# coding=utf-8

from __future__ import print_function, absolute_import, unicode_literals

import numpy as np

import pandas as pd

from gm.api import *

'''

'''

def init(context):

context.symbol = 'SHFE.rb1801'

# 订阅SHFE.rb1801, bar频率为1min

subscribe(symbols=context.symbol, frequency='60s')

# 获取过去300个价格数据

timeseries = history_n(symbol=context.symbol, frequency='60s', count=300, fields='close', fill_missing='Last',

end_time='2017-07-01 08:00:00', df=True)['close'].values

# 获取网格区间分界线

context.band = np.mean(timeseries) + np.array([-40, -3, -2, 2, 3, 40]) * np.std(timeseries)

# 设置网格的仓位

context.weight = [0.5, 0.3, 0.0, 0.3, 0.5]

def on_bar(context, bars):

bar = bars[0]

# 根据价格落在(-40,-3],(-3,-2],(-2,2],(2,3],(3,40]的区间范围来获取最新收盘价所在的价格区间

grid = pd.cut([bar.close], context.band, labels=[0, 1, 2, 3, 4])[0]

# 获取多仓仓位

position_long = context.account().position(symbol=context.symbol, side=PositionSide_Long)

# 获取空仓仓位

position_short = context.account().position(symbol=context.symbol, side=PositionSide_Short)

# 若无仓位且价格突破则按照设置好的区间开仓

if not position_long and not position_short and grid != 2:

# 大于3为在中间网格的上方,做多

if grid >= 3:

order_target_percent(symbol=context.symbol, percent=context.weight[grid], order_type=OrderType_Market,

position_side=PositionSide_Long)

print(context.symbol, '以市价单开多仓到仓位', context.weight[grid])

if grid <= 1:

order_target_percent(symbol=context.symbol, percent=context.weight[grid], order_type=OrderType_Market,

position_side=PositionSide_Short)

print(context.symbol, '以市价单开空仓到仓位', context.weight[grid])

# 持有多仓的处理

elif position_long:

if grid >= 3:

order_target_percent(symbol=context.symbol, percent=context.weight[grid], order_type=OrderType_Market,

position_side=PositionSide_Long)

print(context.symbol, '以市价单调多仓到仓位', context.weight[grid])

# 等于2为在中间网格,平仓

elif grid == 2:

order_target_percent(symbol=context.symbol, percent=0, order_type=OrderType_Market,

position_side=PositionSide_Long)

print(context.symbol, '以市价单全平多仓')

# 小于1为在中间网格的下方,做空

elif grid <= 1:

order_target_percent(symbol=context.symbol, percent=0, order_type=OrderType_Market,

position_side=PositionSide_Long)

print(context.symbol, '以市价单全平多仓')

order_target_percent(symbol=context.symbol, percent=context.weight[grid], order_type=OrderType_Market,

position_side=PositionSide_Short)

print(context.symbol, '以市价单开空仓到仓位', context.weight[grid])

# 持有空仓的处理

elif position_short:

# 小于1为在中间网格的下方,做空

if grid <= 1:

order_target_percent(symbol=context.symbol, percent=context.weight[grid], order_type=OrderType_Market,

position_side=PositionSide_Short)

print(context.symbol, '以市价单调空仓到仓位', context.weight[grid])

# 等于2为在中间网格,平仓

elif grid == 2:

order_target_percent(symbol=context.symbol, percent=0, order_type=OrderType_Market,

position_side=PositionSide_Short)

print(context.symbol, '以市价单全平空仓')

# 大于3为在中间网格的上方,做多

elif grid >= 3:

order_target_percent(symbol=context.symbol, percent=0, order_type=OrderType_Market,

position_side=PositionSide_Short)

print(context.symbol, '以市价单全平空仓')

order_target_percent(symbol=context.symbol, percent=context.weight[grid], order_type=OrderType_Market,

position_side=PositionSide_Long)

print(context.symbol, '以市价单开多仓到仓位', context.weight[grid])

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='2017-07-01 08:00:00',

backtest_end_time='2017-10-01 16:00:00',

backtest_adjust=ADJUST_PREV,

backtest_initial_cash=10000000,

backtest_commission_ratio=0.0001,

backtest_slippage_ratio=0.0001)