backtrader demo

[asmcos]

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


# Create a Stratey
class TestStrategy(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 __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
        self.order = None

    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 enough cash
        if order.status in [order.Completed]:
            if order.isbuy():
                self.log('BUY EXECUTED, %.2f' % order.executed.price)
            elif order.issell():
                self.log('SELL EXECUTED, %.2f' % order.executed.price)

            self.bar_executed = len(self)

        elif order.status in [order.Canceled, order.Margin, order.Rejected]:
            self.log('Order Canceled/Margin/Rejected')

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

    def next(self):
        # Simply log the closing price of the series from the reference
        self.log('Close, %.2f' % self.dataclose[0])

        # 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.dataclose[-1]:
                    # current close less than previous close

                    if self.dataclose[-1] < self.dataclose[-2]:
                        # previous close less than the previous close

                        # BUY, BUY, BUY!!! (with default parameters)
                        self.log('BUY CREATE, %.2f' % self.dataclose[0])

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

        else:

            # Already in the market ... we might sell
            if len(self) >= (self.bar_executed + 5):
                # SELL, SELL, SELL!!! (with all possible default parameters)
                self.log('SELL CREATE, %.2f' % self.dataclose[0])

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


if __name__ == '__main__':
    # Create a cerebro entity
    cerebro = bt.Cerebro()

    # Add a strategy
    cerebro.addstrategy(TestStrategy)

    # Datas are in a subfolder of the samples. Need to find where the script is
    # because it could have been called from anywhere
    modpath = os.path.dirname(os.path.abspath(sys.argv[0]))
    datapath = os.path.join(modpath, '../../datas/orcl-1995-2014.txt')

    # Create a Data Feed
    data = bt.feeds.YahooFinanceCSVData(
        dataname=datapath,
        # Do not pass values before this date
        fromdate=datetime.datetime(2000, 1, 1),
        # Do not pass values before this date
        todate=datetime.datetime(2000, 12, 31),
        # 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(100000[ NaN:0 ].0)

    # 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())

[asmcos]

from __future__ import (absolute_import, division, print_function,
                        unicode_literals)

from Klang import Kl,Klang

import backtrader as bt
import pandas as pd
import math

class LongOnly(bt.Sizer):
    params = (('stake', 1),)
    def _getsizing(self, comminfo, cash, data, isbuy):
        # buy 1/2
        cash = math.floor(cash * 95 / 100 )

        if isbuy:
            divide = math.floor(cash/data.close[0])
            self.p.stake = divide
            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


class PandasData(bt.feeds.PandasData):
    params = (
        ('datetime', None),
        ('open','open'),
        ('high','high'),
        ('low','low'),
        ('close','close'),
        ('volume','vol'),
        ('openinterest',None),
    )

# Create a Stratey
class KStrategy(bt.Strategy):

    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 __init__(self):
        # Keep a reference to the "close" line in the data[0] dataseries
        self.dataclose = self.datas[0].close
        self.order = None
        self.macdhist = bt.ind.MACDHisto(self.data)

    def notify_order(self, order):
        if order.status == order.Completed:
            pass

        if not order.alive():
            self.order = None  # indicate no order is pending

        if order.status in [order.Submitted, order.Accepted]:
            # Buy/Sell order submitted/accepted to/by broker - Nothing to do
            return

        if order.status in [order.Completed, order.Canceled, order.Margin]:
            if order.isbuy():
                self.log(
                    'BUY EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f,value %.2f' %
                    (order.executed.price,
                     order.executed.value,
                     order.executed.comm,self.broker.getvalue()))

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

        self.order = None
    def next(self):
        # Simply log the closing price of the series from the reference
        if not self.position:
            if self.macdhist > 0:
                self.order=self.buy()
        else:
            if self.macdhist < 0:
                self.order = self.sell()


def init_btr():
    cerebro = bt.Cerebro(stdstats=False)

    # Add a strategy
    cerebro.addstrategy(KStrategy)

    Kl.code("sh.600062[ 22.08:-0.72 ]")
    df = Kl.currentdf['df'] 

    df.index=pd.to_datetime(df.datetime)
    df['openinterest'] = 0
    df= df[['open','high','low','close','vol','openinterest']]

    data = PandasData(dataname=df)

    cerebro.adddata(data)

    cerebro.addsizer(LongOnly)
    cerebro.broker.setcash(100000[ NaN:0 ].0)
    
    print('成本: %.2f' % cerebro.broker.getvalue())
    # Run over everything
    cerebro.run()

    print('总剩余: %.2f' % cerebro.broker.getvalue())
    # Plot the result
    cerebro.plot(style='bar')   

if __name__ == '__main__':
    Klang.Klang_init(); #加载所有股票列表

    init_btr();

结果：
正在从文件 /Users/jiashenghe/.klang_stock_list.csv 加载股票列表
正在从网上下载股票数据,时间将会有点长
成本: 100000.00
2021-09-02, BUY EXECUTED, Price: 11.55, Cost: 94998.75, Comm 0.00,value 100082.25
2021-10-27, SELL EXECUTED, Price: 11.60, Cost: 94998.75, Comm 0.00,value 100411.25
2021-11-19, BUY EXECUTED, Price: 11.75, Cost: 95386.50, Comm 0.00,value 100979.51
2022-01-27, SELL EXECUTED, Price: 12.15, Cost: 95386.50, Comm 0.00,value 103658.45
2022-03-08, BUY EXECUTED, Price: 12.54, Cost: 98627.10, Comm 0.00,value 99883.25
2022-03-09, SELL EXECUTED, Price: 12.10, Cost: 98627.10, Comm 0.00,value 100197.85
2022-03-23, BUY EXECUTED, Price: 12.84, Cost: 95182.92, Comm 0.00,value 100271.98
总剩余: 228220.36