def __init__(self):
self.vix_records = YahooEquityDAO().get_all_equity_price_by_symbol(
'^VXV', from_date_str='2010-12-1')
self.vxv_records = YahooEquityDAO().get_all_equity_price_by_symbol(
'^VXMT', from_date_str='2010-12-1')
self.vix_values = map(lambda x: x[1], self.vix_records)
self.vxv_values = map(lambda x: x[1], self.vxv_records)
def __init__(self, vol_circle=10):
from_date_str = '2006-07-17'
spy_records = YahooEquityDAO().get_all_equity_price_by_symbol(
'SPY', from_date_str)
self.vol_list = OptionCalculator.get_year_history_volatility_list(
spy_records, vol_circle)
self.vix_records = YahooEquityDAO().get_all_equity_price_by_symbol(
'^VIX', from_date_str)[vol_circle:]
self.vol_values = map(lambda x: x[1] * 100, self.vol_list)
self.vix_values = map(lambda x: x[1], self.vix_records)
def __init__(self):
self.spy_monthly_records = YahooEquityDAO(
).get_equity_monthly_price_by_symbol('SPY')
self.spy_monthly_indicator = self.get_spy_monthly_indicator()
self.vix_records = YahooEquityDAO().get_all_equity_price_by_symbol(
'^VIX', from_date_str='2006-07-17')
self.vxv_records = YahooEquityDAO().get_all_equity_price_by_symbol(
'^VXV', from_date_str='2006-07-17')
self.vix_values = map(lambda x: x[1], self.vix_records)
self.vxv_values = map(lambda x: x[1], self.vxv_records)
def plot_2symbol(self, symbol1, symbol2, from_date_str='2006-07-17'):
fig, ax = plt.subplots()
records1 = YahooEquityDAO().get_all_equity_price_by_symbol(
symbol1, from_date_str=from_date_str)
records2 = YahooEquityDAO().get_all_equity_price_by_symbol(
symbol2, from_date_str=from_date_str)
values1 = map(lambda x: x[1], records1)
values2 = map(lambda x: x[1], records2)
dates = map(lambda x: x[0], records1)
ax.plot(dates, values1, 'r-', label=symbol1)
ax.plot(dates, values2, 'b-', label=symbol2)
plt.legend(bbox_to_anchor=(1.05, 1), loc=8, borderaxespad=0.)
plt.show()
def plot_xiv_vxx(self):
fig, ax1 = plt.subplots()
xiv_records = YahooEquityDAO().get_all_equity_price_by_symbol(
'XIV', from_date_str='2013-12-17')
vxx_records = YahooEquityDAO().get_all_equity_price_by_symbol(
'VXX', from_date_str='2013-12-17')
dates = map(lambda x: x[0], xiv_records)[0:756]
xiv_values = map(lambda x: x[1], xiv_records)[0:756]
vxx_values = map(lambda x: x[1], vxx_records)[0:756]
ax2 = ax1.twinx()
ax1.plot(dates, xiv_values, 'r-', label='xiv')
ax2.plot(dates, vxx_values, 'b-', label='vxx')
plt.legend(bbox_to_anchor=(1.05, 1), loc=8, borderaxespad=0.)
plt.show()
def __init__(self):
self.vix_records = YahooEquityDAO().get_all_equity_price_by_symbol(
'^VIX', from_date_str='2006-07-17')
self.vxv_records = YahooEquityDAO().get_all_equity_price_by_symbol(
'^VXV', from_date_str='2006-07-17')
# self.vix_records = YahooEquityDAO().get_all_equity_price_by_symbol('^VIX', from_date_str='2010-01-01')
# self.vxv_records = YahooEquityDAO().get_all_equity_price_by_symbol('^VXV', from_date_str='2010-01-01')
self.vix_values = map(lambda x: x[1], self.vix_records)
self.vxv_values = map(lambda x: x[1], self.vxv_records)
self.xiv_records = YahooEquityDAO().get_all_equity_price_by_symbol(
'XIV', from_date_str='2006-07-17')
self.xiv_values = map(lambda x: x[1], self.xiv_records)
self.vxx_records = YahooEquityDAO().get_all_equity_price_by_symbol(
'VXX', from_date_str='2006-07-17')
self.vxx_values = map(lambda x: x[1], self.vxx_records)
def history_min(self, symbol, window):
# yahoo_symbol = Symbols.get_mapped_symbol(symbol, Symbols.YahooSymbolMapping)
us_dt = datetime.datetime.now(tz=pytz.timezone('US/Eastern'))
end_time = datetime.datetime(us_dt.year, us_dt.month, us_dt.day, us_dt.hour, us_dt.minute, us_dt.second)
days_window = window/391 + 2
from_date = TradeTime.get_from_date_by_window(days_window)
start_time = datetime.datetime(from_date.year, from_date.month, from_date.day, 0, 0)
rows = YahooEquityDAO().get_min_time_and_price(symbol, start_time, end_time)
return rows[-window:]
def history_min(self, symbol, window, current_date_time):
# us_dt = datetime.datetime.now(tz=pytz.timezone('US/Eastern'))
# end_time = datetime.datetime(us_dt.year, us_dt.month, us_dt.day, us_dt.hour, us_dt.minute, us_dt.second)
end_time = current_date_time
days_window = window/391 + 2
from_date = TradeTime.get_from_date_by_window(days_window, current_date_time.date())
start_time = datetime.datetime(from_date.year, from_date.month, from_date.day, 0, 0)
rows = YahooEquityDAO().get_min_time_and_price(symbol, start_time, end_time)
return rows[-window:]
def plot_vxx(self):
fig, ax = plt.subplots()
vxx_records = YahooEquityDAO().get_all_equity_price_by_symbol(
'VXX', from_date_str='2010-12-17')
vxx_values = map(lambda x: x[1], vxx_records)
dates = map(lambda x: x[0], vxx_records)
ax.plot(dates, vxx_values, 'r-', label='vxx')
plt.legend(bbox_to_anchor=(1.05, 1), loc=8, borderaxespad=0.)
plt.show()
def history(self, symbol, field, window):
fields_dic = {'open': 'openPrice', 'close': 'adjclosePrice', 'high': 'highPrice', 'low': 'lowPrice',
'price': 'adjclosePrice', 'unadj':'closePrice'}
fields = fields_dic.keys()
if field.lower() not in field:
raise Exception('the field should be in %s...'%fields)
price_field = fields_dic[field]
yahoo_symbol = Symbols.get_mapped_symbol(symbol, Symbols.YahooSymbolMapping)
from_date = TradeTime.get_from_date_by_window(window)
rows = YahooEquityDAO().get_all_equity_price_by_symbol(yahoo_symbol, from_date.strftime('%Y-%m-%d'), price_field)
return rows
def plot_vxv_minus_vix(self):
fig, ax = plt.subplots()
dates = map(lambda x: x[0], self.vix_records)
values = map(lambda x, y: x - y, self.vxv_values, self.vix_values)
xiv_records = YahooEquityDAO().get_all_equity_price_by_symbol(
'XIV', from_date_str='2006-07-17')
xiv_values = map(lambda x: x[1], xiv_records)
ax.plot(dates, values, 'r-', label='vxv-vix')
ax.plot(dates, xiv_values, 'b-', label='xiv')
plt.legend(bbox_to_anchor=(1.05, 1), loc=8, borderaxespad=0.)
plt.show()
def history(self, symbol, field, window, current_date):
fields_dic = {'open': 'openPrice', 'close': 'adjclosePrice', 'high': 'highPrice', 'low': 'lowPrice',
'price': 'adjclosePrice', 'unadj':'closePrice'}
fields = fields_dic.keys()
if field.lower() not in field:
raise Exception('the field should be in %s...'%fields)
price_field = fields_dic[field]
yahoo_symbol = Symbols.get_mapped_symbol(symbol, Symbols.YahooSymbolMapping)
from_date = TradeTime.get_from_date_by_window(window+1, current_date) # window + 1: get one day more data.
rows = YahooEquityDAO().get_equity_prices_by_start_end_date(yahoo_symbol, from_date, current_date, price_field)
return rows[0:window] # remove current date data.
def plot_symbol_with_ma(self, symbol, ma_window):
fig, ax = plt.subplots()
records = YahooEquityDAO().get_all_equity_price_by_symbol(
symbol, from_date_str='2006-07-17')
values = map(lambda x: x[1], records)
dates = map(lambda x: x[0], records)[ma_window:]
values1 = pd.Series(values).rolling(window=5).mean().tolist()[5:]
ma_values = pd.Series(values).rolling(
window=ma_window).mean().tolist()[ma_window:]
ax.plot(dates, values1[15:], 'r-', label=symbol)
ax.plot(dates, ma_values, 'b-', label='%s_ma%s' % (symbol, ma_window))
plt.legend(bbox_to_anchor=(1.05, 1), loc=8, borderaxespad=0.)
plt.show()
def condition_momentum(self, symbol, momentum_window=10):
records = YahooEquityDAO().get_all_equity_price_by_symbol(
symbol, from_date_str='2006-07-17')
values = map(lambda x: x[1], records)
result = []
for i, value in enumerate(values):
if i < momentum_window:
result.append(True)
else:
if value > values[i - momentum_window]:
result.append(True)
else:
result.append(False)
return result
def plot_vxv_ma_minus_vix_ma(self, ma_window):
fig, ax = plt.subplots()
dates = map(lambda x: x[0], self.vix_records)[ma_window:]
vxv_ma = pd.Series(self.vxv_values).rolling(
window=ma_window).mean().tolist()[ma_window:]
vix_ma = pd.Series(self.vix_values).rolling(
window=ma_window).mean().tolist()[ma_window:]
values = map(lambda x, y: x - y, vxv_ma, vix_ma)
xiv_records = YahooEquityDAO().get_all_equity_price_by_symbol(
'XIV', from_date_str='2006-07-17')
xiv_values = map(lambda x: x[1], xiv_records)[ma_window:]
ax.plot(dates, values, 'r-', label='vxv_ma-vix_ma, ma=%s' % ma_window)
ax.plot(dates, xiv_values, 'b-', label='xiv')
plt.legend(bbox_to_anchor=(1.05, 1), loc=8, borderaxespad=0.)
plt.show()
def plot_z_score_with_xiv(self, ma_window_short=7, ma_window_long=20):
rate = map(lambda x, y: x / y, self.vxv_values, self.vix_values)
rate_ma_short = pd.Series(rate).rolling(
window=ma_window_short).mean().tolist()
rate_ma_long = pd.Series(rate).rolling(
window=ma_window_long).mean().tolist()
rate_std = pd.Series(rate).rolling(
window=ma_window_long).std().tolist()
zscore = map(lambda x, y, z: (x - y) / z,
rate_ma_short[ma_window_long:],
rate_ma_long[ma_window_long:], rate_std[ma_window_long:])
dates = map(lambda x: x[0], self.vxv_records)[ma_window_long:]
xiv_records = YahooEquityDAO().get_all_equity_price_by_symbol(
'XIV', from_date_str='2006-07-17')
xiv_values = map(lambda x: x[1], xiv_records[ma_window_long:])
fig, ax1 = plt.subplots()
ax2 = ax1.twinx()
ax1.plot(dates, zscore, 'r-', label='z score')
ax2.plot(dates, xiv_values, 'b-', label='xiv')
plt.legend(bbox_to_anchor=(1.05, 1), loc=8, borderaxespad=0.)
plt.show()
def _get_daily_records(symbol, start, end):
return YahooEquityDAO().get_equity_prices_by_start_end_date(symbol, start, end)
def _get_min_records(symbol, start, end):
return YahooEquityDAO().get_min_time_and_price(symbol, start, end)
risk_free_interest_rate,
sigma,
flag='c'):
theta = vollib.black_scholes.greeks.numerical.theta(
flag, underlying_price, strike_price, left_days / 365.0,
risk_free_interest_rate, sigma)
return theta
@staticmethod
def get_rho(underlying_price,
strike_price,
left_days,
risk_free_interest_rate,
sigma,
flag='c'):
rho = vollib.black_scholes.greeks.numerical.rho(
flag, underlying_price, strike_price, left_days / 365.0,
risk_free_interest_rate, sigma)
return rho
if __name__ == '__main__':
import datetime
from dataaccess.db import YahooEquityDAO
from_date_str = (datetime.date.today() -
datetime.timedelta(100)).strftime('%Y-%m-%d')
equity_records = YahooEquityDAO().get_all_equity_price_by_symbol(
'SPY', from_date_str)
results = OptionCalculator.get_year_history_volatility_list(equity_records)
print results
def _get_equity_price_list_as_dic(symbol):
records = YahooEquityDAO().get_all_equity_price_by_symbol(symbol)
result = {}
for [d,v] in records:
result[int(d.strftime('%Y%m%d'))] = v
return result
def history_30_min(self, symbol, window):
return YahooEquityDAO().get_latest_equity_30_min_prices(symbol, window)
def history_30_min(self, symbol, window, current_date_time):
return YahooEquityDAO().get_latest_equity_30_min_prices(symbol, window, end_time=current_date_time)
def __init__(self):
self.xiv_records = YahooEquityDAO().get_all_equity_price_by_symbol(
'XIV', from_date_str='2006-07-17')
self.xiv_values = map(lambda x: x[1], self.xiv_records)