哪个网站做推广好,湘潭今天刚刚发生的新闻,网站系统下载,长荣建设深圳公司网站Backtrader 文档学习- Observers
1.概述
在backtrader中运行的策略主要处理数据源和指标。 数据源被加载到Cerebro实例中#xff0c;并最终成为策略的一部分#xff08;解析和提供实例的属性#xff09;#xff0c;而指标则由策略本身声明和管理。 到目前为止#xff0c…Backtrader 文档学习- Observers
1.概述
在backtrader中运行的策略主要处理数据源和指标。 数据源被加载到Cerebro实例中并最终成为策略的一部分解析和提供实例的属性而指标则由策略本身声明和管理。 到目前为止所有backtrader示例图表都有三个默认绘制的东西因为它们没有在任何地方声明默认执行
现金和价值经纪人中的资金情况交易也称为操作买入/卖出订单 它们是Observers观察者存在于子模块backtrader.observers中。它们存在是因为Cerebro支持一个参数来自动添加或不添加它们到策略中stdstats默认值True 如果默认值被使用Cerebro将执行以下等效的用户代码
import backtrader as bt...cerebro bt.Cerebro() # default kwarg: stdstatsTruecerebro.addobserver(bt.observers.Broker)
cerebro.addobserver(bt.observers.Trades)
cerebro.addobserver(bt.observers.BuySell)观察带有这三个默认观察者的常规图表即使没有下达订单没有交易发生现金和组合价值也没有变化
from __future__ import (absolute_import, division, print_function,unicode_literals)
%matplotlib inline
import backtrader as bt
import backtrader.feeds as btfeedsif __name__ __main__:cerebro bt.Cerebro() # stdstatsFalsecerebro.addstrategy(bt.Strategy)data bt.feeds.BacktraderCSVData(dataname./datas/2006-day-001.txt)cerebro.adddata(data)cerebro.run()cerebro.plot(iplotFalse)图示 在创建Cerebro实例时将stdstats的值更改为False也可以在调用run时完成: cerebro bt.Cerebro(stdstatsFalse) 2.Accesing the Observers
观察者在默认情况下已经存在并收集可用于统计目的的信息这就是为什么可以通过策略的一个属性来访问观察者
stats
它只是一个占位符。如果回想一下如何添加默认的观察者
...
cerebro.addobserver(backtrader.observers.Broker)
...显然问题是如何访问Broker观察者。例如如何从策略的next方法中执行此操作
class MyStrategy(bt.Strategy):def next(self):if self.stats.broker.value[0] 1000.0:print(WHITE FLAG ... I LOST TOO MUCH)elif self.stats.broker.value[0] 10000000.0:print(TIME FOR THE VIRGIN ISLANDS ....!!!)Broker观察者就像数据、指标和策略本身一样也是一个Lines对象。在这种情况下Broker有2条线
cashvalue
3.Observer Implementation
实现与指标非常相似
class Broker(Observer):alias (CashValue,)lines (cash, value)plotinfo dict(plotTrue, subplotTrue)def next(self):self.lines.cash[0] self._owner.broker.getcash()self.lines.value[0] value self._owner.broker.getvalue()步骤
从Observer而不是Indicator派生根据需要声明行和参数Broker有2行但没有参数将自动属性_owner设置为持有观察者的策略
注意_owner的属性
观察者开始工作
在所有指标计算完成后在策略next方法执行后意味着在循环结束时…观察到发生了什么 在Broker中只是机械地记录在每个时间点上经纪人现金和组合价值。
4.Adding Observers to the Strategy
如上所指出的Cerebro使用stdstats参数来决定是否添加3个默认的观察者减轻了最终用户的工作。 添加其他观察者是可能的无论是沿着stdstats还是删除它们。 让我们采用通常的策略当close价格超过SimpleMovingAverage时购买如果相反则卖出。 增加一个观察者
DrawDown 回撤它是backtrader 生态系统中已经存在的观察者
from __future__ import (absolute_import, division, print_function,unicode_literals)import argparse
import datetime
import os.path
import time
import sysimport backtrader as bt
import backtrader.feeds as btfeeds
import backtrader.indicators as btind%matplotlib inlineclass MyStrategy(bt.Strategy):params ((smaperiod, 15),)def log(self, txt, dtNone): Logging function fot this strategydt dt or self.data.datetime[0]if isinstance(dt, float):dt bt.num2date(dt).date()print(%s, %s % (dt.isoformat(), txt))def __init__(self):# SimpleMovingAverage on main data# Equivalent to - sma btind.SMA(self.data, periodself.p.smaperiod)sma btind.SMA(periodself.p.smaperiod)# CrossOver (1: up, -1: down) close / smaself.buysell btind.CrossOver(self.data.close, sma, plotTrue)# Sentinel to None: new ordersa allowedself.order Nonedef next(self):# Access -1, because drawdown[0] will be calculated after nextself.log(DrawDown: %.2f % self.stats.drawdown.drawdown[-1])self.log(MaxDrawDown: %.2f % self.stats.drawdown.maxdrawdown[-1])# Check if we are in the marketif self.position:if self.buysell 0:self.log(SELL CREATE, %.2f % self.data.close[0])self.sell()elif self.buysell 0:self.log(BUY CREATE, %.2f % self.data.close[0])self.buy()def runstrat():cerebro bt.Cerebro()data bt.feeds.BacktraderCSVData(dataname./datas/2006-day-001.txt)cerebro.adddata(data)cerebro.addobserver(bt.observers.DrawDown)cerebro.addstrategy(MyStrategy)cerebro.run()cerebro.plot(iplotFalse)if __name__ __main__:runstrat()图表的输出显示了回撤的演变 输出
... ...
2006-12-12, DrawDown: 0.63
2006-12-12, MaxDrawDown: 2.62
2006-12-13, DrawDown: 0.63
2006-12-13, MaxDrawDown: 2.62
2006-12-14, DrawDown: 0.56
2006-12-14, MaxDrawDown: 2.62
2006-12-15, DrawDown: 0.22
2006-12-15, MaxDrawDown: 2.62
2006-12-18, DrawDown: 0.00
2006-12-18, MaxDrawDown: 2.62
2006-12-19, DrawDown: 0.00
2006-12-19, MaxDrawDown: 2.62
2006-12-20, DrawDown: 0.10
2006-12-20, MaxDrawDown: 2.62
2006-12-21, DrawDown: 0.39
2006-12-21, MaxDrawDown: 2.62
2006-12-22, DrawDown: 0.21
2006-12-22, MaxDrawDown: 2.62
2006-12-27, DrawDown: 0.28
2006-12-27, MaxDrawDown: 2.62
2006-12-28, DrawDown: 0.65
2006-12-28, MaxDrawDown: 2.62
2006-12-29, DrawDown: 0.06
2006-12-29, MaxDrawDown: 2.62注意 如文本输出和代码中所示DrawDown观察者实际上有2条线
drawdownmaxdrawdown 选择不绘制最大回撤线但使其可供用户使用。 实际上maxdrawdown的最后一个值也可以通过一个直接属性而不是一条线来获得该属性的名称为maxdd
5.Developing Observers
上面展示了Broker观察者的实现。为了产生有意义的观察者实现可以使用以下信息 self._owner是当前正在执行的策略 策略中的任何内容都可以用于观察者 策略中可用的默认内部内容可能有用 broker- 属性提供对策略创建订单的broker实例的访问 如在Broker中所见通过调用方法getcash和getvalue收集现金和组合值 _orderspending- 策略创建的订单列表broker已向策略通知事件。 BuySell观察者遍历列表查找已执行完全或部分的订单以创建给定时间点索引0的平均执行价格 _tradespending- 交易列表已完成的买入/卖出或卖出/买入对的集合从买入/卖出订单编译而成 观察者可以通过self._owner.stats路径访问其他观察者。
6.Custom OrderObserver
标准的BuySell观察者只关心已执行的操作。可以创建一个观察者显示订单何时创建以及它们是否过期。 为了可见性显示将不会沿价格轴上绘制而是在单独的轴上绘制。
from __future__ import (absolute_import, division, print_function,unicode_literals)import datetimeimport backtrader as bt
import backtrader.feeds as btfeeds
import backtrader.indicators as btind#直接放在一个程序中。
#from backtrader.orderobserver import OrderObserver
%matplotlib inlineclass MyStrategy(bt.Strategy):params ((smaperiod, 15),(limitperc, 1.0),(valid, 7),)def log(self, txt, dtNone): Logging function fot this strategydt dt or self.data.datetime[0]if isinstance(dt, float):dt bt.num2date(dt).date()print(%s, %s % (dt.isoformat(), txt))def notify_order(self, order):if order.status in [order.Submitted, order.Accepted]:# Buy/Sell order submitted/accepted to/by broker - Nothing to doself.log(ORDER ACCEPTED/SUBMITTED, dtorder.created.dt)self.order orderreturnif order.status in [order.Expired]:self.log(BUY EXPIRED)elif 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))else: # Sellself.log(SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f %(order.executed.price,order.executed.value,order.executed.comm))# Sentinel to None: new orders allowedself.order Nonedef __init__(self):# SimpleMovingAverage on main data# Equivalent to - sma btind.SMA(self.data, periodself.p.smaperiod)sma btind.SMA(periodself.p.smaperiod)# CrossOver (1: up, -1: down) close / smaself.buysell btind.CrossOver(self.data.close, sma, plotTrue)# Sentinel to None: new ordersa allowedself.order Nonedef next(self):if self.order:# pending order ... do nothingreturn# Check if we are in the marketif self.position:if self.buysell 0:self.log(SELL CREATE, %.2f % self.data.close[0])self.sell()elif self.buysell 0:plimit self.data.close[0] * (1.0 - self.p.limitperc / 100.0)valid self.data.datetime.date(0) \datetime.timedelta(daysself.p.valid)self.log(BUY CREATE, %.2f % plimit)self.buy(exectypebt.Order.Limit, priceplimit, validvalid)class OrderObserver(bt.observer.Observer):lines (created, expired,)plotinfo dict(plotTrue, subplotTrue, plotlinelabelsTrue)plotlines dict(createddict(marker*, markersize8.0, colorlime, fillstylefull),expireddict(markers, markersize8.0, colorred, fillstylefull))def next(self):for order in self._owner._orderspending:if order.data is not self.data:continueif not order.isbuy():continue# Only interested in buy orders, because the sell orders# in the strategy are Market orders and will be immediately# executedif order.status in [bt.Order.Accepted, bt.Order.Submitted]:self.lines.created[0] order.created.priceelif order.status in [bt.Order.Expired]:self.lines.expired[0] order.created.pricedef runstrat():cerebro bt.Cerebro()data bt.feeds.BacktraderCSVData(dataname./datas/2006-day-001.txt)cerebro.adddata(data)cerebro.addobserver(OrderObserver)cerebro.addstrategy(MyStrategy)cerebro.run()cerebro.plot(iplotFalse)if __name__ __main__:runstrat()自定义观察者只关心买入订单因为这是一种只买入以试图获利的策略。卖出订单是市价订单将立即执行。 Close-SMA CrossOver策略规则更改为
创建一个价格低于此时刻收盘价1.0以下的限价订单订单的有效期为7日历天
如新子图红色方块所示新增的Observer 对象created 和 expired 有几个订单已过期还看到在创建和执行间隔了几天。
输出结果
2006-01-26, BUY CREATE, 3605.01
2006-01-26, ORDER ACCEPTED/SUBMITTED
2006-01-26, ORDER ACCEPTED/SUBMITTED
2006-02-02, BUY EXPIRED
2006-03-10, BUY CREATE, 3760.48
2006-03-10, ORDER ACCEPTED/SUBMITTED
2006-03-10, ORDER ACCEPTED/SUBMITTED
2006-03-17, BUY EXPIRED
2006-03-30, BUY CREATE, 3835.86
2006-03-30, ORDER ACCEPTED/SUBMITTED
2006-03-30, ORDER ACCEPTED/SUBMITTED
2006-04-05, BUY EXECUTED, Price: 3835.86, Cost: 3835.86, Comm 0.00
2006-04-07, SELL CREATE, 3823.11
2006-04-07, ORDER ACCEPTED/SUBMITTED
2006-04-07, ORDER ACCEPTED/SUBMITTED
2006-04-10, SELL EXECUTED, Price: 3822.35, Cost: 3835.86, Comm 0.00
2006-04-20, BUY CREATE, 3821.40
2006-04-20, ORDER ACCEPTED/SUBMITTED
2006-04-20, ORDER ACCEPTED/SUBMITTED
2006-04-27, BUY EXPIRED
2006-05-04, BUY CREATE, 3804.65
2006-05-04, ORDER ACCEPTED/SUBMITTED
2006-05-04, ORDER ACCEPTED/SUBMITTED
2006-05-11, BUY EXPIRED
2006-06-01, BUY CREATE, 3611.85
2006-06-01, ORDER ACCEPTED/SUBMITTED
2006-06-01, ORDER ACCEPTED/SUBMITTED
2006-06-05, BUY EXECUTED, Price: 3611.85, Cost: 3611.85, Comm 0.00
2006-06-05, SELL CREATE, 3604.33
2006-06-05, ORDER ACCEPTED/SUBMITTED
2006-06-05, ORDER ACCEPTED/SUBMITTED
2006-06-06, SELL EXECUTED, Price: 3598.58, Cost: 3611.85, Comm 0.00
2006-06-21, BUY CREATE, 3491.57
2006-06-21, ORDER ACCEPTED/SUBMITTED
2006-06-21, ORDER ACCEPTED/SUBMITTED
2006-06-28, BUY EXPIRED
2006-07-24, BUY CREATE, 3596.60
2006-07-24, ORDER ACCEPTED/SUBMITTED
2006-07-24, ORDER ACCEPTED/SUBMITTED
2006-07-31, BUY EXPIRED
2006-09-12, BUY CREATE, 3751.07
2006-09-12, ORDER ACCEPTED/SUBMITTED
2006-09-12, ORDER ACCEPTED/SUBMITTED
2006-09-19, BUY EXPIRED
2006-09-20, BUY CREATE, 3802.90
2006-09-20, ORDER ACCEPTED/SUBMITTED
2006-09-20, ORDER ACCEPTED/SUBMITTED
2006-09-22, BUY EXECUTED, Price: 3802.90, Cost: 3802.90, Comm 0.00
2006-11-02, SELL CREATE, 3974.62
2006-11-02, ORDER ACCEPTED/SUBMITTED
2006-11-02, ORDER ACCEPTED/SUBMITTED
2006-11-03, SELL EXECUTED, Price: 3979.73, Cost: 3802.90, Comm 0.00
2006-11-06, BUY CREATE, 4004.77
2006-11-06, ORDER ACCEPTED/SUBMITTED
2006-11-06, ORDER ACCEPTED/SUBMITTED
2006-11-13, BUY EXPIRED
2006-12-11, BUY CREATE, 4012.36
2006-12-11, ORDER ACCEPTED/SUBMITTED
2006-12-11, ORDER ACCEPTED/SUBMITTED
2006-12-18, BUY EXPIRED最后应用新的观察者的策略代码见前。
7.Saving/Keeping the statistics
保存/保持统计信息到目前为止backtrader尚未实现任何机制来跟踪观察者的值并将其存储到文件中。最好的方法是
在策略的start方法中打开文件在策略的next方法中将值写入 考虑到DrawDown观察者可以做
class MyStrategy(bt.Strategy):def start(self):self.mystats open(mystats.csv, wb)self.mystats.write(datetime,drawdown, maxdrawdown\n)def next(self):self.mystats.write(self.data.datetime.date(0).strftime(%Y-%m-%d))self.mystats.write(,%.2f % self.stats.drawdown.drawdown[-1])self.mystats.write(,%.2f % self.stats.drawdown.maxdrawdown-1])self.mystats.write(\n)要保存索引0的值一旦处理完所有观察者可以将自定义观察者添加为系统中的最后一个观察者以将值保存到csv文件中。
注意Writer的功能可以自动化此任务。
