Below is the original code pasted from the site exactly as it is. Getting error:
C:\Users\Sam\Anaconda64Best\python.exe "C:/Users/Sam/PycharmProjects/Test/.ipynb_checkpoints/Backtrader Target Value Example.py"
usage: Backtrader Target Value Example.py [-h] [--data DATA]
[--fromdate FROMDATE]
[--todate TODATE] [--cash CASH]
(--target-size | --target-value | --target-percent)
[--plot [kwargs]]
Backtrader Target Value Example.py: error: one of the arguments --target-size --target-value --target-percent is required
I have tried to set either size, target value, or target percent to 'True' to from its current default 'False' to try to resolve in the block of code:
params = ( # define target size, value, or percent as order type
('use_target_size', False),
('use_target_value', False),
('use_target_percent', False),
)
However, error still comes up. Is there somewhere else in the code that needs to be set to 'True' instead that I am not seeing and changing? Thanks for the help in advance. Full code is below from the website:
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import argparse
import datetime # For datetime objects
from datetime import datetime
import backtrader as bt
import backtrader.feeds as btfeeds
class TheStrategy(bt.Strategy):
'''
This strategy is loosely based on some of the examples from the Van
K. Tharp book: *Trade Your Way To Financial Freedom*. The logic:
- Enter the market if:
- The MACD.macd line crosses the MACD.signal line to the upside
- The Simple Moving Average has a negative direction in the last x
periods (actual value below value x periods ago)
- Set a stop price x times the ATR value away from the close
- If in the market:
- Check if the current close has gone below the stop price. If yes,
exit.
- If not, update the stop price if the new stop price would be higher
than the current
# The logic in the sample is rather dumb and only meant for testing:
During odd months (Jan, Mar, ...), use the day as TARGET (in the case of order_target_value multiplying the day by 1000)
This mimics an increasing target
During even months (Feb, Apr, ...) use 31 - day as the TARGET
This mimics an decreasing target
'''
params = ( # define target size, value, or percent as order type
('use_target_size', False),
('use_target_value', False),
('use_target_percent', False),
)
def notify_order(self, order):
if order.status == order.Completed:
pass
if not order.alive():
self.order = None # indicate no order is pending
def start(self):
self.order = None # sentinel to avoid operations on pending order
def next(self):
dt = self.data.datetime.date()
portfolio_value = self.broker.get_value()
print('%04d - %s - Position Size: %02d - Value %.2f' %
(len(self), dt.isoformat(), self.position.size, portfolio_value))
data_value = self.broker.get_value([self.data]) # portfolio value for that specific stock
if self.p.use_target_value: # if we use target value as order execution
print('%04d - %s - data value %.2f' %
(len(self), dt.isoformat(), data_value))
elif self.p.use_target_percent: # if we use target percentage as order execution
port_perc = data_value / portfolio_value
print('%04d - %s - data percent %.2f' %
(len(self), dt.isoformat(), port_perc))
if self.order: # if order is placed
return # pending order execution
size = dt.day # size of order is based on the day (odd or even months)
if (dt.month % 2) == 0:
size = 31 - size # if it is an even month, use 31 - day as the target (for odd months, use the day as the target)
# determine if we base our order on either: target size, target value, or target percentage
if self.p.use_target_size: # if we use target size as the order execution
target = size # target is the size of the trade (number of shares)
print('%04d - %s - Order Target Size: %02d' %
(len(self), dt.isoformat(), size)) # based on size
self.order = self.order_target_size(target=size) # place order based on order target size (number of shares)
elif self.p.use_target_value: # if we use target value, target value = size (number of shares * 1000) as we are multiplying the day by 1000
value = size * 1000
print('%04d - %s - Order Target Value: %.2f' %
(len(self), dt.isoformat(), value)) # based on value
self.order = self.order_target_value(target=value)
elif self.p.use_target_percent: # if we use target percentage of portfolio to place orders (number of shares (size) divided by 100 to see what % of the portfolio it is)
percent = size / 100.0
print('%04d - %s - Order Target Percent: %.2f' %
(len(self), dt.isoformat(), percent)) # based on percentage
self.order = self.order_target_percent(target=percent)
def runstrat(args=None):
args = parse_args(args)
cerebro = bt.Cerebro()
cerebro.broker.setcash(args.cash) # set brokerage cash value
dkwargs = dict()
if args.fromdate is not None:
dkwargs['fromdate'] = datetime.strptime(args.fromdate, "%m/%d/%Y")
if args.todate is not None:
dkwargs['todate'] = datetime.strptime(args.todate, "%m/%d/%Y")
# data
data = btfeeds.GenericCSVData(
dataname='C:\\Users\\Sam\\PycharmProjects\\Test\\.ipynb_checkpoints\\orcl-1995-2014.csv',
fromdate=datetime.datetime.strptime("1/1/2000", "%m/%d/%Y"),
todate=datetime.datetime.strptime("12/31/2000", "%m/%d/%Y"),
nullvalue=0.0, # missing values to be replaced with 0
dtformat=('%m/%d/%Y'),
datetime=0,
time=-1,
open=1,
high=2,
low=3,
close=4,
adjclose=5,
volume=6,
openinterest=-1,
)
cerebro.adddata(data)
# strategy
cerebro.addstrategy(TheStrategy,
use_target_size=args.target_size,
use_target_value=args.target_value,
use_target_percent=args.target_percent)
cerebro.run()
if args.plot: # plot strategy
pkwargs = dict(style='bar')
if args.plot is not True: # evals to True but is not True
npkwargs = eval('dict(' + args.plot + ')') # args were passed
pkwargs.update(npkwargs)
cerebro.plot(**pkwargs)
def parse_args(pargs=None):
parser = argparse.ArgumentParser(
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
description='Sample for Order Target')
parser.add_argument('--data', required=False,
default='C:\\Users\\Sam\\PycharmProjects\\Test\\.ipynb_checkpoints\\orcl-1995-2014.csv', # set file path
help='Specific data to be read in')
parser.add_argument('--fromdate', required=False,
default='2005-01-01',
help='Starting date in MM/DD/YYYY format') # set file format
parser.add_argument('--todate', required=False,
default='2006-12-31',
help='Ending date in MM/DD/YYYY format') # set file format
parser.add_argument('--cash', required=False, action='store', # ending cash at end of date
type=float, default=1000000,
help='Ending date in MM/DD/YYYY format') # set file format
pgroup = parser.add_mutually_exclusive_group(required=True)
pgroup.add_argument('--target-size', required=False, action='store_true', # use target size
help=('Use order_target_size'))
pgroup.add_argument('--target-value', required=False, action='store_true', # use target value
help=('Use order_target_value'))
pgroup.add_argument('--target-percent', required=False, # use target percentage
action='store_true',
help=('Use order_target_percent'))
# Plot options
parser.add_argument('--plot', '-p', nargs='?', required=False,
metavar='kwargs', const=True,
help=('Plot the read data applying any kwargs passed\n'
'\n'
'For example:\n'
'\n'
' --plot style="candle" (to plot candles)\n'))
if pargs is not None:
return parser.parse_args(pargs)
return parser.parse_args()
if __name__ == '__main__':
runstrat()
