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strategy.py
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strategy.py
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from __future__ import (absolute_import, division,
print_function, unicode_literals)
import datetime # For datetime objects
import os.path # To manage paths
import sys # To find out the script name (in argv[0])
# Import the backtrader platform
import backtrader as bt
import backtrader.feeds as btfeeds
import pandas as pd
import streamlit as st
# Create a Stratey
class TestStrategy(bt.Strategy):
params = (('p1', 8),
('p2', 21),
('p3', 55),
('p4', 144),
('rsi', 40),
('rr', 2),
('rrp', 1),
('candleper', 0.005),
('delay', -1),
('pricelimitper', 0.001),
('bodyper', 0.7),
)
def log(self, txt, dt=None):
''' Logging function fot this strategy'''
dt = dt or self.datas[0].datetime.date(0)
#print('%s, %s' % (dt.isoformat(), txt))
print('%s,%s, %s' % (dt.strftime("%d/%m/%Y"),self.datas[0].datetime.time().strftime("%H:%M:%S") ,txt))
st.sidebar.write('%s,%s, %s' % (dt.strftime("%d/%m/%Y"),self.datas[0].datetime.time().strftime("%H:%M:%S") ,txt))
def __init__(self):
# Keep a reference to the "close" line in the data[0] dataseries
self.dataclose = self.datas[0].close
self.dataopen = self.datas[0].open
self.datalow = self.datas[0].low
self.datahigh = self.datas[0].high
# To keep track of pending orders and buy price/commission
self.order = None
self.buyprice = None
self.buycomm = None
self.sl = 1
self.reward = 0
# Add a MovingAverageSimple indicator
self.sma1 = bt.indicators.EMA(period=self.p.p1)
self.sma2 = bt.indicators.EMA(period=self.p.p2)
self.sma3 = bt.indicators.EMA(period=self.p.p3)
self.sma4 = bt.indicators.EMA(period=self.p.p4)
self.rsi = bt.indicators.RSI(self.datas[0],plothlines=[55, 45])
#self.vwap = bt.indicators.VWAP(self.datas[0])
def notify_order(self, order):
if order.status in [order.Submitted, order.Accepted]:
# Buy/Sell order submitted/accepted to/by broker - Nothing to do
return
# Check if an order has been completed
# Attention: broker could reject order if not enough cash
if order.status in [order.Completed]:
if order.isbuy():
self.log(
'BUY EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f, candle_pos = %.2f,' %
(order.executed.price,
order.executed.value,
order.executed.comm,
len(self)))
self.buyprice = order.executed.price
self.buycomm = order.executed.comm
else: # Sell
self.log('SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f candle_pos =%.2f,' %
(order.executed.price,
order.executed.value,
order.executed.comm,
len(self)))
self.bar_executed = len(self)
elif order.status in [order.Canceled, order.Margin, order.Rejected]:
self.log('Order Canceled/Margin/Rejected')
self.order = None
def notify_trade(self, trade):
if not trade.isclosed:
return
self.log('OPERATION PROFIT, GROSS %.2f, NET %.2f \n \n' %
(trade.pnl, trade.pnlcomm))
def next(self):
# Simply log the closing price of the series from the reference
#self.log('Close, %.2f' % self.dataclose[0])
# Check if time is greater 9 30 or not
if (self.data.datetime.time() < datetime.time(9,30) ) or (self.data.datetime.time() > datetime.time(15,10)) :
return
# Check if an order is pending ... if yes, we cannot send a 2nd one
if self.order:
return
# Check if we are in the market
if self.position.size == 0:
# Not yet ... we MIGHT BUY if ... self.datas[0].close
c1 = (self.dataclose[self.p.delay] > self.dataopen[self.p.delay]) # Green Candle
c2 = (self.rsi[self.p.delay] >= self.p.rsi) # RSI>55
c3 = (self.dataclose[self.p.delay] > self.sma1[self.p.delay]) & (self.dataclose[self.p.delay] > self.sma2[self.p.delay]) # Close above EMA1 and 2
c4 = (self.datalow[self.p.delay] < self.sma1[self.p.delay]) & (self.datalow[self.p.delay] < self.sma2[self.p.delay]) #low below 9 and 21 ema
c5 = ((self.datahigh[self.p.delay]-self.datalow[self.p.delay]) < self.p.candleper * self.dataclose[self.p.delay]) # hi-low < 0.5% of close
c6 = self.dataclose[self.p.delay] > self.sma3[self.p.delay]
c7 = self.dataclose[self.p.delay] > self.sma4[self.p.delay]
#c8 = self.dataclose[0] > self.vwap[0]
c9 = (self.dataclose[self.p.delay]-self.dataopen[self.p.delay]) > self.p.bodyper * (self.datahigh[self.p.delay] - self.datalow[self.p.delay])
testcandle = 3110
if(len(self) == testcandle):
self.log("Entering candle no " + str(testcandle))
if (c1 & c2 & c3 & c4 & c5 & c9):
##diff = self.dataclose[0] - self.dataclose[lastred]
rr = self.p.rr
if(c6):
rr += self.p.rrp
if( c7 ):
rr += self.p.rrp
# if( c8 ):
# rr+=1
#rr =2
cash = self.stats.broker.cash[self.p.delay]
maxRisk = cash * 0.01
diff = abs(2*(self.datahigh[self.p.delay]-self.datalow[self.p.delay]))
self.sl = self.dataclose[self.p.delay] - diff
self.reward = rr*diff+self.dataclose[self.p.delay]
self.bsize = int(min(maxRisk/diff , cash/self.dataclose[self.p.delay]))
# BUY, BUY, BUY!!! (with all possible default parameters)
bprice = self.data.close[self.p.delay] * (1+self.p.pricelimitper)
self.log(" Buy Signal at candle_pos = "+str(len(self))+ " Buy limit at "+ str(bprice))
# Keep track of the created order to avoid a 2nd order
#self.order = self.buy(size=self.bsize)
self.order = self.buy(exectype=bt.Order.Stop,
size=self.bsize,price=bprice,
valid=datetime.datetime.now() + datetime.timedelta(minutes=30)
)
self.log('BUY CREATE, %.2f' % self.dataclose[self.p.delay])
else:
# Already in a position? check exit criteria
# Long Eixt criteria
e1 = (self.dataclose[0] < self.sl) # SL reached
e2 = (self.dataclose[0] > self.reward) # Reward reached
e3 = (self.dataopen[0] > self.reward) # Reward reached
if (e1 | e2 | e3):
# SELL, SELL, SELL!!! (with all possible default parameters)
self.log('SELL CREATE... closed position, %.2f ' % self.dataclose[0])
# Keep track of the created order to avoid a 2nd order
self.order = self.sell(size=self.bsize)
#printf(f) Close all positions EOD
if self.position.size != 0:
if self.data.datetime.time() > datetime.time(15,10):
self.close(exectype=bt.Order.Market,size=self.position.size)