Dual power strategy

The dual-power strategy is a very well-known strategy in the futures field. Here we have transplanted this strategy to the stock field. Since stocks can only be long, we directly delete the strategy logic of short futures to get the dual-power strategy for stocks. The logic of the strategy is shown in the figure below:

There is the logic of shorting here. We delete it and use the logic of longing directly. The program code is as follows:

import talib

def initialize(context):
    # 初始化此策略
    # 设置我们要操作的股票池, 这里我们只操作一支股票
    g.security = '600570.SS'
    set_universe(g.security)
    g.K1 = 0.4
    g.K2 = 0.6
    g.buy = 0
    
#当五日均线高于十日均线时买入，当五日均线低于十日均线时卖出
def handle_data(context, data):
    security = g.security
    # 获取历史价格，最高价
    H = get_history(30, '1d', field = 'high', fq = 'pre')
    # 获取历史价格，最低价
    L = get_history(30, '1d', field = 'low', fq = 'pre')
    # 获取历史价格，收盘价
    C = get_history(30, '1d', field = 'close', fq = 'pre')
    # 获取历史价格，开盘价
    O = get_history(30, '1d', field = 'open', fq = 'pre')
    # 最高价最高价
    HH = H[security].max()
    # 收盘价最低价
    LC = C[security].min()
    # 收盘价最高价
    HC = C[security].max()
    # 最低价最低价
    LL = L[security].min()
    
    # 用于计算入场指标
    Range = max(HH - LC, HC - LL)
    
    # 计算移动平均线
    ma10 = talib.MA(C[security].values, 20)
    
    JX = ma10[-1]
    ZSX = min(ma10[-11:-1])
    
    amount = context.portfolio.positions[security]['amount']
    cash = context.portfolio.cash
    
    if H[security][-1] > (O[security][-1] + g.K1 * Range) and C[security][-1] > JX and amount == 0:
        # 全部的可用资金买入
        order_target_value(security, cash)
        # 记录买入价格
        g.buy = C[security][-1]
    if (L[security][-1] < (O[security][-1] - g.K2 * Range) and amount > 0) or (L[security][-1] > g.buy and L[security][-1] < ZSX):
        order_target(security, 0)
        g.buy = 0