oh_my_bot_app/test_backtrader.py

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.analyzers as btanalyzers

import math
import pandas as pd
import numpy as np

# 데이터 넣기
# 주 지표 적용
# 보조 지표 적용
# 지표 혼합 적용
# 경우의 수에 따른 시뮬레이팅

PARAMS = (
    ('maperiod', 15),  # moving average period
    ('period', 15),  #
    ('willperiod', 14),  # moving average period
    ('sizer', None),
)


class TestStrategy(bt.Strategy):
    params = PARAMS

    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 __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.order = self.order_target_percent(target=0.1)
        self.buyprice = None
        self.buycomm = None
        # self.sma = bt.indicators.SimpleMovingAverage(self.datas[0], period=self.params.maperiod)
        self.sma = bt.indicators.ExponentialMovingAverage(self.datas[0], period=25)


    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 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))

                self.buyprice = order.executed.price
                self.buycomm = order.executed.comm
            else:  # Sell
                self.log('SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
                         (order.executed.price,
                          order.executed.value,
                          order.executed.comm))

            self.bar_executed = len(self)

        # Write down: no pending order
        self.order = None

    def notify_trade(self, trade):
        if not trade.isclosed:
            return

        self.log('OPERATION PROFIT, GROSS %.2f, NET %.2f' %
                 (trade.pnl, trade.pnlcomm))

    def next(self):
        # Simply log the closing price of the series from the reference
        # 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 not self.position:
            # Not yet ... we MIGHT BUY if ...
            if self.dataclose[0] > self.sma[0]:
                # BUY, BUY, BUY!!! (with all possible default parameters)
                self.log('BUY CREATE, close : %.2f, sma25 : %.2f' % (self.dataclose[0], self.sma[0]))
                # Keep track of the created order to avoid a 2nd order
                self.order = self.buy()
        else:

            if self.dataclose[0] < self.sma[0]:
                # SELL, SELL, SELL!!! (with all possible default parameters)
                self.log('SELL CREATE, close : %.2f, sma25 : %.2f' % (self.dataclose[0], self.sma[0]))

                # Keep track of the created order to avoid a 2nd order
                self.order = self.sell()


class LongOnly(bt.Sizer):
    params = (('stake', 1),)

    def _getsizing(self, comminfo, cash, data, isbuy):
        if isbuy:
            divide = math.floor(cash / data.close[0])
            #			divide = math.floor(cash/data.open[1])
            self.p.stake = divide
            #			print(self.p.stake)
            #			print(math.floor(cash/data.close[0]))

            return self.p.stake
        # Sell situation
        position = self.broker.getposition(data)
        if not position.size:
            return 0  # do not sell if nothing is open
        return self.p.stake


if __name__ == '__main__':
    cerebro = bt.Cerebro()
    # Add a strategy
    cerebro.addstrategy(TestStrategy)
    # Add Sizer
    cerebro.addsizer(LongOnly)

    # because it could have been called from anywhere
    modpath = os.path.dirname(os.path.abspath(sys.argv[0]))
    datapath = os.path.join(modpath, 'orcl-2014.txt')

    # Create a Data Feed
    data = bt.feeds.YahooFinanceCSVData(
        dataname=datapath,
        # Do not pass values before this date
        # Do not pass values before this date
        # Do not pass values after this date
        reverse=False)

    # Add the Data Feed to Cerebro
    cerebro.adddata(data)

    # Set our desired cash start
    cerebro.broker.setcash(1000.0)

    #	In order to buy on open you may want to
    #	bt.filters.BarReplayer_Open(data)
    cerebro.broker.set_coc(True)

    # Set the commission
    cerebro.broker.setcommission(commission=0.005)

    # Print out the starting conditions
    print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())

    # Run over everything
    cerebro.run()

    # Print out the final result
    print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())

    # Plot the result
    cerebro.plot()