Great! Now the chart is working. Here's what it looks like with your simple tweak:
self.signal_add(bt.SIGNAL_LONGEXIT, -1.0*self.sellsignal)
And I'd like to add that the community behind this software is fantastic!
My next step will be to figure out the date time. I believe I need to create a new Signal class with an if statement to check the date, correct? Since I won't be using a CrossUp, I'll simply compare the date and data0-pp1.p
OK, baby steps. I got the CrossUp and CrossDown signals generated but it doesn't do LONGEXIT
See image: 
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import argparse
import backtrader as bt
import backtrader.feeds as btfeeds
import backtrader.utils.flushfile
class St(bt.SignalStrategy):
params = (('usepp1', False),
('plot_on_daily', False))
def __init__(self):
autoplot = self.p.plot_on_daily
self.pp = pp = bt.ind.PivotPoint(self.data1, _autoplot=autoplot)
## Here is here I am trying to buy when the daily close is less than the
## pivot on the Xth day and sell whenever it crosses r1
pp1 = self.pp() # couple the entire indicators
self.buysignal = bt.ind.CrossUp(self.data0.close, pp1)
self.sellsignal = bt.ind.CrossDown(self.data0.close, pp1.r1)
self.signal_add(bt.SIGNAL_LONG, self.buysignal)
self.signal_add(bt.SIGNAL_LONGEXIT, self.sellsignal)
def next(self):
txt = ','.join(
['%04d' % len(self),
'%04d' % len(self.data0),
'%04d' % len(self.data1),
self.data.datetime.date(0).isoformat(),
'%04d' % len(self.pp),
'%.2f' % self.pp[0]])
print(txt)
def runstrat():
args = parse_args()
cerebro = bt.Cerebro()
data = btfeeds.BacktraderCSVData(dataname=args.data)
cerebro.adddata(data)
cerebro.resampledata(data, timeframe=bt.TimeFrame.Months)
cerebro.broker.setcash(100000.0)
#cerebro.signal_accumulate(True)
cerebro.addstrategy(St,
plot_on_daily=args.plot_on_daily)
cerebro.run(runonce=False)
if args.plot:
cerebro.plot(style='bar')
def parse_args():
parser = argparse.ArgumentParser(
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
description='Sample for pivot point and cross plotting')
parser.add_argument('--data', required=False,
default='../../datas/2005-2006-day-001.txt',
help='Data to be read in')
parser.add_argument('--plot', required=False, action='store_true',
help=('Plot the result'))
parser.add_argument('--plot-on-daily', required=False, action='store_true',
help=('Plot the indicator on the daily data'))
return parser.parse_args()
if __name__ == '__main__':
runstrat()
@backtrader Let me give it a shot!
Also, side question, how are dataX automagically created? I don't see them defined anywhere -- I assume this is in the indicator?
@backtrader said in Executing Buy Sell Strategy for PivotPoint:
I ideally want to buy once a month when it crosses the pivot after a certain day
The previous statement raises, at least, the following questions, which may help you into coding your strategy:
- Which pivot?
The first pivot, and R1
- Crossing to the upside? To the downside?
Crossing to the upside
- Which certain day?
The 15th of the month
@SShepherd said in Executing Buy Sell Strategy for PivotPoint:
@backtrader Thanks for response, I uploaded the entire file and dataset
Here is the full code: http://dpaste.com/0FYC29P
Here is the dataset: http://dpaste.com/37EGH80 [same as 2005-2006-day-001.txt]
I ideally want to buy once a month when it crosses the pivot after a certain day, but not sure how to do that
I'm copying the code into this forum for archival purposes:
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import argparse
import backtrader as bt
import backtrader.feeds as btfeeds
import backtrader.utils.flushfile
class St(bt.SignalStrategy):
params = (('usepp1', False),
('plot_on_daily', False))
def __init__(self):
autoplot = self.p.plot_on_daily
self.pp = pp = bt.ind.PivotPoint(self.data1, _autoplot=autoplot)
## Here is here I am trying to buy when the daily close is less than the
## pivot on the Xth day and sell whenever it crosses r1
pp1 = self.pp() # couple the entire indicators
self.buysignal = self.data0.close < pp1.p
self.sellsignal = self.data0.close > pp1.r1
self.signal_add(bt.SIGNAL_LONG, self.buysignal)
self.signal_add(bt.SIGNAL_LONGEXIT, self.sellsignal)
def next(self):
txt = ','.join(
['%04d' % len(self),
'%04d' % len(self.data0),
'%04d' % len(self.data1),
self.data.datetime.date(0).isoformat(),
'%04d' % len(self.pp),
'%.2f' % self.pp[0]])
print(txt)
def runstrat():
args = parse_args()
cerebro = bt.Cerebro()
data = btfeeds.BacktraderCSVData(dataname=args.data)
cerebro.adddata(data)
cerebro.resampledata(data, timeframe=bt.TimeFrame.Months)
cerebro.addstrategy(St,
plot_on_daily=args.plot_on_daily)
cerebro.run(runonce=False)
if args.plot:
cerebro.plot(style='bar')
def parse_args():
parser = argparse.ArgumentParser(
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
description='Sample for pivot point and cross plotting')
parser.add_argument('--data', required=False,
default='../../datas/2005-2006-day-001.txt',
help='Data to be read in')
parser.add_argument('--plot', required=False, action='store_true',
help=('Plot the result'))
parser.add_argument('--plot-on-daily', required=False, action='store_true',
help=('Plot the indicator on the daily data'))
return parser.parse_args()
if __name__ == '__main__':
runstrat()
@backtrader Thanks for response, I uploaded the entire file and dataset
Here is the full code: http://dpaste.com/0FYC29P
Here is the dataset: http://dpaste.com/37EGH80 [same as 2005-2006-day-001.txt]
I ideally want to buy once a month when it crosses the pivot after a certain day, but not sure how to do that
Trying to execute a strategy for buying at the first P and selling at the R1:
class St(bt.SignalStrategy):
params = ()
def __init__(self):
self.pp = bt.ind.PivotPoint(self.data1)
pp1 = self.pp() # couple the entire indicators
self.buysignal = self.data0.close < pp1.p
self.sellsignal = self.data0.close > pp1.r1
self.signal_add(bt.SIGNAL_LONG, self.buysignal)
self.signal_add(bt.SIGNAL_LONGEXIT, self.sellsignal)
def runstrat():
args = parse_args()
cerebro = bt.Cerebro()
data = use_clf_data()
# Add commodity
commCL= bt.CommissionInfo(commission=2.0, margin=1000.0, mult=1000.0)
cerebro.broker.addcommissioninfo(commCL)
cerebro.broker.setcash(100000.0)
cerebro.signal_accumulate(True)
# Add the data
cerebro.adddata(data)
cerebro.resampledata(data, timeframe=bt.TimeFrame.Months)
cerebro.addstrategy(St)
cerebro.run(runonce=False)
if args.plot:
#cerebro.plot(style='bar')
cerebro.plot(style='line')
However, I get this: 
I'm expecting a lot more buy and sell events. What did I do wrong?
This can initiate the buy but only for the first datapoint:
self.pp = bt.ind.PivotPoint(self.data1)
pp1 = self.pp() # couple the entire indicators
self.buysignal = self.data0.close < pp1.r1
self.sellsignal = self.data0.close > pp1.p
self.signal_add(bt.SIGNAL_LONG, self.buysignal)
self.signal_add(bt.SIGNAL_LONGEXIT, self.sellsignal)
And here's my runstrat():
cerebro.signal_accumulate(True)
# Add the data
cerebro.adddata(data)
cerebro.resampledata(data, timeframe=bt.TimeFrame.Months)
cerebro.addstrategy(St)
How would I attach a Strategy to this to LONG when it crosses P and SHORT when it crosses R1?
This does not work:
class MySignal(bt.Indicator):
lines = ('signal',)
def __init__(self):
self.lines.signal = self.data - bt.indicators.PivotPoint(self.data)
I think, just set one up and see who joins. Then we'll use social darwinism to determine which chat room stays
With that said, I'm interested