Backtrader寫下來

隨著 1.1.7.88 版本的發布， backtrader有了一個新的補充：作家

這可能早就到期了，應該已經存在了，問題 #14中的討論也應該已經開始了開發。

但遲到總比沒有好。

Writer實現嘗試與backtrader環境中的其他對象保持一致

通過Cerebro添加
提供最合理的默認值
不要強迫用戶做太多事情

當然，更重要的是了解作者實際寫了什麼。那就是：

的 CSV 輸出

- `datas` added to the system (can be switched off)

- `strategies` (a Strategy can have named lines)

- `indicators` inside the strategies (only 1st level)

- `observers` inside the strategies (only 1st level)

Which `indicators` and `observers` output data to the CSV stream is
controlled by the attribute:

  `csv` in each instance

The defaults are:

  - Observers have `csv = True`

  - Indicators have `csv = False`

The value can be overriden for any instance created inside a strategy

回測階段結束後， Writers為Cerebro實例添加一個新部分，並添加以下子部分：

系統中datas的屬性（名稱、壓縮、時間範圍）
系統中strategies的屬性（行、參數）
- 策略中indicators的屬性（行、參數）
- 策略中observers的屬性（行，參數）
- 具有以下屬性的分析器
- 參數
- 分析

考慮到所有這些，一個例子可能是展示writers的力量（或弱點）的最簡單方法。

但在如何將它們添加到cerebro之前。

將writer參數用於cerebro ：
```
cerebro = bt.Cerebro(writer=True)
```
這將創建一個默認實例。
具體補充：
```
cerebro = bt.Cerebro()

cerebro.addwriter(bt.WriterFile, csv=False)
```
添加（現在唯一的writer ）一個WriterFile類到writer列表，以便稍後用csv= False實例化（不會在輸出中生成 csv 流。

多空策略的長期示例（完整代碼見下文），通過執行使用Close -SMA 交叉作為信號：

$ ./writer-test.py

圖表：

使用以下輸出：

===============================================================================
Cerebro:
  -----------------------------------------------------------------------------
  - Datas:
    +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
    - Data0:
      - Name: 2006-day-001
      - Timeframe: Days
      - Compression: 1
  -----------------------------------------------------------------------------
  - Strategies:
    +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
    - LongShortStrategy:
      *************************************************************************
      - Params:
        - csvcross: False
        - printout: False
        - onlylong: False
        - stake: 1
        - period: 15
      *************************************************************************
      - Indicators:
        .......................................................................
        - SMA:
          - Lines: sma
          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
          - Params:
            - period: 15
        .......................................................................
        - CrossOver:
          - Lines: crossover
          - Params: None
      *************************************************************************
      - Observers:
        .......................................................................
        - Broker:
          - Lines: cash, value
          - Params: None
        .......................................................................
        - BuySell:
          - Lines: buy, sell
          - Params: None
        .......................................................................
        - Trades:
          - Lines: pnlplus, pnlminus
          - Params: None
      *************************************************************************
      - Analyzers:
        .......................................................................
        - Value:
          - Begin: 100000
          - End: 100826.1
        .......................................................................
        - SQN:
          - Params: None
          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
          - Analysis:
            - sqn: 0.05
            - trades: 22

運行後，我們對系統的設置方式以及分析人員最後所說的內容進行了完整的總結。在這種情況下，分析儀是

Value是策略中的一個假分析器，它收集投資組合的開始和結束值
由 Van K. Tharp 定義的SQN （或 SystemQualityNumber）（除了backtrader 1.1.7.88，它告訴我們它已經看到 22 筆交易併計算出 0.05 的sqn 。
這實際上是相當低的。我們可以通過查看一整年後的小額利潤來弄清楚（幸運的是系統沒有虧損）

測試腳本允許我們將策略調整為long-only ：

$ ./writer-test.py --onlylong --plot

圖表：

現在的輸出是：

===============================================================================
Cerebro:
  -----------------------------------------------------------------------------
  - Datas:
    +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
    - Data0:
      - Name: 2006-day-001
      - Timeframe: Days
      - Compression: 1
  -----------------------------------------------------------------------------
  - Strategies:
    +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
    - LongShortStrategy:
      *************************************************************************
      - Params:
        - csvcross: False
        - printout: False
        - onlylong: True
        - stake: 1
        - period: 15
      *************************************************************************
      - Indicators:
        .......................................................................
        - SMA:
          - Lines: sma
          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
          - Params:
            - period: 15
        .......................................................................
        - CrossOver:
          - Lines: crossover
          - Params: None
      *************************************************************************
      - Observers:
        .......................................................................
        - Broker:
          - Lines: cash, value
          - Params: None
        .......................................................................
        - BuySell:
          - Lines: buy, sell
          - Params: None
        .......................................................................
        - Trades:
          - Lines: pnlplus, pnlminus
          - Params: None
      *************************************************************************
      - Analyzers:
        .......................................................................
        - Value:
          - Begin: 100000
          - End: 102795.0
        .......................................................................
        - SQN:
          - Params: None
          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
          - Analysis:
            - sqn: 0.91
            - trades: 11

可以看到策略“參數”的變化（onlylong 已變為True ），分析器講述了一個不同的故事：

期末價值從 100826.1 提高到 102795.0
SQN 看到的交易從 22 減少到 11
SQN 分數從 0.05 增長到 0.91，這要好得多

但是仍然看不到 CSV 輸出。讓我們運行腳本來打開它：

$ ./writer-test.py --onlylong --writercsv

更新輸出：

===============================================================================
Id,2006-day-001,len,datetime,open,high,low,close,volume,openinterest,LongShortStrategy,len,Broker,len,cash,value,Buy
Sell,len,buy,sell,Trades,len,pnlplus,pnlminus
1,2006-day-001,1,2006-01-02 23:59:59+00:00,3578.73,3605.95,3578.73,3604.33,0.0,0.0,LongShortStrategy,1,Broker,1,1000
00.0,100000.0,BuySell,1,,,Trades,1,,
2,2006-day-001,2,2006-01-03 23:59:59+00:00,3604.08,3638.42,3601.84,3614.34,0.0,0.0,LongShortStrategy,2,Broker,2,1000
00.0,100000.0,BuySell,2,,,Trades,2,,
...
...
...
255,2006-day-001,255,2006-12-29 23:59:59+00:00,4130.12,4142.01,4119.94,4119.94,0.0,0.0,LongShortStrategy,255,Broker,255,100795.0,102795.0,BuySell,255,,,Trades,255,,
===============================================================================
Cerebro:
  -----------------------------------------------------------------------------
...
...

我們可以跳過大部分 csv 流和已經看到的摘要。 CSV 流已打印出以下內容

開頭的剖麵線分隔符
標題行
對應數據

請注意每個對像如何打印其“長度”。儘管在這種情況下它沒有提供太多信息，但如果使用多時間幀數據或重放數據，它會提供。

writer默認執行以下操作：

沒有打印指標（簡單移動平均線和交叉點都沒有）
觀察者被打印出來

讓我們使用附加參數運行腳本，以將 CrossOver 指示器添加到 CSV 流中：

$ ./writer-test.py --onlylong --writercsv --csvcross

輸出：

===============================================================================
Id,2006-day-001,len,datetime,open,high,low,close,volume,openinterest,LongShortStrategy,len,CrossOver,len,crossover,B
roker,len,cash,value,BuySell,len,buy,sell,Trades,len,pnlplus,pnlminus
1,2006-day-001,1,2006-01-02 23:59:59+00:00,3578.73,3605.95,3578.73,3604.33,0.0,0.0,LongShortStrategy,1,CrossOver,1,,
Broker,1,100000.0,100000.0,BuySell,1,,,Trades,1,,
...
...

這顯示了作家的一些力量。該類的進一步文檔仍然是待辦事項。

同時，示例中使用的執行可能性和代碼。

用法：

$ ./writer-test.py --help
usage: writer-test.py [-h] [--data DATA] [--fromdate FROMDATE]
                      [--todate TODATE] [--period PERIOD] [--onlylong]
                      [--writercsv] [--csvcross] [--cash CASH] [--comm COMM]
                      [--mult MULT] [--margin MARGIN] [--stake STAKE] [--plot]
                      [--numfigs NUMFIGS]

MultiData Strategy

optional arguments:
  -h, --help            show this help message and exit
  --data DATA, -d DATA  data to add to the system
  --fromdate FROMDATE, -f FROMDATE
                        Starting date in YYYY-MM-DD format
  --todate TODATE, -t TODATE
                        Starting date in YYYY-MM-DD format
  --period PERIOD       Period to apply to the Simple Moving Average
  --onlylong, -ol       Do only long operations
  --writercsv, -wcsv    Tell the writer to produce a csv stream
  --csvcross            Output the CrossOver signals to CSV
  --cash CASH           Starting Cash
  --comm COMM           Commission for operation
  --mult MULT           Multiplier for futures
  --margin MARGIN       Margin for each future
  --stake STAKE         Stake to apply in each operation
  --plot, -p            Plot the read data
  --numfigs NUMFIGS, -n NUMFIGS
                        Plot using numfigs figures

和測試腳本。

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

import argparse
import datetime

# The above could be sent to an independent module
import backtrader as bt
import backtrader.feeds as btfeeds
import backtrader.indicators as btind
from backtrader.analyzers import SQN


class LongShortStrategy(bt.Strategy):
    '''This strategy buys/sells upong the close price crossing
    upwards/downwards a Simple Moving Average.

    It can be a long-only strategy by setting the param "onlylong" to True
    '''
    params = dict(
        period=15,
        stake=1,
        printout=False,
        onlylong=False,
        csvcross=False,
    )

    def start(self):
        pass

    def stop(self):
        pass

    def log(self, txt, dt=None):
        if self.p.printout:
            dt = dt or self.data.datetime[0]
            dt = bt.num2date(dt)
            print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):
        # To control operation entries
        self.orderid = None

        # Create SMA on 2nd data
        sma = btind.MovAv.SMA(self.data, period=self.p.period)
        # Create a CrossOver Signal from close an moving average
        self.signal = btind.CrossOver(self.data.close, sma)
        self.signal.csv = self.p.csvcross

    def next(self):
        if self.orderid:
            return  # if an order is active, no new orders are allowed

        if self.signal > 0.0:  # cross upwards
            if self.position:
                self.log('CLOSE SHORT , %.2f' % self.data.close[0])
                self.close()

            self.log('BUY CREATE , %.2f' % self.data.close[0])
            self.buy(size=self.p.stake)

        elif self.signal < 0.0:
            if self.position:
                self.log('CLOSE LONG , %.2f' % self.data.close[0])
                self.close()

            if not self.p.onlylong:
                self.log('SELL CREATE , %.2f' % self.data.close[0])
                self.sell(size=self.p.stake)

    def notify_order(self, order):
        if order.status in [bt.Order.Submitted, bt.Order.Accepted]:
            return  # Await further notifications

        if order.status == order.Completed:
            if order.isbuy():
                buytxt = 'BUY COMPLETE, %.2f' % order.executed.price
                self.log(buytxt, order.executed.dt)
            else:
                selltxt = 'SELL COMPLETE, %.2f' % order.executed.price
                self.log(selltxt, order.executed.dt)

        elif order.status in [order.Expired, order.Canceled, order.Margin]:
            self.log('%s ,' % order.Status[order.status])
            pass  # Simply log

        # Allow new orders
        self.orderid = None

    def notify_trade(self, trade):
        if trade.isclosed:
            self.log('TRADE PROFIT, GROSS %.2f, NET %.2f' %
                     (trade.pnl, trade.pnlcomm))

        elif trade.justopened:
            self.log('TRADE OPENED, SIZE %2d' % trade.size)


def runstrategy():
    args = parse_args()

    # Create a cerebro
    cerebro = bt.Cerebro()

    # Get the dates from the args
    fromdate = datetime.datetime.strptime(args.fromdate, '%Y-%m-%d')
    todate = datetime.datetime.strptime(args.todate, '%Y-%m-%d')

    # Create the 1st data
    data = btfeeds.BacktraderCSVData(
        dataname=args.data,
        fromdate=fromdate,
        todate=todate)

    # Add the 1st data to cerebro
    cerebro.adddata(data)

    # Add the strategy
    cerebro.addstrategy(LongShortStrategy,
                        period=args.period,
                        onlylong=args.onlylong,
                        csvcross=args.csvcross,
                        stake=args.stake)

    # Add the commission - only stocks like a for each operation
    cerebro.broker.setcash(args.cash)

    # Add the commission - only stocks like a for each operation
    cerebro.broker.setcommission(commission=args.comm,
                                 mult=args.mult,
                                 margin=args.margin)

    cerebro.addanalyzer(SQN)

    cerebro.addwriter(bt.WriterFile, csv=args.writercsv, rounding=2)

    # And run it
    cerebro.run()

    # Plot if requested
    if args.plot:
        cerebro.plot(numfigs=args.numfigs, volume=False, zdown=False)


def parse_args():
    parser = argparse.ArgumentParser(description='MultiData Strategy')

    parser.add_argument('--data', '-d',
                        default='../../datas/2006-day-001.txt',
                        help='data to add to the system')

    parser.add_argument('--fromdate', '-f',
                        default='2006-01-01',
                        help='Starting date in YYYY-MM-DD format')

    parser.add_argument('--todate', '-t',
                        default='2006-12-31',
                        help='Starting date in YYYY-MM-DD format')

    parser.add_argument('--period', default=15, type=int,
                        help='Period to apply to the Simple Moving Average')

    parser.add_argument('--onlylong', '-ol', action='store_true',
                        help='Do only long operations')

    parser.add_argument('--writercsv', '-wcsv', action='store_true',
                        help='Tell the writer to produce a csv stream')

    parser.add_argument('--csvcross', action='store_true',
                        help='Output the CrossOver signals to CSV')

    parser.add_argument('--cash', default=100000, type=int,
                        help='Starting Cash')

    parser.add_argument('--comm', default=2, type=float,
                        help='Commission for operation')

    parser.add_argument('--mult', default=10, type=int,
                        help='Multiplier for futures')

    parser.add_argument('--margin', default=2000.0, type=float,
                        help='Margin for each future')

    parser.add_argument('--stake', default=1, type=int,
                        help='Stake to apply in each operation')

    parser.add_argument('--plot', '-p', action='store_true',
                        help='Plot the read data')

    parser.add_argument('--numfigs', '-n', default=1,
                        help='Plot using numfigs figures')

    return parser.parse_args()


if __name__ == '__main__':
    runstrategy()

Backtrader寫下來

推薦閱讀

相關文章

Backtrader教程：經紀人 - 開倉作弊

BacktraderPython Hidden Powers 2

Backtrader訂單歷史

Backtrader在同一軸上列印

Backtrader實際使用方式

Backtrader Python隐藏的细节

Backtrader 教程：數據饋送 - 開發 - CSV

Backtrader開場作弊

Backtrader信貸利息

Backtrader熊貓數據饋送