本策略首先买入SHSE.600000股票10000股，随后根据60s的数据来计算MACD(12,26,9)线,并在MACD>0的时候买入100股,MACD<0的时候卖出100股
，但每日操作的股票数不超过原有仓位,并于收盘前把仓位调整至开盘前的仓位
回测数据为:SHSE.600000的60s数据
回测时间为:2017-09-01 08:00:00到2017-10-01 16:00:00
- # coding=utf-8
- from __future__ import print_function, absolute_import, unicode_literals
- try:
- import talib
- except:
- print('请安装TA-Lib库')
- from gm.api import *
- def init(context):
- # 设置标的股票
- context.symbol = 'SHSE.600000'
- # 用于判定第一个仓位是否成功开仓
- context.first = 0
- # 订阅浦发银行, bar频率为1min
- subscribe(symbols=context.symbol, frequency='60s', count=35)
- # 日内回转每次交易100股
- context.trade_n = 100
- # 获取昨今天的时间
- context.day = [0, 0]
- # 用于判断是否触发了回转逻辑的计时
- context.ending = 0
- def on_bar(context, bars):
- bar = bars[0]
- if context.first == 0:
- # 最开始配置仓位
- # 需要保持的总仓位
- context.total = 10000
- # 购买10000股浦发银行股票
- order_volume(symbol=context.symbol, volume=context.total, side=PositionSide_Long,
- order_type=OrderType_Market, position_effect=PositionEffect_Open)
- print(context.symbol, '以市价单开多仓10000股')
- context.first = 1.
- day = bar.bob.strftime('%Y-%m-%d')
- context.day[-1] = day[-2:]
- # 每天的仓位操作
- context.turnaround = [0, 0]
- return
- # 更新最新的日期
- day = bar.bob.strftime('%Y-%m-%d %H:%M:%S')
- context.day[0] = bar.bob.day
- # 若为新的一天,获取可用于回转的昨仓
- if context.day[0] != context.day[-1]:
- context.ending = 0
- context.turnaround = [0, 0]
- if context.ending == 1:
- return
- # 若有可用的昨仓则操作
- if context.total >= 0:
- # 获取时间序列数据
- symbol = bar['symbol']
- recent_data = context.data(symbol=symbol, frequency='60s', count=35, fields='close')
- # 计算MACD线
- macd = talib.MACD(recent_data['close'].values)[0][-1]
- # 根据MACD>0则开仓,小于0则平仓
- if macd > 0:
- # 多空单向操作都不能超过昨仓位,否则最后无法调回原仓位
- if context.turnaround[0] + context.trade_n < context.total:
- # 计算累计仓位
- context.turnaround[0] += context.trade_n
- order_volume(symbol=context.symbol, volume=context.trade_n, side=PositionSide_Long,
- order_type=OrderType_Market, position_effect=PositionEffect_Open)
- print(symbol, '市价单开多仓', context.trade_n, '股')
- elif macd < 0:
- if context.turnaround[1] + context.trade_n < context.total:
- context.turnaround[1] += context.trade_n
- order_volume(symbol=context.symbol, volume=context.trade_n, side=PositionSide_Short,
- order_type=OrderType_Market, position_effect=PositionEffect_Close)
- print(symbol, '市价单平多仓', context.trade_n, '股')
- # 临近收盘时若仓位数不等于昨仓则回转所有仓位
- if day[11:16] == '14:55' or day[11:16] == '14:57':
- position = context.account().position(symbol=context.symbol, side=PositionSide_Long)
- if position['volume'] != context.total:
- order_target_volume(symbol=context.symbol, volume=context.total, order_type=OrderType_Market,
- position_side=PositionSide_Long)
- print('市价单回转仓位操作...')
- context.ending = 1
- # 更新过去的日期数据
- context.day[-1] = context.day[0]
- if __name__ == '__main__':
- '''
- strategy_id策略ID,由系统生成
- filename文件名,请与本文件名保持一致
- mode实时模式:MODE_LIVE回测模式:MODE_BACKTEST
- token绑定计算机的ID,可在系统设置-密钥管理中生成
- backtest_start_time回测开始时间
- backtest_end_time回测结束时间
- backtest_adjust股票复权方式不复权:ADJUST_NONE前复权:ADJUST_PREV后复权:ADJUST_POST
- backtest_initial_cash回测初始资金
- backtest_commission_ratio回测佣金比例
- backtest_slippage_ratio回测滑点比例
- '''
- run(strategy_id='strategy_id',
- filename='main.py',
- mode=MODE_BACKTEST,
- token='token_id',
- backtest_start_time='2017-09-01 08:00:00',
- backtest_end_time='2017-10-01 16:00:00',
- backtest_adjust=ADJUST_PREV,
- backtest_initial_cash=2000000,
- backtest_commission_ratio=0.0001,
- backtest_slippage_ratio=0.0001)
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