def Xindicator(self, syms, dates):
sma = ind.SMA(syms, 20, dates)
bb = ind.BB(syms, 20, 2, dates)
_, macd = ind.MACD(syms, 12, 26, 9, dates)
rsi = ind.RSI(syms, 14, dates)
X = pd.DataFrame({'SMA': sma, 'BB': bb, "MACD": macd, "RSI": rsi})
return X
def calculate_thres():
symbol = 'JPM'
sd=dt.datetime(2008,1,1)
ed=dt.datetime(2009,12,31)
date = pd.date_range(sd - dt.timedelta(days=50), ed)
stockvals = get_data([symbol], date)
stockvals = stockvals.loc[:, [symbol]]
sma = ind.SMA(symbol, 20, date, gen_plot = False)
sma = sma[sma.index >= sd]
bb = ind.BB(symbol, 20, 2, date, gen_plot = False)
bb = bb[bb.index >= sd]
_, macd = ind.MACD(symbol, 12, 26, 9, date, gen_plot = False)
macd = macd[macd.index >= sd]
rsi = ind.RSI(symbol, 14, date, gen_plot = False)
rsi = rsi[rsi.index >= sd]
bounds = [(0, 1), (60, 85), (15,40)]
optimal_thres = differential_evolution(optimalize, bounds, args=(sma, bb, macd, rsi, ))
return(optimal_thres)
def testPolicy(symbol = 'JPM', sd=dt.datetime(2008,1,1), ed=dt.datetime(2009,12,31), sv = 100000):
date = pd.date_range(sd - dt.timedelta(days=50), ed)
stockvals = get_data([symbol], date)
stockvals = stockvals.loc[:, [symbol]]
sma = ind.SMA(symbol, 20, date, gen_plot = False)
sma = sma[sma.index >= sd]
bb = ind.BB(symbol, 20, 2, date, gen_plot = False)
bb = bb[bb.index >= sd]
_, macd = ind.MACD(symbol, 12, 26, 9, date, gen_plot = False)
macd = macd[macd.index >= sd]
rsi = ind.RSI(symbol, 14, date, gen_plot = False)
rsi = rsi[rsi.index >= sd]
thres = [0.99243522, 84.70103144, 25.01519814]
"""
from calculate_thres
"""
order_signal = signal(sma, bb, macd, rsi, thres)
order = Order(order_signal)
return order