海龟交易系统回测

import numpy as np
import pandas as pd
import talib  as ta
import datetime


start = '2015-01-01'                       # 回测起始时间
end = '2015-06-01'                         # 回测结束时间
universe = DynamicUniverse('A')        # 证券池，支持股票、基金、期货、指数四种资产
benchmark = 'HS300'                        # 策略参考标准
freq = 'd'                                 # 策略类型，'d'表示日间策略使用日线回测，'m'表示日内策略使用分钟线回测
refresh_rate = 1                          # 调仓频率，表示执行handle_data的时间间隔，若freq = 'd'时间间隔的单位为交易日，若freq = 'm'时间间隔为分钟
  
# 配置账户信息，支持多资产多账户
accounts = {
    'fantasy_account': AccountConfig(account_type='security', capital_base=10000000)
}


Max_position_per = 0.1
Max_history_window = 250
Max_time_range = 30
limit_unit = 4
atrlength = 20                   #计算真实波幅考虑的周期数
DC_range = 20                    #计算DC通道的周期
trade_percent = 0.01             #每次交易占比 基础值


record = pd.DataFrame({'symbol':[],'add_time':[],'last_buy_price':[] })




def initialize(context):
    pass


def handle_data(context):  
    timing_turtle(context)

def calcUnit(portfolio_value,ATR):
    value  = portfolio_value * trade_percent
    return int((value/ATR)/100)*100
    
def timing_turtle(context):
    global record
    account =  context.get_account('fantasy_account')
    current_universe = context.get_universe(exclude_halt=True)
    security_position = account.get_positions()
    history = context.history(current_universe,['closePrice','lowPrice','highPrice'],Max_time_range,rtype= 'array')
    cash = account.cash
    
    for sec in  current_universe:
        close = history[sec]['closePrice']
        low = history[sec]['lowPrice']
        high = history[sec]['highPrice']
        current_price = context.current_price(sec)
        #计算atr
        atr = ta.ATR(high,low,close,atrlength) [-1]
        #入场 突破唐奇安通道 上轨 买入一个UNIT
        if current_price>high[-DC_range:-1].max() and sec not in  security_position:
            unit = calcUnit(account.portfolio_value,atr)
            account.order_to(sec,unit)
            if len(record) !=0:
                record = record[record['symbol']!=sec]    #清空不符合要求记录
            record = record.append(pd.DataFrame({'symbol':[sec],'add_time':[1],'last_buy_price':[current_price] }))
            continue
            
        elif sec in security_position:
            last_price = float(record[record['symbol']==sec]['last_buy_price'])
            add_price = last_price +  0.5*atr
            add_unit = float(record[record['symbol']==sec]['add_time'])
            if current_price > add_price and add_unit  <limit_unit:
                unit = calcUnit(account.portfolio_value,atr)
                account.order_to(sec,unit)
                record.loc[record['symbol'] ==sec ,'add_time'] =record[record['symbol']==sec]['add_time']+1
                record.loc[record['symbol'] ==sec ,'last_buy_price'] =current_price
            
            elif current_price <low[-int(DC_range/2) :-1].min or current_price< (last_buy_price -2*atr):
                account.order_to(sec,0)
                record =  record[ record['symbol']!=sec]