def timing_test_for_distribution_addition_2():
# Define Events
event1 = TakeoutEvent('CLVS', 1)
event2 = SysEvt_PresElection('CLVS', .2)
event3 = Earnings('CLVS', .2, 'Q2_2018')
event4 = Earnings('CLVS', .005, 'Q3_2018')
event5 = Earnings('CLVS', .3, 'Q4_2018')
expiry = dt.date(2018, 5, 1)
events = [event2, event3]
added_distribution = event1.get_distribution(expiry)
for event in events:
added_distribution += event.get_distribution()
rprint(added_distribution.mean_move)
def create_earnings_events(stocks: 'list of stocks'):
"""Create Earnings Events for a List of Stocks based on Random Dates"""
event_names = ['Q4_2018', 'Q1_2019', 'Q2_2019', 'Q3_2019']
q4_date_range = list(
pd.date_range(dt.date(2018, 10, 1), dt.date(2018, 12, 30)))
earnings_events = []
for stock in stocks:
# Set Event Input
event_input = random.uniform(.03, .08)
# Set Earnings Dates
q4_date = random.choice(q4_date_range)
timing_descriptors = [
q4_date, q4_date + timedelta(90), q4_date + timedelta(180),
q4_date + timedelta(270)
]
# Instantiate Earnings Events and append to main list
for i in range(4):
earnings_evt = Earnings(stock, event_input, timing_descriptors[i],
event_names[i])
earnings_events.append(earnings_evt)
return earnings_events
def get_earnings_events():
earns_evts = []
for earns in get_earnings_table().itertuples():
earns_evt = Earnings(
earns.stock, earns.event_input,
dt.datetime.strptime(earns.timing_descriptor, '%Y-%m-%d').date(),
earns.event_name)
earns_evts.append(earns_evt)
return earns_evts
def get_earnings_events(symbol=None):
conn = sqlite3.connect('earnings.db', check_same_thread=False)
c = conn.cursor()
with conn:
if symbol is None:
c.execute("SELECT * FROM earnings")
else:
c.execute("SELECT * FROM earnings WHERE stock=:stock",
{'stock': symbol})
return [Earnings(*params) for params in c.fetchall()]
def get_earnings_events(symbol=None):
if symbol is None:
earns_evts = []
for earns in get_earnings_table().itertuples():
earns_evt = Earnings(
earns.stock, earns.event_input,
dt.datetime.strptime(earns.timing_descriptor,
'%Y-%m-%d').date(), earns.event_name)
earns_evts.append(earns_evt)
return earns_evts
else:
c.execute("SELECT * FROM earnings WHERE stock=:stock",
{'stock': symbol})
return [instantiate_earnings_event(params) for params in c.fetchall()]
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)
mc_distribution = get_total_mc_distribution(event_grouping, expiry)
return get_vol_surface_from_mc_distribution(mc_distribution, expiry)
def get_vol_surface(events, expiry):
return get_vol_surface_from_event_grouping(events, expiry)
def get_vol_surface_spline(vol_surface):
strikes = vol_surface.index.values.tolist()
vols = vol_surface.iloc[:, 0].values.tolist()
return interp1d(strikes, vols, kind='cubic')
#---------------------------------I optimize for speed again below here---------------------------------------------#
EarningsDist = Earnings('CRBP', .05, 'Q2_2018').get_distribution(
dt.date(2018, 7, 1)).mc_simulation(10**4)
IdiosyncraticVolDist = IdiosyncraticVol(
'CRBP', .10).get_distribution(dt.date.today() +
timedelta(365)).mc_simulation(10**4)
#@my_time_decorator
def get_total_mc_distribution(events,
expiry=None,
symbol=None,
mc_iterations=10**4):
"""Add the simulation results of individual events to return the total simulated distribution."""
"""
events = [evt for evt in events if event_prob_by_expiry(evt.timing_descriptor, expiry) > 0]
distributions = map(lambda evt: evt.get_distribution(expiry), events)
mc_distributions = map(lambda dist: dist.mc_simulation(mc_iterations), distributions)
from option_model.Event_Module import Earnings
import datetime as dt
from utility.decorators import my_time_decorator
event = Earnings('CRBP', .075, 'Q2_2018')
distribution = event.get_distribution(dt.date(2018, 5, 20))
@my_time_decorator
def get_simulation_results(mc_iterations):
return distribution.mc_simulation(mc_iterations)
simulation_results = list(get_simulation_results(10**7))
print(type(simulation_results), len(simulation_results))
@my_time_decorator
def list_of_list(my_list):
return list(my_list)
list_of_list(simulation_results)
def instantiate_earnings_event(
params: 'tuple of Earnings params from sqlite db'):
return Earnings(*params)
def instantiate_timer(params, n=1):
for i in range(n):
evt = Earnings(*params)
def get_earnings_events(symbol=None):
if symbol is None:
c.execute("SELECT * FROM earnings")
else:
c.execute("SELECT * FROM earnings WHERE stock=:stock", {'stock': symbol})
return [Earnings(*params) for params in c.fetchall()]
def instantiate_earnings_event_2(params):
return Earnings(*params)
def instantiate(n=1):
for i in range(n):
evt = Earnings(*params)
expiry7 = dt.date(2018, 11, 21)
expiry8 = dt.date(2018, 12, 21)
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', .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]
def instantiate_earnings_event(params: 'tuple of Earnings params'):
evt = Earnings(params[0], params[1],
dt.datetime.strptime(params[2], '%Y-%m-%d').date(),
params[3])
return evt
def earnings_params_to_earnings_event(params):
evt = Earnings(params[0], params[1],
dt.datetime.strptime(params[2], '%Y-%m-%d').date(),
params[3])
return evt