def main():
# -------------------------[Set-up]-------------------------
ticker = Ticker('MSFT')
optionManager = OptionManager(ticker, now=None)
i = 0 # <- Time To Maturity curve
exp = optionManager.getExpirations()[i]
optionChain = optionManager.getOptionChain(exp=exp)
# ----------------------------------------------------------
start_time = time.time()
impliedVolatility = ImpliedVolatility(optionChain)
curve = impliedVolatility.getImpliedVolatility()
print('chrono: {}'.format(time.time() - start_time))
fig, ax = plt.subplots(figsize=(8, 5))
ax.set(xlabel='Strike',
ylabel='Volatility',
title='Option implied volatility ({})'.format(
ticker.getInfo().ticker))
ax.plot(curve.calls.strike,
curve.calls.IV,
label='Calls',
color='green',
alpha=.5)
ax.plot(curve.puts.strike,
curve.puts.IV,
label='Puts',
color='red',
alpha=.5)
ax.plot(curve.calls.strike,
curve.calls.naturalIV,
linestyle='dotted',
label='Original Calls',
color='green')
ax.plot(curve.puts.strike,
curve.puts.naturalIV,
linestyle='dotted',
label='Original Puts',
color='red')
plt.legend()
plt.show()
This file is part of the EcoFin-Library (https://github.com/LucaCamerani/EcoFin-Library),
and is released under the "BSD Open Source License".
"""
import os
import pandas as pd
from EcoFin.dataDownload.optionsManager import OptionManager
from EcoFin.dataDownload.ticker import Ticker
from EcoFin.options.deepOptionChain import DeepOptionChain
# -------------------------[Set-up]-------------------------
ticker = Ticker('MSFT')
optionManager = OptionManager(ticker)
exp = optionManager.getExpirationByMaturity(30, method='greater')
optionChain = optionManager.getOptionChain(exp=exp)
# ----------------------------------------------------------
ticker_info = ticker.getInfo()
forwardPrice = optionChain.getForwardPrice()
deepOptionChain = DeepOptionChain(optionChain, computeIV=False)
data = deepOptionChain.getDeepOptionChain()
# ----------------------[EXPORT BLOCK]--------------------------------
path = '../Export/[{}]'.format(ticker.ticker)
if not os.path.exists(path):
os.makedirs(path)
with pd.ExcelWriter('{}/deepOptionChain_[{}].xlsx'.format(path,
"""
import os
import matplotlib.pyplot as plt
from tqdm import tqdm
from EcoFin.dataDownload.optionsManager import OptionManager
from EcoFin.dataDownload.ticker import Ticker
from EcoFin.options.deepOptionChain import DeepOptionChain
from EcoFin.options.equityVIX import EquityVIX
from EcoFin.utils.utils import *
# -------------------------[Set-up]-------------------------
ticker = Ticker('MSFT')
optionManager = OptionManager(ticker)
# Custom
increment = 86400 # 1 day
date1 = 1483228800 # Sunday 01 January 2017
date2 = date1 + increment * 365 * 3
# ----------------------------------------------------------
ticker_info = ticker.getInfo()
output = []
for now in tqdm(range(date1, date2, increment),
desc='Compute history'): # Compute day by day
if optionManager.setNow(now) is not False:
exp = optionManager.getExpirationByMaturity(5, method='greater')
optionChain = optionManager.getOptionChain(exp=exp)
This file is part of the EcoFin-Library (https://github.com/LucaCamerani/EcoFin-Library),
and is released under the "BSD Open Source License".
"""
import matplotlib.pyplot as plt
import numpy as np
from EcoFin.dataDownload.optionsManager import OptionManager
from EcoFin.dataDownload.ticker import Ticker
from EcoFin.options.blackScholesModel import BSM
from EcoFin.stat.equityVolatility import EquityVolatility
# -------------------------[Set-up]-------------------------
ticker = Ticker('MSFT')
optionManager = OptionManager(ticker, now=None)
i = 0 # <- Time To Maturity curve
exp = optionManager.getExpirations()[i]
optionChain = optionManager.getOptionChain(exp=exp)
# ----------------------------------------------------------
strikeList = optionChain.getStrikeList()
volatility_back = 260
series = ticker.getHistory(
end=optionChain.getChainDate()).tail(volatility_back)
price = optionChain.getSpotPrice()
r = optionChain.getRiskFreeRate()
from EcoFin.dataDownload.ticker import Ticker
from EcoFin.options.deepOptionSurface import DeepOptionSurface
from EcoFin.options.utils import daysToMaturity
# ---------------------------[Set-Up]--------------------------------
ticker = Ticker('MSFT')
increment = 86400 # 1 day
date1 = 1551657600 # Monday 4 March 2019
date2 = date1 + increment * 1
# -------------------------------------------------------------------
for now in tqdm.tqdm(range(date1, date2, increment),
desc='Generate frames'): # Compute day by day
try:
optionManager = OptionManager(ticker, now=now)
optSurface = optionManager.getOptionSurface()
deepSurface = DeepOptionSurface(optSurface,
computeIV=False,
computeBSM=False,
progressBar=False)
# get IV surface data
exps = optSurface.getExpirations()
fig = plt.figure(figsize=(15, 10))
fig.suptitle('Option Prices Spread Analysis', fontsize=16)
# Plot option price surfaces
ax = fig.add_subplot(211, projection='3d')
ax.set_title('Option Prices Surfaces')
""" surfaceAnalysis.py Created by Luca Camerani at 11/12/2020, University of Milano-Bicocca. ([email protected]) All rights reserved. This file is part of the EcoFin-Library (https://github.com/LucaCamerani/EcoFin-Library), and is released under the "BSD Open Source License". """ from EcoFin.dataDownload.optionsManager import OptionManager from EcoFin.dataDownload.ticker import Ticker ticker = Ticker('MSFT') ticker_info = ticker.getInfo() optionManager = OptionManager(ticker, now=None) optionSurface = optionManager.getOptionSurface() print(optionSurface.getChainByMaturity(30))
def execute(tick: str):
ticker = Ticker(tick)
optionManager = OptionManager(ticker)
output = pd.DataFrame
for now in range(date1, date2, increment): # Compute day by day
try:
# Exclude bad results and weekends
if optionManager.setNow(now) is not False and datetime.fromtimestamp(now).weekday() not in [5, 6]:
exp = optionManager.getExpirationByMaturity(maturity_min, method='greater')
optionChain = optionManager.getOptionChain(exp=exp)
deepOptionChain = DeepOptionChain(optionChain, computeIV=computeIV, progressBar=False)
summary = {'Date': unixtimestamp_to_date(optionChain.getChainDate()),
'Exp': unixtimestamp_to_date(optionChain.getChainExpiration()),
'Maturity': optionChain.getTimeToMaturity().days,
'ForwardPrice': optionChain.getForwardPrice(),
'SpotPrice': optionChain.getSpotPrice(),
}
# compute signals
chainWeights = ChainWeights(optionChain)
for mode, weights in {'EW': chainWeights.computeEquallyWeights(),
'Beta': chainWeights.computeBetaWeights(),
'ATM': chainWeights.computeATMWeights(),
'OI': chainWeights.computeOpenInterestsWeights(),
'Moneyness': chainWeights.computeMoneynessWeights()}.items():
synopsis = OptionChainSinopsys(deepOptionChain, weights=weights)
OPS = synopsis.computeOptionPriceSpread()
IVS = synopsis.computeImpliedVolatilitySpread()
NAP = synopsis.computeNoArbitragePrice()
OIR = synopsis.computeOpenInterestRatio()
summary['OPS_[{}]'.format(mode)] = OPS.mean
summary['IVS_[{}]'.format(mode)] = IVS.mean
summary['NAP_[{}]'.format(mode)] = NAP.value
summary['NAP_ret_[{}]'.format(mode)] = NAP.ret
summary['OIR_[{}]'.format(mode)] = OIR.mean
PCD = synopsis.computePutCallDelta()
summary['PCD'] = PCD
# Compute volatility metrics
VIX = EquityVIX(deepOptionChain)
summary['VIX_[hist]'] = VIX.getHistoricalVolatility()
summary['VIX_[mean]'] = VIX.getMeanVIX().value
summary['VIX_[beta]'] = VIX.getBetaVIX().value
summary['VIX_[CBOE]'] = VIX.getCBOEVIX()
if output.empty:
output = pd.DataFrame(columns=list(summary.keys()), index=[])
output = output.append(summary, ignore_index=True)
except Exception as e:
logs.append('Error with [{}] - [{}]: {}'.format(ticker.ticker, now, e))
pass
# ----------------------[EXPORT BLOCK]--------------------------------
path = '../Export/BackTest/{}'.format(ticker.ticker)
if not os.path.exists(path):
os.makedirs(path)
try:
with pd.ExcelWriter('{}/backTest_[{}].xlsx'.format(path, maturity_min)) as writer:
output.to_excel(writer, sheet_name='Results', index=False)
except:
pass
This file is part of the EcoFin-Library (https://github.com/LucaCamerani/EcoFin-Library),
and is released under the "BSD Open Source License".
"""
from EcoFin.dataDownload.optionsManager import OptionManager
from EcoFin.dataDownload.ticker import Ticker
# -------------------------[Set-up]-------------------------
ticker = Ticker('MSFT')
# 1Y
increment = 86400
maturity = 30
date1 = 1546300800
date2 = 1577664000
# ----------------------------------------------------------
optionManager = OptionManager(ticker)
ticker_info = ticker.getInfo()
for now in range(date1, date2, increment): # Compute day by day
try:
optionManager.setNow(now)
exp = optionManager.getExpirationByMaturity(maturity, 'greater')
optionChain = optionManager.getOptionChain(exp=exp)
print('Maturity: {} days'.format(optionChain.getTimeToMaturity().days))
except:
pass
This file is part of the EcoFin-Library (https://github.com/LucaCamerani/EcoFin-Library),
and is released under the "BSD Open Source License".
"""
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from matplotlib import cm
from EcoFin.dataDownload.optionsManager import OptionManager
from EcoFin.dataDownload.ticker import Ticker
from EcoFin.options.deepOptionSurface import DeepOptionSurface
from EcoFin.options.utils import daysToMaturity
ticker = Ticker('MSFT')
optionManager = OptionManager(ticker, now=1551657600)
optSurface = optionManager.getOptionSurface()
deepSurface = DeepOptionSurface(optSurface, computeIV=True)
# get IV surface data
exps = optSurface.getExpirations()
extraction = ['strike', 'smile']
surfaceData = deepSurface.getDeepChainByDate(exps[0]).getDeepOptionChain()[extraction]. \
rename(columns={'smile': 'smile_{}'.format(exps[0])})
for exp in exps[1:]:
currentDeepChain = deepSurface.getDeepChainByDate(exp).getDeepOptionChain()
surfaceData = pd.merge(surfaceData,