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# 本代码由可视化策略环境自动生成 2018年6月13日 14:03
# 本代码单元只能在可视化模式下编辑。您也可以拷贝代码，粘贴到新建的代码单元或者策略，然后修改。


m1 = M.instruments.v2(
    start_date=T.live_run_param('trading_date', '2015-01-01'),
    end_date=T.live_run_param('trading_date', '2017-01-01'),
    market='CN_STOCK_A',
    instrument_list='600006.SHA',
    max_count=0
)

# 回测引擎：每日数据处理函数，每天执行一次
def m2_handle_data_bigquant_run(context, data):
    today=data.current_dt.strftime('%Y-%m-%d')
    # 长期均线值要有意义，需要在50根k线之后
    k = context.instruments[0] # 标的为字符串格式
    sid = context.symbol(k) # 将标的转化为equity格式
    # 获取价格数据
    prices = data.history(sid, 'price', 100, '1d')
    # 用Talib计算MACD取值，得到三个时间序列数组，分别为macd, signal 和 hist
    import talib
    macd, signal, hist = talib.MACD(np.array(prices), 12,26,9)
      
    # 计算现在portfolio中股票的仓位
    cur_position = context.portfolio.positions[sid].amount
    
    # 策略逻辑
    # 卖出逻辑 macd下穿signal
    if macd[-1] - signal[-1] < 0 and macd[-2] - signal[-2] > 0:
        # 进行清仓
        if cur_position > 0 and data.can_trade(sid):
            context.order_target_value(sid, 0)

    # 买入逻辑  macd上穿signal
    if macd[-1] - signal[-1] > 0 and macd[-2] - signal[-2] < 0:
        # 买入股票
        if cur_position == 0 and data.can_trade(sid):
            context.order_target_percent(sid, 1)
# 回测引擎：准备数据，只执行一次
def m2_prepare_bigquant_run(context):
    pass


# 回测引擎：初始化函数，只执行一次
def m2_initialize_bigquant_run(context):
    
    # 系统已经设置了默认的交易手续费和滑点，要修改手续费可使用如下函数
    context.set_commission(PerOrder(buy_cost=0.0003, sell_cost=0.0013, min_cost=5))

m2 = M.trade.v3(
    instruments=m1.data,
    start_date='',
    end_date='',
    handle_data=m2_handle_data_bigquant_run,
    prepare=m2_prepare_bigquant_run,
    initialize=m2_initialize_bigquant_run,
    volume_limit=0.025,
    order_price_field_buy='open',
    order_price_field_sell='close',
    capital_base=1000001,
    benchmark='000300.SHA',
    auto_cancel_non_tradable_orders=True,
    data_frequency='daily',
    price_type='后复权',
    plot_charts=True,
    backtest_only=False,
    amount_integer=False
)

[2018-06-01 11:21:32.292824] INFO: bigquant: instruments.v2 开始运行..
[2018-06-01 11:21:32.316112] INFO: bigquant: 命中缓存
[2018-06-01 11:21:32.329843] INFO: bigquant: instruments.v2 运行完成[0.037023s].
[2018-06-01 11:21:32.439486] INFO: bigquant: backtest.v7 开始运行..
[2018-06-01 11:21:32.985957] INFO: algo: set price type:backward_adjusted
[2018-06-01 11:21:45.715586] INFO: Performance: Simulated 488 trading days out of 488.
[2018-06-01 11:21:45.718789] INFO: Performance: first open: 2015-01-05 01:30:00+00:00
[2018-06-01 11:21:45.720188] INFO: Performance: last close: 2016-12-30 07:00:00+00:00

[2018-06-01 11:21:52.932024] INFO: bigquant: backtest.v7 运行完成[20.492981s].