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)
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))
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 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)
import datetime as dt 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
expiry5 = dt.date(2018, 9, 21) expiry6 = dt.date(2018, 10, 21) expiry6 = dt.date(2018, 11, 21) expiry6 = 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') event0 = IdiosyncraticVol('CLVS', .15) 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', 4) 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, event6] event0_bid = IdiosyncraticVol('CLVS', .15)
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)
expiry6 = dt.date(2018, 10, 21) 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]
expiry5 = dt.date(2018, 9, 21) expiry6 = dt.date(2018, 10, 21) expiry6 = dt.date(2018, 11, 21) expiry6 = 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', .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]