Improving Commissions: Stocks vs Futures
Posting backtrader usage examples has given me an insight into things that were missing. For starters:
-
Multicore Optimization
-
Commissions: Stocks vs Futures
The latter showed me:
-
The broker was doing the right things with regards to the calculation of profit and loss and providing the right order notifications to the calling strategy
-
The strategy had no access to
operations
(akatrades
) which is the result of an order having opened and closed a position (with the latter showing a P&L figure) -
The plotted
Operation
P&L figures were gathered by anObserver
and had no access to the actualcommission scheme
, hence rendering the same P&L for afutures-like
operation and for astocks-like
one
Clearly a small internal rework was needed to achieve:
-
Operation
notification to the strategy -
Operations
displaying the right P&L figures
The broker
already had all of the needed information and already stuffing
most of it into the order
which was being notified to the strategy
which
had create it. The only decision to make was whether the broker
would fit an
extra information bit into the order or it could calculate the operations
itself.
Since the strategy already gets the orders
and keeping the operations
in
a list seems natural, the broker
just adds the actual P&L when an order has
closed partially/totally a position, leaving the responsibility of the
calculation to the strategy
.
In turn this simplifies the actual role of the Operations Observer
to that
of observing newly closed Operation
and recording it. The role it should
always have had.
The code below has been reworked to no longer calculate the P&L figures, but to
just pay attention to those notified in notify_operation
.
And the charts now reflect realistic P&L figures (The cash
and value
were alredy realistic)
The old logging for futures:
2006-03-09, BUY CREATE, 3757.59
2006-03-10, BUY EXECUTED, Price: 3754.13, Cost: 2000.00, Comm 2.00
2006-04-11, SELL CREATE, 3788.81
2006-04-12, SELL EXECUTED, Price: 3786.93, Cost: 2000.00, Comm 2.00
2006-04-12, OPERATION PROFIT, GROSS 328.00, NET 324.00
2006-04-20, BUY CREATE, 3860.00
2006-04-21, BUY EXECUTED, Price: 3863.57, Cost: 2000.00, Comm 2.00
2006-04-28, SELL CREATE, 3839.90
2006-05-02, SELL EXECUTED, Price: 3839.24, Cost: 2000.00, Comm 2.00
2006-05-02, OPERATION PROFIT, GROSS -243.30, NET -247.30
The new logging for futures:
2006-03-09, BUY CREATE, 3757.59
2006-03-10, BUY EXECUTED, Price: 3754.13, Cost: 2000.00, Comm 2.00
2006-04-11, SELL CREATE, 3788.81
2006-04-12, SELL EXECUTED, Price: 3786.93, Cost: 2000.00, Comm 2.00
2006-04-12, OPERATION PROFIT, GROSS 328.00, NET 324.00
2006-04-20, BUY CREATE, 3860.00
2006-04-21, BUY EXECUTED, Price: 3863.57, Cost: 2000.00, Comm 2.00
2006-04-28, SELL CREATE, 3839.90
2006-05-02, SELL EXECUTED, Price: 3839.24, Cost: 2000.00, Comm 2.00
2006-05-02, OPERATION PROFIT, GROSS -243.30, NET -247.30
2006-05-02, BUY CREATE, 3862.24
The old logging For stocks:
2006-03-09, BUY CREATE, 3757.59
2006-03-10, BUY EXECUTED, Price: 3754.13, Cost: 3754.13, Comm 18.77
2006-04-11, SELL CREATE, 3788.81
2006-04-12, SELL EXECUTED, Price: 3786.93, Cost: 3786.93, Comm 18.93
2006-04-12, OPERATION PROFIT, GROSS 32.80, NET -4.91
2006-04-20, BUY CREATE, 3860.00
2006-04-21, BUY EXECUTED, Price: 3863.57, Cost: 3863.57, Comm 19.32
2006-04-28, SELL CREATE, 3839.90
2006-05-02, SELL EXECUTED, Price: 3839.24, Cost: 3839.24, Comm 19.20
2006-05-02, OPERATION PROFIT, GROSS -24.33, NET -62.84
The new logging for stocks:
2006-03-09, BUY CREATE, 3757.59
2006-03-10, BUY EXECUTED, Price: 3754.13, Cost: 3754.13, Comm 18.77
2006-04-11, SELL CREATE, 3788.81
2006-04-12, SELL EXECUTED, Price: 3786.93, Cost: 3786.93, Comm 18.93
2006-04-12, OPERATION PROFIT, GROSS 32.80, NET -4.91
2006-04-20, BUY CREATE, 3860.00
2006-04-21, BUY EXECUTED, Price: 3863.57, Cost: 3863.57, Comm 19.32
2006-04-28, SELL CREATE, 3839.90
2006-05-02, SELL EXECUTED, Price: 3839.24, Cost: 3839.24, Comm 19.20
2006-05-02, OPERATION PROFIT, GROSS -24.33, NET -62.84
2006-05-02, BUY CREATE, 3862.24
And the charts (only the new ones). The difference between futures-like
operations and stock-like
operations can now be clearly seen and not only in
the evolution of cash
and value
.
Commissions for futures
Commissions for stocks
The code
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import backtrader as bt
import backtrader.feeds as btfeeds
import backtrader.indicators as btind
futures_like = True
if futures_like:
commission, margin, mult = 2.0, 2000.0, 10.0
else:
commission, margin, mult = 0.005, None, 1
class SMACrossOver(bt.Strategy):
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))
def notify(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 enougth cash
if order.status in [order.Completed, order.Canceled, order.Margin]:
if order.isbuy():
self.log(
'BUY EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
(order.executed.price,
order.executed.value,
order.executed.comm))
else: # Sell
self.log('SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
(order.executed.price,
order.executed.value,
order.executed.comm))
def notify_trade(self, trade):
if trade.isclosed:
self.log('TRADE PROFIT, GROSS %.2f, NET %.2f' %
(trade.pnl, trade.pnlcomm))
def __init__(self):
sma = btind.SMA(self.data)
# > 0 crossing up / < 0 crossing down
self.buysell_sig = btind.CrossOver(self.data, sma)
def next(self):
if self.buysell_sig > 0:
self.log('BUY CREATE, %.2f' % self.data.close[0])
self.buy() # keep order ref to avoid 2nd orders
elif self.position and self.buysell_sig < 0:
self.log('SELL CREATE, %.2f' % self.data.close[0])
self.sell()
if __name__ == '__main__':
# Create a cerebro entity
cerebro = bt.Cerebro()
# Add a strategy
cerebro.addstrategy(SMACrossOver)
# Create a Data Feed
datapath = ('../../datas/2006-day-001.txt')
data = bt.feeds.BacktraderCSVData(dataname=datapath)
# Add the Data Feed to Cerebro
cerebro.adddata(data)
# set commission scheme -- CHANGE HERE TO PLAY
cerebro.broker.setcommission(
commission=commission, margin=margin, mult=mult)
# Run over everything
cerebro.run()
# Plot the result
cerebro.plot()