張郎生活的筆記

參考資料 : https://www.backtrader.com/docu/quickstart/quickstart.html

有一些地方我也還不懂, 不過不影響操作(....吧?)

先輸入以下代碼

import backtrader as bt
import pandas as pd
import datetime

if __name__ == '__main__':
    cerebro = bt.Cerebro()
    cerebro.broker.setcash(100000.0)

    print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())

    cerebro.run()

    print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())

當然也是先import必要的套件

然後引入"經紀人broker", 大概是理專之類的意思吧

然後資金設為十萬~

cerebro.run()策略執行前後, 分別print出資金的變化

然後載入我們的數據

import backtrader as bt
import pandas as pd
import datetime

if __name__ == '__main__':
    cerebro = bt.Cerebro()
    
    cerebro.broker.setcash(100000.0)
    
    dataframe = pd.read_csv('d://0050.tw.csv', index_col=0, parse_dates=True)
    dataframe['openinterest'] = 0
    data0 = bt.feeds.PandasData(dataname=dataframe,
                                   fromdate = datetime.datetime(2008, 1, 1),
                                   todate = datetime.datetime(2010, 1, 1)
                                    )

    cerebro.adddata(data0) 

    print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())

    cerebro.run()

    print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())

執行結果沒有啥米變化, 因為我們還沒有導入策略

dataframe['openinterest'] = 0是做啥的我還不清楚, 為什麼要在數據最後多加一行這個呢?

然後開始導入策略

import backtrader as bt
import pandas as pd
import datetime

class TestStrategy(bt.Strategy):

    def log(self, txt, dt=None):
        ''' Logging function fot this strategy'''
        dt = 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]:
                    if self.dataclose[-1] < self.dataclose[-2]:

                        self.log('BUY CREATE, %.2f' % self.dataclose[0])

                        self.order = self.buy()

        else:
            if self.dataclose[-1] > self.dataclose[-2]:
                if self.dataclose[0] > self.dataclose[-1]:                     

                    self.log('SELL CREATE, %.2f' % self.dataclose[0])

                    self.order = self.sell()
                    
if __name__ == '__main__':
    cerebro = bt.Cerebro()    
    cerebro.addstrategy(TestStrategy)      
    cerebro.broker.setcash(100000.0)
    
    dataframe = pd.read_csv('d://0050.tw.csv', index_col=0, parse_dates=True)
    dataframe['openinterest'] = 0
    data0 = bt.feeds.PandasData(dataname=dataframe,
                                   fromdate = datetime.datetime(2008, 1, 1),
                                   todate = datetime.datetime(2010, 1, 1)
                                    )

    cerebro.adddata(data0) 
    print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())

    cerebro.run()

    print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
 

程式碼雖然看起來一大串, 但是我們先注意在紅色的部分就好

self.dataclose[0] < self.dataclose[-1] 意思是今天收盤價  < 昨天收盤價

self.dataclose[-1] < self.dataclose[-2] 昨天收盤價 < 前天收盤價

也就是連三跌的意思, 咱們就給他買下去

那賣出的我們設為相反, 連三漲就給他放棄..喔不是

執行看看

哇! 賺錢耶! 聖杯~~

那我們檢查一下

2009-11-25 54元

2009-11-26 53.85元

2009-11-27 52.20元

符合連三跌, 所以買進

我們最愛看圖表了, 在程式碼最後加這一行 cerebro.plot()

完整程式碼在貼一次

import backtrader as bt
import pandas as pd
import datetime
class TestStrategy(bt.Strategy):
    def log(self, txt, dt=None):
        ''' Logging function fot this strategy'''
        dt = 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]:
                    if self.dataclose[-1] < self.dataclose[-2]:
                        self.log('BUY CREATE, %.2f' % self.dataclose[0])
                        self.order = self.buy()
        else:
            if self.dataclose[-1] > self.dataclose[-2]:
                if self.dataclose[0] > self.dataclose[-1]:                     
                    self.log('SELL CREATE, %.2f' % self.dataclose[0])
                    self.order = self.sell()
                    
if __name__ == '__main__':
    

    
    cerebro = bt.Cerebro()
    
    cerebro.addstrategy(TestStrategy)
    
    cerebro.broker.setcash(100000.0)
    
    dataframe = pd.read_csv('d://0050.tw.csv', index_col=0, parse_dates=True)
    dataframe['openinterest'] = 0
    data0 = bt.feeds.PandasData(dataname=dataframe,
                                   fromdate = datetime.datetime(2008, 1, 1),
                                   todate = datetime.datetime(2010, 1, 1)
                                    )
    cerebro.adddata(data0) 

    print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
    cerebro.run()
    print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
    cerebro.plot()