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optomise2.py
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import backtrader as bt
from datetime import datetime
class firstStrategy(bt.Strategy):
params = (
("period", 21),
("rsi_low", 41),
("rsi_high", 66),
)
def __init__(self):
self.startcash = self.broker.getvalue()
self.rsi = bt.indicators.RSI_SMA(self.data.close, period=self.params.period)
def next(self):
if not self.position:
if self.rsi < self.params.rsi_low:
self.buy(size=100)
else:
if self.rsi > self.params.rsi_high:
self.sell(size=100)
# INPUT DATA TO FEED INTO CEREBRO IS ADDED HERE
if __name__ == '__main__':
# Variable for our starting cash
startcash = 10000
# Create an instance of cerebro
cerebro = bt.Cerebro(optreturn=False)
# Add our strategy
cerebro.optstrategy(firstStrategy, period=range(10, 11), rsi_low=range(30, 40), rsi_high=range(55, 75))
# Get Apple data from Yahoo Finance.
data = bt.feeds.YahooFinanceData(
dataname='MSFT',
fromdate=datetime(2016, 1, 1),
todate=datetime(2018, 1, 1),
buffered=True
)
# Add the data to Cerebro
cerebro.adddata(data)
# Set our desired cash start
cerebro.broker.setcash(startcash)
# RUN STRATEGY THROUGH CEREBRO USING INPUT DATA
opt_runs = cerebro.run()
# CREATE A LIST VARIABLE THAT CONTAINS RESULTS
final_results_list = []
for run in opt_runs:
for strategy in run:
value = round(strategy.broker.get_value(), 2)
PnL = round(value - startcash, 2)
period = strategy.params.period
rsi_low = strategy.params.rsi_low
rsi_high = strategy.params.rsi_high
final_results_list.append([period, rsi_low, rsi_high, PnL])
# Sort Results List
by_period = sorted(final_results_list, key=lambda x: x[0])
by_PnL = sorted(final_results_list, key=lambda x: x[3], reverse=True)
# Print results
#print('Results: Ordered by period:')
#for result in by_period:
#print('Period: {}, rsi_low: {}, rsi_high: {}, PnL: {}'.format(result[0], result[1], result[3], result[4]))
print('Results: Ordered by Profit:')
for result in by_PnL:
print('Period: {}, rsi_low: {}, rsi_high: {}, PnL: {}'.format(result[0], result[1], result[2], result[3]))