Thank you very much! I got it fixed, I just changed:
the logging function from
def log(self, txt, dt=None):
''' Logging function for this strategy'''
dt = dt or self.datas[0].datetime.date(0)
print('%s, %s' % (dt.isoformat(), txt))
to
def log(self, txt, dt=None):
''' Logging function for this strategy'''
dt = dt or self.datas[0].datetime.datetime(0)
print('%s, %s' % (dt.isoformat(), txt))
Hi there,
I'm still trying to convert unix timestamp to date, but I just can't get it to work.
From
https://www.backtrader.com/docu/datafeed/#genericcsvdata
So I tried it on my code:
here's a sample of my csv:
Open Time ,Open ,High ,Low ,Close ,Volume ,Close Time ,QuoteAssetVol ,Not ,Takerbuybv , takerbuyqv ,
1577836800.0,7195.24000000,7196.25000000,7178.64000000,7179.78000000,95.50913300,1577837099999,686317.13625177,1127,32.77324500,235537.29504531,0
and here's the output:
Ah i just need to remove
if args.fractional:
cerebro.broker.addcommissioninfo(CommInfoFractional())
@rajanprabu ohh i didnt know it will affect the data,thanks!
Spent an hour to find whats wrong, and 5 minutes after making this post I found out the red doji is coded wrongly :p
Spent an hour to find whats wrong, and 5 minutes after making this post I found out the red doji is coded wrongly :p
Oh sorry I mean if the market is
Hello,
I am testing a reversal strategy. The strategy is simply if market is at an downtrend (fast ma< mid ma < slow ma), then it will check if theres a green or red doji then it will SHORT and the other way around too.
But I am not sure why the code is buying non-dojis. From what I observed, it seems that it doesn't matter if there is a doji or not, but the code will keep buying if theres is no ongoing trade and (fast ma< mid ma < slow ma) or the other way around.
Here's a pic of a doji if you dont know what it is:
How I define a doji is the total length of the wick should be at least 20x longer than the body. Here's the green doji code:
def greendoji(open0, high0, low0, close0):
if close0 > open0:
if close0-open0 <= ((high0-close0) + (open0-low0)) / 20:
return True
else:
return False
Full Code below:
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import backtrader as bt
import datetime
import math
def greendoji(open0, high0, low0, close0):
if close0 > open0: #Close higher than Open, Resulting in a GREEN BAR
if close0-open0 <= ((high0-close0) + (open0-low0)) / 20: #Body < (Top Wick + Bot Wick) / 20
return True
else:
return False
def reddoji(open0, high0, low0, close0):
if close0 < open0: #Close lower than Open, Resulting in a RED BAR
if close0-open0 <= ((high0-open0) + (close0-low0)) / 20: #Body < (Top Wick + Bot Wick) / 20
return True
else:
return False
def longsizing(cash,entryprice,stoploss):
rpt = 0.01 # 0.01 = 1% risk per trade
rptic = (cash - 490000) * rpt # RPT in CASH. -490,000 from cash to bcs of the margin simulation
slgap = entryprice - stoploss * 1 / entryprice # GAP From High
entryic = rptic / slgap # Entry in Cash = $100 / SLGap
qty = math.floor(entryic / entryprice)
return qty #Returns number of Shares/Contracts to buy/sell
def shortsizing(cash,entryprice,stoploss):
rpt = 0.01 # 0.01 = 1% risk per trade
rptic = (cash - 490000) * rpt # RPT in CASH. -490,000 from cash to bcs of the margin simulation
slgap = stoploss - entryprice * 1 / entryprice # GAP From High
entryic = rptic / slgap # Entry in Cash = $100 / SLGap
qty = math.floor(entryic / entryprice)
return qty #Returns number of Shares/Contracts to buy/sell
class FxPattern(bt.Strategy):
# list of parameters which are configurable for the strategy
stoploss = 0
takeprofit = 0
tradeinicash = 10000
islong = False
skip = False
params = dict(
pfaster =20,
pfast =50, # period for the fast moving average
pslow =200 # period for the slow moving average
)
def __init__(self):
# To keep track of pending orders and buy price/commission
self.order = None
self.buyprice = None
self.buycomm = None
self.dataopen = self.datas[0].open
self.dataclose = self.datas[0].close
self.datahigh = self.datas[0].high
self.datalow = self.datas[0].low
self.datapreviouslow = self.datas[0].low(-1)
self.dataprevioushigh = self.datas[0].high(-1)
self.datapreviousclose = self.datas[0].close(-1)
#MA Function
self.sma0 = bt.ind.EMA(period=self.p.pfaster)# faster moving average
self.sma1 = bt.ind.EMA(period=self.p.pfast) # fast moving average
self.sma2 = bt.ind.EMA(period=self.p.pslow) # slow moving average
#self.crossover = bt.ind.CrossOver(self.sma1, self.sma2) # crossover signal
# LOGGING FUNCTION
def log(self, txt, dt=None):
''' Logging function for this strategy'''
dt = dt or self.datas[0].datetime.date(0)
print('%s, %s' % (dt.isoformat(), txt))
def next(self):
if self.skip:
self.skip = False
return
cash = self.broker.get_cash()
# ATR FUNCTION
range_total = 0
for i in range(-13, 1):
x = self.datahigh[i] - self.datalow[i]
y = self.datahigh[i] - self.datapreviousclose[i]
z = self.datalow[i] - self.datapreviousclose[i]
if x > y:
temp_truerange = x
else:
temp_truerange = y
if temp_truerange > z:
true_range = temp_truerange
else:
true_range = z
range_total += true_range
self.atr = range_total / 14
# Instants
close = self.dataclose[0]
cash = cerebro.broker.getcash()
atr = self.atr
self.log('C: %.5f' % (self.dataclose[0]))
# ORDER CHECK (If order is in place, can't place another until filled)
if self.order:
return
# LONG ENTRY
if not self.position:
if self.sma0 < self.sma1 < self.sma2: #downtrend
if greendoji(self.dataopen[0],self.datahigh[0],self.datalow[0],self.dataclose[0]) \
or reddoji(self.dataopen[0],self.datahigh[0],self.datalow[0],self.dataclose[0]):
qty = longsizing(self.broker.get_cash(), self.dataclose[0], self.atr) #Long Entry Sizing
self.stoploss = self.datalow[0] - (self.atr * 1) #NOTE:MULTIPLIER MUST SYNC WITH THE SIZING
self.takeprofit = self.dataclose[0] + ((self.dataclose[0] - self.stoploss)*1.5) #1.5x Reward to risk
self.order = self.buy_bracket(size=qty, price=self.dataclose[0],
limitprice=self.takeprofit,
stopprice=self.stoploss)
self.log('[ LONG ENTRY ] P: %.3f, Qty: %.1f, B: %.3f, ATR: %.3f, TP: %.5f, SL: %.5f' % (close, qty, cash, atr, self.takeprofit, self.stoploss))
#SHORT ENTRY
elif self.sma0 > self.sma1 > self.sma2: #Uptrend
if greendoji(self.dataopen[0],self.datahigh[0],self.datalow[0],self.dataclose[0]) \
or reddoji(self.dataopen[0],self.datahigh[0],self.datalow[0],self.dataclose[0]):
qty = shortsizing(self.broker.get_cash(), self.dataclose[0], self.atr) #SHORT Entry Sizing
self.stoploss = self.datahigh[0] + (self.atr * 1) #NOTE:MULTIPLIER MUST SYNC WITH THE SIZING
self.takeprofit = self.dataclose[0] - ((self.stoploss - self.dataclose[0])*1.5) #1.5x Reward to risk
self.order = self.sell_bracket(size=qty, price=self.dataclose[0],
limitprice=self.takeprofit,
stopprice=self.stoploss)
self.log('[ LONG ENTRY ] P: %.3f, Qty: %.1f, B: %.3f, ATR: %.3f, TP: %.5f, SL: %.5f' % (close, qty, cash, atr, self.takeprofit, self.stoploss))
# EXECUTED ORDER NOTIFICATIONS
def notify_order(self, order):
if order.status in [order.Submitted, order.Accepted]:
return
# Check if an order has been completed. Broker could reject if not enough cash
price = (order.executed.price)
qty = (order.executed.size)
balance = (cerebro.broker.getcash())
cost = (order.executed.value)
comm = (order.executed.comm)
atr = (self.atr)
if order.status in [order.Completed]:
# LONG BUY EXECUTED
if order.isbuy():
self.log(
"[ BUY EXECUTED ] P: %.3f, Qty: %.1f, B: %.3f, Cost: %.5f, Comm %.5f, ATR: %.5f" %
(price, qty, balance, cost, comm, atr))
# LONG SELL EXECUTED
elif order.issell():
self.log(
"[ SELL EXECUTED ] P: %.3f, Qty: %.1f, B: %.3f, Cost: %.5f, Comm %.5f" %
(price, (qty * -1), balance, cost, comm))
self.bar_executed = len(self)
elif order.status in [order.Canceled, order.Margin, order.Rejected]:
self.log("Order Canceled/Margin/Rejected")
self.order = None
# CLOSED OPERATION LOG
def notify_trade(self, trade):
if not trade.isclosed:
return
cp = (cerebro.broker.getcash() / 10000) * 100 # cumulative profit
profitpercent = (cerebro.broker.getcash() / self.tradeinicash) - 1 #
self.log("[ OPERATION PROFIT ] GROSS: %.2f, NET: %.2f, B: %.2f" %
(trade.pnl, trade.pnlcomm, cerebro.broker.getcash()))
self.log("[ In Percentage ] G/L: %.2f Percent, Cumulative: %.2f Percent" %
(profitpercent, cp))
self.cprof = cp
#self.skip = True
print()
def printTradeAnalysis(analyzer):
'''
Function to print the Technical Analysis results in a nice format.
'''
#Get the results we are interested in
total_open = analyzer.total.open
total_closed = analyzer.total.closed
total_won = analyzer.won.total
total_lost = analyzer.lost.total
win_streak = analyzer.streak.won.longest
lose_streak = analyzer.streak.lost.longest
pnl_net = round(analyzer.pnl.net.total,2)
strike_rate = round((total_won / total_closed) * 100,2)
#Designate the rows
h1 = ['Total Open', 'Total Closed', 'Total Won', 'Total Lost']
h2 = ['Strike Rate','Win Streak', 'Losing Streak', 'PnL Net']
r1 = [total_open, total_closed,total_won,total_lost]
r2 = [strike_rate, win_streak, lose_streak, pnl_net]
#Check which set of headers is the longest.
if len(h1) > len(h2):
header_length = len(h1)
else:
header_length = len(h2)
#Print the rows
print_list = [h1,r1,h2,r2]
row_format ="{:<15}" * (header_length + 1)
print("Trade Analysis Results:")
for row in print_list:
print(row_format.format('',*row))
def printSQN(analyzer):
sqn = round(analyzer.sqn,2)
print('SQN: {}'.format(sqn))
cerebro = bt.Cerebro() # create a "Cerebro" engine instance
data = bt.feeds.GenericCSVData(
dataname="data/Forex/EURGBP_D1.csv",
nullvalue=0.0,
dtformat=('%Y-%m-%d %H:%M'),
timeframe=bt.TimeFrame.Days,
compression=1,
fromdate=datetime.datetime(2007, 1, 1, 00, 00, 00),
todate=datetime.datetime(2018, 12, 29, 23, 59, 00),
open=1,
high=2,
low=3,
close=4,
openinterest=-1
)
cerebro.adddata(data) # Add the data feed
cerebro.broker.set_cash(500000)
cerebro.broker.setcommission(commission=0.000)
cerebro.addstrategy(FxPattern) # Add the trading strategy
cerebro.addanalyzer(bt.analyzers.TradeAnalyzer, _name="ta")
cerebro.addanalyzer(bt.analyzers.SQN, _name="sqn")
print("Starting Portfolio Value :%.5f" % (cerebro.broker.getvalue()-490000))
strategies = cerebro.run() # run it all
firstStrat = strategies[0]
print("Final Portfolio Value:%.5f" % (cerebro.broker.getvalue()-490000))
print("Final Portfolio Cash :%.5f" % (cerebro.broker.getcash()-490000))
printTradeAnalysis(firstStrat.analyzers.ta.get_analysis())
printSQN(firstStrat.analyzers.sqn.get_analysis())
cerebro.plot(style="candlestick", barup='green', bardown='red')
Hi there,
The full code below works perfectly as it is but I wonder why removing the
else:
if self.rsi > 70:
self.sell(size=100)
from the next function will cause an error?
This is the error i get
This is the full code:
import backtrader as bt
from datetime import datetime
from collections import OrderedDict
class firstStrategy(bt.Strategy):
def __init__(self):
self.rsi = bt.indicators.RSI_SMA(self.data.close, period=21)
def next(self):
if not self.position:
if self.rsi < 30:
self.buy(size=100)
else:
if self.rsi > 70:
self.sell(size=100)
def printTradeAnalysis(analyzer):
'''
Function to print the Technical Analysis results in a nice format.
'''
#Get the results we are interested in
total_open = analyzer.total.open
total_closed = analyzer.total.closed
total_won = analyzer.won.total
total_lost = analyzer.lost.total
win_streak = analyzer.streak.won.longest
lose_streak = analyzer.streak.lost.longest
pnl_net = round(analyzer.pnl.net.total,2)
strike_rate = (total_won / total_closed) * 100
#Designate the rows
h1 = ['Total Open', 'Total Closed', 'Total Won', 'Total Lost']
h2 = ['Strike Rate','Win Streak', 'Losing Streak', 'PnL Net']
r1 = [total_open, total_closed,total_won,total_lost]
r2 = [strike_rate, win_streak, lose_streak, pnl_net]
#Check which set of headers is the longest.
if len(h1) > len(h2):
header_length = len(h1)
else:
header_length = len(h2)
#Print the rows
print_list = [h1,r1,h2,r2]
row_format ="{:<15}" * (header_length + 1)
print("Trade Analysis Results:")
for row in print_list:
print(row_format.format('',*row))
def printSQN(analyzer):
sqn = round(analyzer.sqn,2)
print('SQN: {}'.format(sqn))
#Variable for our starting cash
startcash = 100000
#Create an instance of cerebro
cerebro = bt.Cerebro()
#Add our strategy
cerebro.addstrategy(firstStrategy)
#Get Apple data from Yahoo Finance.
data = bt.feeds.YahooFinanceData(
dataname='AAPL',
fromdate = datetime(2009,1,1),
todate = datetime(2017,1,1),
buffered= True
)
#Add the data to Cerebro
cerebro.adddata(data)
# Set our desired cash start
cerebro.broker.setcash(startcash)
# Add the analyzers we are interested in
cerebro.addanalyzer(bt.analyzers.TradeAnalyzer, _name="ta")
cerebro.addanalyzer(bt.analyzers.SQN, _name="sqn")
# Run over everything
strategies = cerebro.run()
firstStrat = strategies[0]
# print the analyzers
printTradeAnalysis(firstStrat.analyzers.ta.get_analysis())
printSQN(firstStrat.analyzers.sqn.get_analysis())
#Get final portfolio Value
portvalue = cerebro.broker.getvalue()
#Print out the final result
print('Final Portfolio Value: ${}'.format(portvalue))
#Finally plot the end results
cerebro.plot(style='candlestick')
Hii,
I am trying to use bracket orders in my strategy and I can't grasp it enough to implement it.
Can anyone explain to me what is the strategy of the sample code?
What is this switching function in the sample code?
if self.p.switchp1p2:
p1, p2 = p2, p1
valid1, valid2 = valid2, valid1
mainside = self.buy(price=13.50, exectype=bt.Order.Limit, transmit=False)
https://www.backtrader.com/docu/order-creation-execution/bracket/bracket/#sample-code
@rajanprabu ohh i didnt know it will affect the data,thanks!
hey,
Idk what happened but the datafeed should start from 01-01-2007, but it started from 08-03-2007.
Can anyone point out the problem here?
Here's the log:
from datetime import datetime
import backtrader as bt
# Create a subclass of Strategy to define the indicators and logic
class SmaCross(bt.Strategy):
# list of parameters which are configurable for the strategy
stoploss = 0
takeprofit = 0
params = dict(
pfast=50, # period for the fast moving average
pslow=300 # period for the slow moving average
)
def __init__(self):
# To keep track of pending orders and buy price/commission
self.order = None
self.buyprice = None
self.buycomm = None
self.dataclose = self.datas[0].close
self.datahigh = self.datas[0].high
self.datalow = self.datas[0].low
self.datapreviousclose = self.datas[0].close(-1)
#MA Function
self.sma1 = bt.ind.SMA(period=self.p.pfast) # fast moving average
self.sma2 = bt.ind.SMA(period=self.p.pslow) # slow moving average
self.crossover = bt.ind.CrossOver(self.sma1, self.sma2) # crossover signal
# LOGGING FUNCTION
def log(self, txt, dt=None):
''' Logging function for this strategy'''
dt = dt or self.datas[0].datetime.date(0)
print('%s, %s' % (dt.isoformat(), txt))
def next(self):
# ATR FUNCTION
range_total = 0
for i in range(-13, 1):
x = self.datahigh[i] - self.datalow[i]
y = self.datahigh[i] - self.datapreviousclose[i]
z = self.datalow[i] - self.datapreviousclose[i]
if x > y:
temp_truerange = x
else:
temp_truerange = y
if temp_truerange > z:
true_range = temp_truerange
else:
true_range = z
range_total += true_range
self.atr = range_total / 14
# ATR Multiplier
self.atr = self.atr * 1
self.log('C: %.8f' % (self.dataclose[0]))
# ORDER CHECK (If order is in place, can't place another until filled)
if self.order:
return
if not self.position:
if self.sma1[0] > self.sma2[0]:
if self.datapreviousclose[0] < self.sma1[0]:
if self.dataclose[0] > self.sma1[0]:
self.buy() # enter long
av = self.sma1[0]
print(av)
print(self.dataclose[0])
self.stoploss = self.datalow[0] - self.atr
self.takeprofit = (self.atr*3) + self.datalow[0]
elif self.dataclose[0] < self.stoploss: # in the market & cross to the downside
self.close()
elif self.dataclose[0] >= self.takeprofit:
self.close()
cerebro = bt.Cerebro() # create a "Cerebro" engine instance
# Create a data feed
data = bt.feeds.YahooFinanceCSVData(
dataname="data/Forex/AUDJPY_H4.csv",
dtformat=2,
fromdate=datetime(2007,1,1),
todate=datetime(2007,12,29),
reverse=False,
adjclose=False)
cerebro.adddata(data) # Add the data feed
cerebro.addstrategy(SmaCross) # Add the trading strategy
cerebro.run() # run it all
cerebro.plot(style="candlestick", barup='green', bardown='red')
I revised the code a bit:
class TestStrategy(bt.Strategy):
'''
Inside this "TestStrategy", there will be some "uncommon" scripts:
- ATR Function: Self-made ATR, because I needed it for sizing.
- Trade Period: To count the amound of bars passed after the start of an on going trade
- Trade Count: To count trades for pyramiding function since the first trade.
'''
stoploss = 0
params = dict(
pfast=50,
pslow=300,
)
def __init__(self):
# Keep a reference to the "close" line in the data[0] dataseries
self.dataclose = self.datas[0].close
# To keep track of pending orders and buy price/commission
self.order = None
self.buyprice = None
self.buycomm = None
# SMA use
self.sma1 = bt.ind.SMA(period=self.p.pfast) # fast moving average
self.sma2 = bt.ind.SMA(period=self.p.pslow) # slow moving average
self.crossover = bt.ind.CrossOver(self.sma1, self.sma2) # crossover signal
# ATR use
self.dataclose = self.datas[0].close
self.datahigh = self.datas[0].high
self.datalow = self.datas[0].low
self.datapreviousclose = self.datas[0].close(-1)
self.atr = 0
# self.my_atr = bt.ind.ATR(period = 14,)
# LOGGING FUNCTION
def log(self, txt, dt=None):
''' Logging function for this strategy'''
dt = dt or self.datas[0].datetime.date(0)
print('%s, %s' % (dt.isoformat(), txt))
def next(self):
cash = self.broker.get_cash()
#MA Function
self.sma1 = bt.ind.SMA(period=self.p.pfast) # fast moving average
self.sma2 = bt.ind.SMA(period=self.p.pslow) # slow moving average
self.crossover = bt.ind.CrossOver(self.sma1, self.sma2) # crossover signal
# ATR FUNCTION
range_total = 0
for i in range(-13, 1):
x = self.datahigh[i] - self.datalow[i]
y = self.datahigh[i] - self.datapreviousclose[i]
z = self.datalow[i] - self.datapreviousclose[i]
if x > y:
temp_truerange = x
else:
temp_truerange = y
if temp_truerange > z:
true_range = temp_truerange
else:
true_range = z
range_total += true_range
self.atr = range_total / 14
#ATR Multiplier
self.atr = self.atr * 1
#Instants
close = (self.dataclose[0])
cash = (cerebro.broker.getcash())
atr = (self.atr)
self.log('C: %.8f, ATR:%.8f' % (self.dataclose[0], atr))
# ORDER CHECK (If order is in place, can't place another until filled)
if self.order:
return
# LONG BUY CREATE CONDITION:
if not self.position :
if self.datas[0].close(-1) <= self.sma1[0]:
if self.dataclose() > self.sma1[0]:
self.order = self.buy(size=1)
print()
self.log(
'[ LONG BUY CREATE ] P: %.8f, Qty: %.10f, B: %.8f, ATR: %.8f' % (close, 1, cash, atr))
self.stoploss =self.datalow() - self.atr
# LONG SELL CREATE CONDITION
elif self.dataclose() < self.stoploss:# or self.crossover < 0: # in the market & cross to the downside
self.close()
self.log("[ LONG SELL CREATE ] P: %.8f" % close)