def run_strategy(self, market_data, portfolio):
if (pd.isnull(market_data)).any()[0]:
#Raise this error to make sure there's no gaps in data
raise ValueError("Series XY = {0}, {1} do not have equal date range".format(self.series_x_label, self.series_y_label))
reg_params = [self.intercept, self.scaling]
md = pairs_md(market_data,
xInd = self.series_x_label,
yInd = self.series_y_label)
md.generateTradeSigs(windowLength = self.window_length,
entryScale= self.entry_scale,
exitScale = self.exit_scale,
# ewma_par= 100,
reg_params = reg_params
)
Reversion_EntryExitTechnical.run_strategy(self,
md,
portfolio)
if self.plot_flag:
md.plot_spreadAndSignals()
def fit(self, data):
#drop na data so that can fit ols
md = pairs_md(data.dropna(), self.series_x_label, self.series_y_label)
md.fitOLS()
self.scaling = md.results.params[self.series_x_label]
self.intercept = md.results.params['const']
def PairTradeSP500():
#Setup market data
import sqlite3
con = sqlite3.connect("/home/phcostello/Documents/Data/FinanceData.sqlite")
SP500 = md.read_db(con, "SP500")
BA = md.read_db(con,"BA")
dim = 'Adj Close'
SP500AdCl = SP500[dim]
BAAdCl = BA[dim]
dataObj = pd.merge(pd.DataFrame(BAAdCl), pd.DataFrame(SP500AdCl), how='inner',left_index = True, right_index = True)
dataObj.columns = ['y','x']
pmd = md.pairs_md(dataOb=dataObj,xInd='x',yInd='y')
#pmd.printSummary()
pmd.fitOLS()
pmd.generateTradeSigs(50, entryScale=1, exitScale=0.5)
#pmd.plot_spreadAndSignals()
#Setup portfolio
spreadTrade = td.TradeEquity("spread", notional=0, price_series_label="spread")
port = pf.Portfolio("portfolio", cashAmt=100)
port.add_trade(spreadTrade)
#No more trade types
port.fixed_toggle()
#Setup Strategy
pairsStrat = Pairs_Trade(market_data=pmd, portfolio=port, initial_time_index=0)
pairsStrat.run_strategy()
#print pairsStrat.result['Signal']
#print pairsStrat.result.index[1:10]
#print "Sharpe Ratio", pairsStrat.sharpe_ratio()
fig = plt.figure()
ax1= fig.add_subplot(3,1,1)
ax2 = fig.add_subplot(3,1,2)
ax3= fig.add_subplot(3,1,3)
pairsStrat.market_data.core_data[['spread','entryUpper','exitUpper','entryLower','exitLower']].plot(ax=ax1)
pairsStrat.result['Value'].plot(ax=ax2)
pd.DataFrame(100*SP500AdCl/SP500AdCl[0]).plot(ax=ax2)
#pd.DataFrame(100*SP500AdCl/SP500AdCl[0]).plot(ax=ax3)
rets = pairsStrat.get_returns(referenceIndex='x')
rets.plot(ax=ax3)
#plt.show()
dd = pairsStrat.draw_downs()
#print dd['Drawdown']
maxDD = max(dd['Drawdown'])
maxDDr = dd.ix[dd['Drawdown'] == maxDD]
#print maxDDr.ix[1]
#dd.to_csv('../dd.csv', sep='\t')
#plt.show()
pairsStrat.summary()
def PairTradeSP500(stdWindowLength, entryScale, exitScale):
#Read in data and setup object
dbpath = "/home/phcostello/Documents/Data/FinanceData.sqlite"
the_data_reader = dr.DBReader(dbpath)
SP500 = the_data_reader.readSeries("SP500")
BA = the_data_reader.readSeries("BA")
dim = 'Adj_Close' #Choose dim to analyse
SP500AdCl = SP500[dim]
BAAdCl = BA[dim]
# print SP500AdCl.head()
# print BAAdCl.head()
dataObj = pd.merge(pd.DataFrame(BAAdCl), pd.DataFrame(SP500AdCl), how='inner',left_index = True, right_index = True)
dataObj.columns = ['y','x']
#Construct data object for pairs trading strat
pmd = md.pairs_md(dataOb=dataObj,xInd='x',yInd='y')
maxdate = datetime.date(2013,1,1)
pmd.core_data = pmd.core_data[:maxdate]
pmd.fitOLS()
pmd.generateTradeSigs(stdWindowLength, entryScale, exitScale)
#Setup portfolio
spreadTrade = td.TradeEquity("spread", notional=0, price_series_label="spread")
port = pf.Portfolio("portfolio", cashAmt=100)
port.add_trade(spreadTrade)
#No more trade types
port.fixed_toggle()
#Setup Strategy
pairsStrat = tsc.Reversion_EntryExitTechnical(market_data=pmd, portfolio=port, initial_time_index=1)
return pairsStrat
tic = time.clock()
pairsStrat.run_strategy()
toc = time.clock()
print "strategy took {} seconds to run".format(toc - tic)
outfile = open("pickled_pairs.pkl", 'wb')
pairs_strategy_run = pickle.dump(pairsStrat,outfile)
outfile.close()
from ImplementedStrategies import PairTradeSP500
#Read in data and setup object
dbpath = "/home/phcostello/Documents/Data/FinanceData.sqlite"
the_data_reader = dr.DBReader(dbpath)
SP500 = the_data_reader.readSeries("SP500")
BA = the_data_reader.readSeries("BA")
dim = 'Adj_Close' #Choose dim to analyse
SP500AdCl = SP500[dim]
BAAdCl = BA[dim]
dataObj = pd.merge(pd.DataFrame(BAAdCl), pd.DataFrame(SP500AdCl), how='inner',left_index = True, right_index = True)
dataObj.columns = ['y','x']
#Construct data object for pairs trading strat
pmd = md.pairs_md(dataOb=dataObj,xInd='x',yInd='y')
maxdate = datetime.date(2013,1,1)
pmd.core_data = pmd.core_data[:maxdate]
pmd.fitOLS()
def optimFunc(pars):
stdWindowLength = pars[0]
entryScale= pars[1]
exitScale= pars[2]
# #Read in data and setup object
# dbpath = "/home/phcostello/Documents/Data/FinanceData.sqlite"
# the_data_reader = dr.DBReader(dbpath)
