def get_options_dict(ticker_list,warm_dict=None):
if not warm_dict:
tdict={}
else:
tdict=warm_dict
for ticker in ticker_list:
if not tdict.has_key(ticker):
print '****\n****\n**** getting for %s\n****\n****' % ticker
op = Options(ticker, 'yahoo')
try:
data = op.get_all_data()
up = op.underlying_price
time.sleep(1200)
tdict[ticker]={'data':data,'up':up}
except pd.io.data.RemoteDataError:
print'Request Refused, Dumping and Exiting...'
cPickle.dump(tdict,open('warm_dict.pkl','wb'))
sys.exit(0)
return tdict
def get_options(sym, expiry, above_below=0):
opt = Options(sym, 'yahoo')
now = datetime.datetime.now()
opt_data = opt.get_options_data(expiry=expiry)
if (above_below > 0):
opt_data = opt.get_near_stock_price(expiry=expiry, put=True, above_below=above_below)
now2 = datetime.datetime.now()
print 'get_options():', now2-now
return (now2, opt_data)
def __validate_source_connection__(self):
""" Check internet connection """
test_stock = 'AAPL'
try:
aapl = Options(test_stock, self.source)
data = aapl.get_all_data()
return True
except Exception:
return False
def __validate_source_connection__(self):
""" Check internet connection """
test_stock='AAPL'
try:
aapl = Options(test_stock, self.source)
data = aapl.get_all_data()
return True
except Exception:
return False
def retrieve_option_chain(ticker="SPY"):
spy_data = pandas.DataFrame()
print(" --> Today's option chain not on system: downloading it now... ")
try:
spy_options = Options(ticker, "yahoo")
spy_data = spy_options.get_all_data()
spy_data = spy_data.reset_index()
if "Symbol" in spy_data.keys():
spy_data = spy_data.set_index("Symbol")
spy_data.to_csv(filename, date_format="%Y-%m-%d")
# Load the data from the CSV you just wrote
# (this ensures that re-shaping is always done
# by retrieve_option_chain_from_file() )
spy_data = retrieve_option_chain_from_file(filename)
except:
print("Error with retrieving data. Please double-check the ticker symbol")
return spy_data
return spy_data
def pull_data(self, ticket_list):
"""
Pull online option data
:param ticket_list: list contains tickets you want to download
:return: option data dict, in the form of [ ticket : DataFrame, ... ]
"""
if isinstance(ticket_list, str):
ticket_list = (ticket_list, )
option_dict = {}
for ticket in ticket_list:
print "Pull Option Data : %s ..." % ticket
try:
option_method = Options(ticket, self.source)
option_dict[ticket] = option_method.get_all_data()
if len(option_dict[ticket]) == 0:
print "Length of data is Zero during the time asked"
except Exception as err_message:
option_dict[ticket] = None
print "Exception: %s" % err_message
# raise RuntimeError("Can't not download Stock: %s" % stock)
return option_dict
def pull_data(self, ticket_list):
"""
Pull online option data
:param ticket_list: list contains tickets you want to download
:return: option data dict, in the form of [ ticket : DataFrame, ... ]
"""
if isinstance(ticket_list, str):
ticket_list = (ticket_list, )
option_dict = {}
for ticket in ticket_list:
print "Pull Option Data : %s ..." % ticket
try:
option_method = Options(ticket, self.source)
option_dict[ticket] = option_method.get_all_data()
if len(option_dict[ticket]) == 0:
print "Length of data is Zero during the time asked"
except Exception as err_message:
option_dict[ticket] = None
print "Exception: %s" % err_message
# raise RuntimeError("Can't not download Stock: %s" % stock)
return option_dict
# pick a recent date and subtract seven days to be sure we get a quote # http://pymotw.com/2/datetime/#date-arithmetic today = dt.date.today() one_week = dt.timedelta(days=7) start = today - one_week stock = web.DataReader(ticker, 'yahoo', start) print(stock.tail()) # just to see what we have # take the last close (that's what the -1 does) atm = stock.ix[-1,'Close'] # the -1 takes the last observation #%% # get option prices for same ticker # http://pandas.pydata.org/pandas-docs/stable/remote_data.html#yahoo-finance-options option = Options(ticker, 'yahoo') expiry = dt.date(2014, 12, 20) data_calls = option.get_call_data(expiry=expiry) data_puts = option.get_put_data(expiry=expiry) print(data_calls.tail()) print(data_puts.tail()) #%% # plot puts v strike, call v strike calls_bid = data_calls['Bid'] calls_ask = data_calls['Ask'] calls_strikes = data_calls['Strike'] calls_mid = (data_calls['Bid'] + data_calls['Ask'])/2
def get_option_data(self, symbol):
aapl = Options(symbol, 'google')
data = aapl.get_all_data()
return data
from pandas.io.data import Options
import datetime
aapl = Options('AAPL', 'yahoo')
expiry = datetime.date(2014, 5, 1)
aapl.get_call_data(expiry=expiry)
for i in range(10000):
sigma=0.0001*(i+1)
d1=(log(S/X)+(r+sigma*sigma/2.)*T)/(sigma*sqrt(T))
d2 = d1-sigma*sqrt(T)
c2=S*stats.norm.cdf(d1)-X*exp(-r*T)*stats.norm.cdf(d2)
abs_diff=abs(c2-c)
#print 'i=',i,'c=', c,'c2=',c2,'abs_diff=',abs_diff,'min_value=',min_value
if abs_diff<min_value:
min_value=abs_diff
implied_vol=sigma
k=i
return implied_vol
ticker='IBM'
m=2
y=2014
s=185.08
r=0.0003
T=2./12.0
x = Options(ticker,'yahoo')
puts,calls = x.get_options_data(month=m,year=y)
print 'done'
n=len(calls.Strike)
for i in range(n):
x=calls.Strike[i]
c=(calls.Bid[i]+calls.Ask[i])/2.0
if c >0:
vol=implied_vol_call_min(s,x,T,r,c)
print x,c,vol
# -*- coding: utf-8 -*-
"""
Created on Thu Jul 16 18:02:31 2015
@author: justin.malinchak
"""
#import pullprices_optionsonly as pp
#
#pp.options('VIX',
# '2015-07-17',
# 'c:\\Batches\\$Work')
from pandas.io.data import Options
temp = Options('SPY','yahoo')
z = temp.get_options_data(7,2014)
print z
def get_option_data(tickrr, exp_date):
x = Options(ticker, 'yahoo')
puts, calls = x.get_options_data(expiry=exp_date)
return puts, calls
>>> implied_vol_call(40,40,1.,0.1,5.31)
(39, 0.2, 0.0021293661356418525)
>>>
"""
from scipy import log, exp, sqrt, stats
for i in range(200):
sigma = 0.005 * (i + 1)
d1 = (log(S / X) + (r + sigma * sigma / 2.) * T) / (sigma * sqrt(T))
d2 = d1 - sigma * sqrt(T)
diff = c - (S * stats.norm.cdf(d1) -
X * exp(-r * T) * stats.norm.cdf(d2))
if abs(diff) <= 0.01:
return sigma
ticker = 'IBM'
m = 2
y = 2014
s = 185.08
x = Options(ticker, 'yahoo')
calls, puts = x.get_options_data(month=m, year=y)
print 'done'
n = len(calls.Strike)
for i in range(n):
x = calls.Strike[i]
c = (calls.Bid[i] + calls.Ask[i]) / 2.0
if c > 0:
vol = implied_vol_call(s, x, 2. / 12., 0.03, c)
print x, c, vol
from pandas.io.data import Options
import datetime as dt
#import matplotlib.pylab as plt
# ticker
ticker = 'spy'
today = dt.date.today()
one_week = dt.timedelta(days=7)
start = today - one_week
stock = web.DataReader(ticker, 'yahoo', start)
# take the last close (-1 is the last, 'Close' is the close)
atm = stock.ix[-1, 'Close'] # the -1 takes the last observation
print('Stock price (at the money): ', atm)
# get option prices for same ticker
option = Options(ticker, 'yahoo')
expiry = dt.date(2016, 2, 19)
#data_calls = option.get_call_data(expiry=expiry).dropna()
#data_puts = option.get_put_data(expiry=expiry).dropna()
# compute mid of bid and ask and arrange series for plotting
calls_bid = data_calls['Bid']
calls_ask = data_calls['Ask']
calls_strikes = data_calls['Strike']
calls_mid = (data_calls['Bid'] + data_calls['Ask']) / 2
puts_strikes = data_puts['Strike']
puts_mid = (data_puts['Bid'] + data_puts['Ask']) / 2
# plot call and put prices v strike
plt.plot(calls_strikes, calls_mid, 'r', lw=2, label='calls')
def get_option_data(tickrr,exp_date):
x = Options(ticker,'yahoo')
puts,calls = x.get_options_data(expiry=exp_date)
return puts, calls
""" Name : 4375OS_10_33_option_data_Yahoo.py Book : Python for Finance Publisher: Packt Publishing Ltd. Author : Yuxing Yan Date : 12/26/2013 email : [email protected] [email protected] """ from pandas.io.data import Options x = Options('IBM','yahoo') puts,calls = x.get_options_data() print calls.head()
# pick a recent date and subtract seven days to be sure we get a quote # http://pymotw.com/2/datetime/#date-arithmetic today = dt.date.today() one_week = dt.timedelta(days=7) start = today - one_week stock = web.DataReader(ticker, 'yahoo', start) print(stock.tail()) # just to see what we have # take the last close (that's what the -1 does) atm = stock.ix[-1, 'Close'] # the -1 takes the last observation #%% # get option prices for same ticker # http://pandas.pydata.org/pandas-docs/stable/remote_data.html#yahoo-finance-options option = Options(ticker, 'yahoo') expiry = dt.date(2014, 12, 20) data_calls = option.get_call_data(expiry=expiry) data_puts = option.get_put_data(expiry=expiry) print(data_calls.tail()) print(data_puts.tail()) #%% # plot puts v strike, call v strike calls_bid = data_calls['Bid'] calls_ask = data_calls['Ask'] calls_strikes = data_calls['Strike'] calls_mid = (data_calls['Bid'] + data_calls['Ask']) / 2
def call_data(tickrr,exp_date):
x = Options(ticker,'yahoo')
data= x.get_call_data(expiry=exp_date)
return data
startTickerIndex = 0
if startTickerIndex >= len(tickersList):
startTickerIndex = 0
for i in range(startTickerIndex, len(tickersList)):
ticker = tickersList[i]
if ticker in downloaded:
print "Already downloaded",ticker," ... Skipping."
continue
print "Downloading", ticker, "...",
# download the data
toDownload = Options(ticker, "yahoo")
try:
data = toDownload.get_options_data();
pd.DataFrame(data).to_csv(baseDir+"/data/" + ticker)
print "done."
except (ValueError, RemoteDataError, StopIteration) as e:
print "skipped."
print e
downloaded.add(ticker)
last = open(baseDir+"last-downloaded", "w")
if i != len(tickersList) - 1:
last.write(ticker)
last.close()
time.sleep(0.1)
""" Name : 4375OS_10_33_option_data_Yahoo.py Book : Python for Finance Publisher: Packt Publishing Ltd. Author : Yuxing Yan Date : 12/26/2013 email : [email protected] [email protected] """ from pandas.io.data import Options x = Options('IBM', 'yahoo') puts, calls = x.get_options_data() print calls.head()
start = dt.datetime(2015, 1, 1)
msi = web.DataReader('msi', 'yahoo', start)
msi['Close'].plot()
#%%
"""
Options data -- doesn't work
http://pandas.pydata.org/pandas-docs/stable/remote_data.html#yahoo-finance-options
"""
import pandas as pd
print('Pandas version:', pd.__version__)
from pandas.io.data import Options
aapl = Options('aapl', 'yahoo')
data = aapl.get_all_data()
#%%
"""
convert do file to pandas format and variable labels
CPS
http://www.nber.org/data/cps_progs.html
MEPS
http://meps.ahrq.gov/mepsweb/data_stats/download_data_files_detail.jsp?cboPufNumber=HC-155
"""
import pandas as pd
url = 'http://www.nber.org/data/progs/cps/cpsmar2014.dct'
pd.read_csv(url, sep='\s+')
#open(url).read()
# -*- coding: utf-8 -*-
"""
Created on Thu Jul 16 18:02:31 2015
@author: justin.malinchak
"""
#import pullprices_optionsonly as pp
#
#pp.options('VIX',
# '2015-07-17',
# 'c:\\Batches\\$Work')
from pandas.io.data import Options
temp = Options('SPY', 'yahoo')
z = temp.get_options_data(7, 2014)
print z
from pandas.io.data import Options
spy = Options('spy', 'yahoo')
chain = spy.get_all_data()
import time
import math
t1 = time.time()
options = pd.read_csv("options.csv")
tickers = options['Symbol']
#tickers=['GNW','MBI','VLO','BP']
yahoo_cap_url = 'http://finance.yahoo.com/d/quotes.csv?s='
bank_roll = 14000
offers = []
for e in tickers:
expiry_2 = (2018, 1)
expiry_1 = (2017, 1)
tick = Options(e, 'yahoo')
try:
frame = tick.get_call_data(month=expiry_2[1], year=expiry_2[0])
a = list(frame.index)
except:
try:
frame = tick.get_call_data(month=expiry_1[1], year=expiry_1[0])
a = list(frame.index)
except:
print e
pass
strike = []
for e in a:
strike.append(e[0])
frame['Strike'] = strike
def get_straddle():
options = Options("AAPL", "yahoo")
call = get_price(options, True, False)
put = get_price(options, False, True)
return call + put
options.rror.iloc[i] = (p / -l)
options = options.drop(['sv', 'lv'], axis = 1)
return options
###############################################################################
# Calculate Best Options for multiple indexes and secruities
###############################################################################
securities = ['spy', 'iwm', 'qqq', 'aapl', 'nflx', 'kmx']
for s in securities:
try:
opt = Options(s, 'yahoo')
today = datetime.datetime.today()
today = datetime.date(today.year, today.month, today.day)
for e in opt.expiry_dates:
if (e - today).days > 4 and (e - today).days < 15:
expiry = e
call = opt.get_call_data(expiry=expiry)
price = call.Underlying_Price[0]
prices, p = cdf(s, expiry, price)
def call_data(tickrr, exp_date):
x = Options(ticker, 'yahoo')
data = x.get_call_data(expiry=exp_date)
return data
"""
"""
the usual checks
"""
import sys
import pandas as pd
print('\nPython version: ', sys.version)
print('\nPandas version: ', pd.__version__, '\n')
#%%
"""
Remote data access
"""
from pandas.io.data import Options
aapl = Options('aapl', 'yahoo')
data = aapl.get_all_data()
#%%
"""
Set up simple dataframes to play with
"""
# create arbitrary dataframe
gdp = [2, 5, 7, 9]
pop = [9, 6, 3, 10]
cty = ['USA', 'USA', 'FRA', 'FRA']
year = ['2010', '2011', '2012', '2013']
data = {'gdp': gdp, 'pop': pop, 'cty': cty}
""" Name : 4375OS_10_34_get_option_data_given_year_month.py Book : Python for Finance Publisher: Packt Publishing Ltd. Author : Yuxing Yan Date : 12/26/2013 email : [email protected] [email protected] """ from pandas.io.data import Options ticker='IBM' month=2 year=2014 x = Options(ticker,'yahoo') puts,calls = x.get_options_data(month,year) print puts.head()
from pandas.io.data import Options
aapl = Options('AAPL')
vals = aapl.get_options_data()
print(vals)
import pandas as pd, datetime
from pandas_datareader import data
# Stocks
start=datetime.datetime(2013, 1, 1)
end=datetime.datetime(2015, 9, 30)
s = data.DataReader("SSW", 'yahoo', start, end)
print s.head()
# Options
from pandas.io.data import Options
aapl = Options('AAPL',"yahoo")
df = aapl.get_options_data()
print df.head()
options.rror.iloc[i] = (p / -l)
options = options.drop(['sv', 'lv'], axis=1)
return options
###############################################################################
# Calculate Best Options for multiple indexes and secruities
###############################################################################
securities = ['spy', 'iwm', 'qqq', 'aapl', 'nflx', 'kmx']
for s in securities:
try:
opt = Options(s, 'yahoo')
today = datetime.datetime.today()
today = datetime.date(today.year, today.month, today.day)
for e in opt.expiry_dates:
if (e - today).days > 4 and (e - today).days < 15:
expiry = e
call = opt.get_call_data(expiry=expiry)
price = call.Underlying_Price[0]
prices, p = cdf(s, expiry, price)
bull = bull_call_spread()
if bull.empty:
