval')
events = [idio, earns_q2, earns_q3, earns_q4, takeout, event8]
events = [takeout]
events_bid = [event.event_bid for event in events]
events_ask = [event.event_ask for event in events]
# Define Event Groupings
event_groupings = {}
for i in range(len(events)):
event_groupings[i] = [events[i] for i in range(i + 1)]
