def manual_test_policy_bb(symbol, sd, ed, start_value):
trades_df = manual_bb_indicator(symbol, sd, ed)
commission = 0
impact = 0.005
# pass df_trade to marketsimcode to plot
portvals = mktsim.compute_portvals(trades_df=trades_df, start_val=start_value, commission=commission, impact=impact)
mktsim.gen_plot(trades_df, portvals, "BollingerBandStrategy: Fund vs Benchmark", symbol)
def test_policy_sma(symbol, sd, ed, start_value):
trades_df = sma_indicator(symbol, sd, ed)
commission = 9.95
impact = 0.005
portvals = mktsim.compute_portvals(symbol,
trades_df=trades_df,
start_val=start_value,
commission=commission,
impact=impact)
mktsim.gen_plot(trades_df, portvals,
"SimpleMovingAverageStrategy: Fund vs Benchmark")
elif prices_JPM.iloc[i + 1] < prices_JPM.iloc[i]:
trades_df.iloc[i] = -1000
else:
trades_df.iloc[i] = 0
#print trades_df
#convert to df
trades_df = trades_df.to_frame()
return trades_df
if __name__ == "__main__":
symbol = 'JPM'
start_value = 100000
sd = dt.date(2008, 1, 1)
ed = dt.date(2009, 12, 31)
commission = 0
impact = 0
trades_df = testPolicy(symbol=symbol,
start_date=sd,
end_date=ed,
start_value=start_value)
#print trades_df
# pass df_trade to marketsimcode to plot
portvals = mktsim.compute_portvals(trades_df=trades_df,
start_val=start_value,
commission=commission,
impact=impact)
mktsim.gen_plot(trades_df, portvals,
"BestPossibleStrategy: Fund vs Benchmark")
sym = "JPM" #USE JPM for reports
sd_insample = dt.date(2008, 1, 1)
ed_insample = dt.date(2009, 12, 31)
# train with in-sample data
sl_learner = sl.StrategyLearner(verbose=True, impact=impact)
sl_learner.addEvidence(symbol=sym,
sd=sd_insample,
ed=ed_insample,
sv=10000)
# test with in-sample data
print "Test In-sample with ML strategy\n"
df_delta_trades_ML = sl_learner.testPolicy(symbol=sym,
sd=sd_insample,
ed=ed_insample,
sv=10000)
# pass df_trade to marketsimcode to plot
portvals = mktsim.compute_portvals_trade_delta(
trades_delta_df=df_delta_trades_ML,
start_val=start_value,
commission=commission,
impact=impact,
symbol=sym)
mktsim.gen_plot(df_delta_trades_ML,
portvals,
"Strategy Learner: Fund vs Benchmark",
symbol=sym)
#indic.bollingerBand(sym="JPM", sd=dt.date(2008,1,1), ed=dt.date(2009,12,31))
def manual_test_policy_ema(symbol, sd, ed, start_value):
trades_df = manual_ema_indicator(symbol, sd, ed)
commission = 0
impact = 0.005
portvals = mktsim.compute_portvals(trades_df=trades_df, start_val=start_value, commission=commission, impact=impact)
mktsim.gen_plot(trades_df, portvals, "ExponentialMovingAverageStrategy: Fund vs Benchmark", symbol)