def test_ewma_strat():
#prepare data
import DataHandler.DBReader as dbr
from strategy_tester.trade import TradeEquity
from strategy_tester.Portfolio import Portfolio
dbpath = "/home/phcostello/Documents/Data/FinanceData.sqlite"
dbreader = dbr.DBReader(dbpath)
SP500 = dbreader.readSeries("SP500")
dim = 'Adj_Close'
data = SP500
startDate_train = datetime.date(2012,12,30)
endDate_train = datetime.date(2013,6,30)
dataReduced = data.loc[startDate_train:endDate_train]
#Initialise strategy parameters
strat = EWMA_Trend( MA_win_len=50.0,
std_win_len=50.0,
entryScale= 0,
exitScale= 1)
#Initialize Portfolio
#Generate Signals on Market data
#Run strategy
#Setup portfolio
trade_equity_spread = TradeEquity('Equity',
notional=0,
price_series_label='Adj_Close')
port = Portfolio("portfolio", cashAmt=100)
port.add_trade(trade_equity_spread)
#No more trade types
port.fixed_toggle()
strat.plot_flag=True
strat.run_strategy(market_data = data,
portfolio = port)
# plt.show()
plt.figure()
strat.result['Value'].plot()
# plt.show()
# strat.result.to_csv('Results/pairsmd.csv')
from strategy_tester.ResultsAnalyser import ResultsAnalyser
ra = ResultsAnalyser(data= strat.result) #Sharpe for strat
print ra.sharpe_ratio(), ra.get_cumulative_return().iloc[-1,0]
ra2 = ResultsAnalyser(data = SP500,valueIndex='Adj_Close') #Sharpe for SP500
print ra2.sharpe_ratio(), ra2.get_cumulative_return().iloc[-1,0]
combresdata = pd.merge(strat.result,SP500, how='inner', left_index=True, right_index=True)
ra3 = ResultsAnalyser(data = combresdata,valueIndex='Value',referenceIndex='Adj_Close')
print ra3.sharpe_ratio(useMarketRef=True), ra3.get_cumulative_return(useReference=True).iloc[-1,0]
dbreader = DBReader()
AAPL = dbreader.readSeries('AAPL')
SP500 = dbreader.readSeries('SP500')
print AAPL.info()
print SP500.info()
data = pd.merge(pd.DataFrame(AAPL['Adj_Close']),pd.DataFrame(SP500['Adj_Close']), how='inner', left_index=True, right_index=True)
data_dict = {'AAPL':AAPL , 'SP500':SP500}
panel_series = pd.Panel.from_dict(data_dict,
intersect=True,
orient = 'minor')
print 'panel items', panel_series.items
dim = 'Adj_Close'
df_allseries_dim = panel_series[dim]
dataRed = df_allseries_dim.loc['2011-1-1':'2012-1-1']
rets = dataRed['SP500'].pct_change()
print 'rets std', rets.std()
print rets.head()
#dataRed['SP500'].plot()
plt.show()
ra = ResultsAnalyser(dataRed,valueIndex = 'SP500')#, referenceIndex='SP500')
print "vol", ra.get_volatility(annualising_scalar=1, returns=True)
sharpe = ra.sharpe_ratio(useMarketRef=False)
print sharpe
