量化交易學習筆記（十三）——第一個策略回測程序v11 頭條網

2020-11-23 03:41:48 佚名

v11是第一個策略回測程序的最後一個版本，將對策略參數進行優化。

很多財經書籍裡都指出，不同股票、不同書籍都有個各自的特點和節奏，因此使用同一策略參數應用於所有的交易是不明智的。

在之前的例子中，我們嘗試了使用了簡單移動均值指標，週期參數選定為15，v11將對這個參數進行優化，通過優化找出簡單移動均值的最佳週期數。程序的主要修改部分為在向cerebro添加策略時使用如下代碼：

<code>strats
 = cerebro.optstrategy(
        TestStrategy,
        maperiod
 = range(10, 31))
/<code>

這樣backtrader就會將將簡單移動均值所選取的週期數從10到31進行逐個嘗試，通過計算最終收益，便可以選擇出最優的參數。

v11輸出為：

<code>2020
-02 
-04
,
 (MA
 Period
 10
)
 Ending
 Value
 99852.22
2020
-02
-04
,
 (MA
 Period
 11
)
 Ending
 Value
 99914.55
2020
-02
-04
,
 (MA 
 Period
 12
)
 Ending
 Value
 99946.91
2020
-02
-04
,
 (MA
 Period
 13
)
 Ending
 Value
 99948.27
2020
-02
-04
,
 (MA
 Period
 14
) 
 Ending
 Value
 99957.74
2020
-02
-04
,
 (MA
 Period
 15
)
 Ending
 Value
 99990.11
2020
-02
-04
,
 (MA
 Period
 16
)
 Ending
 Value
 99990.11 

2020
-02
-04
,
 (MA
 Period
 17
)
 Ending
 Value
 100031.43
2020
-02
-04
,
 (MA
 Period
 18
)
 Ending
 Value
 100031.43
2020
-02
-04 
,
 (MA
 Period
 19
)
 Ending
 Value
 99985.39
2020
-02
-04
,
 (MA
 Period
 20
)
 Ending
 Value
 100003.41
2020
-02
-04
,
 (MA
 Period 
 21
)
 Ending
 Value
 99977.38
2020
-02
-04
,
 (MA
 Period
 22
)
 Ending
 Value
 99990.39
2020
-02
-04
,
 (MA
 Period
 23
)
 Ending 
 Value
 99985.39
2020
-02
-04
,
 (MA
 Period
 24
)
 Ending
 Value
 100036.74
2020
-02
-04
,
 (MA
 Period
 25
)
 Ending
 Value
 100036.74
2020 
-02
-04
,
 (MA
 Period
 26
)
 Ending
 Value
 100022.75
2020
-02
-04
,
 (MA
 Period
 27
)
 Ending
 Value
 100022.75
2020
-02
-04
, 
 (MA
 Period
 28
)
 Ending
 Value
 100022.75
2020
-02
-04
,
 (MA
 Period
 29
)
 Ending
 Value
 100022.75
2020
-02
-04
,
 (MA
 Period
 30 
)
 Ending
 Value
 99977.52
/<code>

通過上面的輸出信息我們就可以清晰地看到，選擇不同週期參數時最後的資產情況。本例中，當週期參數選擇為24和25時，可以獲得最大收益。

程序v10-優化：

<code>from __future__ import (absolute_import, division, print_function,
                        unicode_literals)
import datetime   
import os.path   
import sys   
import backtrader as bt  

 
class
 TestStrategy
(bt
.Strategy
):
    params = (
        ('maperiod'
, 15),
        ('printlog', False),
    )
    
def
 log
(
self
, txt, dt=None, doprint = False)
:
        '' 
' 策略的日誌函數'
''
        if
 self
.params.printlog or
 doprint:
            dt = dt or
 self
.datas[0
].datetime.date(0)
            print('%s, %s' % (dt.isoformat(), txt))
    
def
 __init__
(
self
)
:
         
        self
.dataclose = self
.datas[0].close
         
        self.order = None
        self.buyprice = None
        self.buycomm = None
         
        self.sma = bt.indicators.SimpleMovingAverage(
                self
.datas[0 
], period = self.params.maperiod)
    
def
 notify_order
(
self
, order)
:
        if
 order.status in [order.Submitted, order.Accepted]:
             
            return
         
         
        if
 order.status in [order.Completed]:
            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:  
                self
.log('SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
                         (order.executed.price,
                          order.executed.value,
                          order.executed.comm))
            self
.bar_executed = len(self)
        elif order.status in [order.Canceled, order.Margin, order.Rejected]:
            self
.log('Order Canceled/Margin/Rejected')
         
        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
)
:
         
        self
.log('Close, %.2f'
 % self
.dataclose[0])
         
        if
 self
.order:
            return
         
        if 
 not
 self
.position:
             
             
             
            if
 self
.dataclose[0
] > self
.sma[0]:
                 
                self
.log('BUY CREATE, %.2f'
 % self
.dataclose[0])
                 
                self
.order = self.buy()
         
        else:
             
            if
 self
.dataclose[0
] self
.sma[0]:
                self
.log('SELL CREATE, %.2f'
 % self
.dataclose[0])
                 
                self 
.order = self.sell()
    
def
 stop
(
self
)
:
        self
.log('(MA Period %2d) Ending Value %.2f' %
                 (self
.params.maperiod, self.broker.getvalue()), doprint = True)
                
 
cerebro = bt.Cerebro()
 
strats = cerebro.optstrategy(
        TestStrategy,
        maperiod = range(10
, 31))
 
 
modpath = os.path.dirname(os.path.abspath(sys.argv[0]))
datapath = os.path.join(modpath, '../../TQDat/day/stk/000001.csv')
 
data = bt.feeds.GenericCSVData(
        dataname = datapath,
        fromdate = datetime.datetime(2019
, 10
, 1),
        todate = datetime.datetime(2020
, 2
, 29),
        nullvalue = 0
.0,
        dtformat = ('%Y/%m/%d'),
        datetime = 0,
        open = 1 
,
        high = 2,
        low = 3,
        close = 4,
        volume = 5,
        openinterest = -1
        )
 
cerebro.adddata(data)
 
cerebro.broker.setcash(100000.0)
 
cerebro.addsizer(bt.sizers.FixedSize, stake = 100)
 
cerebro.broker.setcommission(commission=0
.001)
 
cerebro.run(maxcpus = 1
)/<code>