def get_atm_ivol(s, ndays=30):
#Need to fix for divs, borrow etc to find atm
symbol = s.ticker
expiry_dict = get_expiries_bracket(symbol, ndays)
#First Shorter One
x = expiry_dict['shorter_expiry']
shorter_call = Call(symbol, d=int(x[0:2]), m=int(x[3:5]), y=int(x[6:10]))
strike_dict = get_strike_bracket(shorter_call.strikes, s.price)
shorter_call.set_strike(strike_dict['lower_strike'])
lower_vol = shorter_call.implied_volatility()
shorter_call.set_strike(strike_dict['higher_strike'])
higher_vol = shorter_call.implied_volatility()
shorter_ivol = lower_vol * strike_dict['lower_weight'] + higher_vol * (
1 - strike_dict['lower_weight'])
#Now longer One
x = expiry_dict['longer_expiry']
longer_call = Call(symbol, d=int(x[0:2]), m=int(x[3:5]), y=int(x[6:10]))
strike_dict = get_strike_bracket(longer_call.strikes, s.price)
longer_call.set_strike(strike_dict['lower_strike'])
lower_vol = longer_call.implied_volatility()
longer_call.set_strike(strike_dict['higher_strike'])
higher_vol = longer_call.implied_volatility()
longer_ivol = lower_vol * strike_dict['lower_weight'] + higher_vol * (
1 - strike_dict['lower_weight'])
implied_ivol = shorter_ivol * expiry_dict[
'shorter_weight'] + longer_ivol * (1 - expiry_dict['shorter_weight'])
one_sigma_move_ndays_day = implied_ivol * math.sqrt(ndays / 365)
return (implied_ivol, one_sigma_move_ndays_day)
def opt_vol(self, type, symbol, option, underlying, day, month, year, strike):
if type == "Equity":
vol = 1
elif option == "CALL":
call = Call(underlying, day, month, year, strike)
vol = float(call.implied_volatility())
elif option == "PUT":
put = Put(underlying, day, month, year, strike)
vol = float(put.implied_volatility())
else:
vol = 0
return vol
def get_atm_ivol(s, ndays=30):
#Need to fix for divs, borrow etc to find atm
symbol = s.ticker
symbol = symbol.upper()
if is_cache_good(f'{symbol}|getatmivol|{ndays}'):
return ast.literal_eval(r.hget(f'{symbol}|getatmivol|{ndays}',
'value'))
expiry_dict = get_expiries_bracket(symbol, ndays)
#First Shorter One
x = expiry_dict['shorter_expiry']
shorter_call = Call(symbol, d=int(x[0:2]), m=int(x[3:5]), y=int(x[6:10]))
strike_dict = get_strike_bracket(shorter_call.strikes, s.price)
shorter_call.set_strike(strike_dict['lower_strike'])
lower_vol = shorter_call.implied_volatility()
shorter_call.set_strike(strike_dict['higher_strike'])
higher_vol = shorter_call.implied_volatility()
shorter_ivol = lower_vol * strike_dict['lower_weight'] + higher_vol * (
1 - strike_dict['lower_weight'])
#Now longer One
x = expiry_dict['longer_expiry']
longer_call = Call(symbol, d=int(x[0:2]), m=int(x[3:5]), y=int(x[6:10]))
strike_dict = get_strike_bracket(longer_call.strikes, s.price)
longer_call.set_strike(strike_dict['lower_strike'])
lower_vol = longer_call.implied_volatility()
longer_call.set_strike(strike_dict['higher_strike'])
higher_vol = longer_call.implied_volatility()
longer_ivol = lower_vol * strike_dict['lower_weight'] + higher_vol * (
1 - strike_dict['lower_weight'])
implied_ivol = shorter_ivol * expiry_dict[
'shorter_weight'] + longer_ivol * (1 - expiry_dict['shorter_weight'])
one_sigma_move_ndays_day = implied_ivol * math.sqrt(ndays / 365)
return_dict = (implied_ivol, one_sigma_move_ndays_day)
r.hset(f'{symbol}|getatmivol|{ndays}', 'time',
datetime.utcnow().strftime('%s'))
r.hset(f'{symbol}|getatmivol|{ndays}', 'value', str(return_dict))
return return_dict
def infos(udlying, day, month, year, stockprice, offset):
"""
Group information
:param udlying: underlying stock object
:param day: int digits
:param month: int digits
:param year:
:param stockprice: stock price
:param offset: strike offset
:return: Tuple of all data
"""
u = Call(udlying, d=day, m=month, y=year, strike=stockprice + offset)
price = u.price
IV = u.implied_volatility()
v = u.vega()
g = u.gamma()
strike = u.strike
return (IV, v, g, price, strike)
def opt_vol_r_T(self, type, symbol, option, underlying, day, month, year, strike):
if type == "Equity":
time = 1
rate = 1
vol = 1
elif option == "CALL":
call = Call(underlying, day, month, year, strike)
time = call.BandS.T
rate = float(call.BandS.r)
vol = float(call.implied_volatility())
elif option == "PUT":
put = Put(underlying, day, month, year, strike)
time = put.BandS.T
rate = float(put.BandS.r)
vol = float(put.implied_volatility())
else:
time = 0;
rate = 0;
vol = 0
return time, rate, vol
symbol = args[2]
day = int(args[3])
month = int(args[4])
year = int(args[5])
min_strike = int(args[6])
max_strike = int(args[7])
step = int(args[8])
options = []
price = min_strike
while price <= max_strike:
option = Call(symbol, d=day, m=month, y=year,
strike=price) if method == 'call' else Put(
symbol, d=day, m=month, y=year, strike=price)
options.append([
price, option.price,
option.implied_volatility(), option.volume, option.underlying.price,
option.delta(),
option.gamma(),
option.theta(), option.expiration
])
price += step
df = pd.DataFrame(options,
columns=[
'Strike', 'Price', 'Implied Vol', 'Volume', 'Underlying',
'Delta', 'Gamma', 'Theta', 'Expiration'
])
print(df)
def main():
parser = argparse.ArgumentParser(
description="Find best trading strategies")
group = parser.add_mutually_exclusive_group()
parser.add_argument("ticker", type=str, help="stock ticker")
# group.add_argument("-t", "--ticker", action="store_true")
group.add_argument("-d", "--date", action="store_true")
parser.add_argument("-s", "--strategy", help="the strategy")
# parser.add_argument("y", type=int, help="the exponent")
args = parser.parse_args()
ticker = yf.Ticker(args.ticker)
# get stock info
print('****** Info **********')
print(ticker.info)
# input("Press Enter to continue...")
# get historical market data
print('****** History **********')
hist = ticker.history(period="max")
print(hist)
# input("Press Enter to continue...")
print('****** Actions **********')
# show actions (dividends, splits)
print(ticker.actions)
# input("Press Enter to continue...")
print('****** dividends **********')
# show dividends
print(ticker.dividends)
# input("Press Enter to continue...")
# show splits
ticker.splits
# show financials
print('****** financials **********')
print(ticker.financials)
print(ticker.quarterly_financials)
# input("Press Enter to continue...")
# show major holders
print(ticker.major_holders)
# show institutional holders
print(ticker.institutional_holders)
# input("Press Enter to continue...")
# show balance heet
print(ticker.balance_sheet)
print(ticker.quarterly_balance_sheet)
# show cashflow
ticker.cashflow
ticker.quarterly_cashflow
# show earnings
print(ticker.earnings)
print(ticker.quarterly_earnings)
# show sustainability
print(ticker.sustainability)
# show analysts recommendations
print(ticker.recommendations)
# show next event (earnings, etc)
print('****** calendars **********')
print(ticker.calendar)
# input("Press Enter to continue...")
# show ISIN code - *experimental*
# ISIN = International Securities Identification Number
print(ticker.isin)
# show options expirations
print('****** calendars **********')
print(ticker.options)
# input("Press Enter to continue...")
# get option chain for specific expiration
opt = ticker.option_chain(ticker.options[0])
# data available via: opt.calls, opt.puts
print(opt.calls)
# input("Press Enter to continue...")
print(opt.puts)
# input("Press Enter to continue...")
history = ticker.history()
last_quote = (history.tail(1)['Close'].iloc[0])
last_price = int(last_quote)
# calls
for opt in ticker.options:
try:
data = []
dt = datetime.fromisoformat(opt)
option = Call(args.ticker
) # d=dt.day, m=dt.month, y=dt.year, strike=ticker.)
for strike in option.strikes:
if strike < last_price - 40 or strike > last_price + 25:
continue
print(f'strike = {strike}')
option.set_strike(strike)
item = {}
item['strike'] = strike
item['price'] = option.price
item['iv'] = option.implied_volatility()
item['delta'] = option.delta()
item['vega'] = option.vega()
item['gamma'] = option.gamma()
# print(f'theta = {option.theta()}')
# print(f'vega = {option.vega()}')
data.append(item)
dataframe = pd.DataFrame(data)
dataframe.to_csv(f'call-{args.ticker}-{dt}')
print(dataframe.to_csv())
except Exception as e:
print(f'{type(e)}: {str(e)} ')
continue
# put
for opt in ticker.options:
try:
data = []
dt = datetime.fromisoformat(opt)
option = Put(
args.ticker
) # d=dt.day, m=dt.month, y=dt.year, strike=ticker.)
for strike in option.strikes:
if strike < last_price - 40 or strike > last_price + 25:
continue
print(f'strike = {strike}')
option.set_strike(strike)
item = {}
item['strike'] = strike
item['price'] = option.price
item['iv'] = option.implied_volatility()
item['delta'] = option.delta()
item['vega'] = option.vega()
item['gamma'] = option.gamma()
# print(f'Rho = {option.rho()}')
# print(f'type = {option.Option_type}')
# print(f'theta = {option.theta()}')
# print(f'vega = {option.vega()}')
data.append(item)
dataframe = pd.DataFrame(data)
dataframe.to_csv(f'put-{args.ticker}-{dt}')
print(dataframe.to_csv())
except Exception as e:
print(f'{type(e)}: {str(e)} ')
continue
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Wallstreet package can be found in the following link
https://pypi.python.org/pypi/wallstreet/0.1.5
@author: chenkai
"""
from wallstreet import Stock, Call, Put
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
g = Call('SPX', d=20, m=7, y=2018, source='yahoo')
x = g.strikes
y = np.zeros(len(x))
for i in range(len(x)):
g.set_strike(x[i])
y[i] = g.implied_volatility()
plt.plot(x, y)
plt.scatter(x, y)