模拟买卖信号

def caculate_max_drawdown(data, window=252):
    """
    计算最大回撤比
    :param data:
    :param window: int, 时间窗口设置，默认为252（日k）
    :return:
    """
    # 模拟持仓金额：投入的总金额 *（1+收益率）
    data['close'] = 10000 * (1 + data['cum_profit'])
    # 选取时间周期中的最大净值
    data['roll_max'] = data['close'].rolling(window=window, min_periods=1).max()
    # 计算当天的回撤比 = (谷值 — 峰值)/峰值 = 谷值/峰值 - 1
    data['daily_dd'] = data['close'] / data['roll_max'] - 1
    # 选取时间周期内最大的回撤比，即最大回撤
    data['max_dd'] = data['daily_dd'].rolling(window, min_periods=1).min()

    return data
    
def compose_signal(data):
    """
    整合信号
    :param data:
    :return:
    """
    data['buy_signal'] = np.where((data['buy_signal'] == 1)
                                  & (data['buy_signal'].shift(1) == 1), 0, data['buy_signal'])
    data['sell_signal'] = np.where((data['sell_signal'] == -1)
                                   & (data['sell_signal'].shift(1) == -1), 0, data['sell_signal'])
    data['signal'] = data['buy_signal'] + data['sell_signal']
    return data



def calculate_prof_pct(data):
    """
    计算单次收益率：开仓、平仓（开仓的全部股数）
    :param data:
    :return:
    """
    # 筛选信号不为0的，并且计算涨跌幅
    data.loc[data['signal'] != 0, 'profit_pct'] = data['close'].pct_change()
    data = data[data['signal'] == -1]  # 筛选平仓后的数据：单次收益
    return data
    
    
def week_period_strategy(code, time_freq, start_date, end_date):
    """
    周期选股（周四买，周一卖）
    :param code:
    :param time_freq:
    :param start_date:
    :param end_date:
    :return:
    """
    data = st.get_single_price(code, time_freq, start_date, end_date)
    # 新建周期字段
    data['weekday'] = data.index.weekday
    # 周四买入
    data['buy_signal'] = np.where((data['weekday'] == 3), 1, 0)
    # 周一卖出
    data['sell_signal'] = np.where((data['weekday'] == 0), -1, 0)

    data = base.compose_signal(data)  # 整合信号
    data = base.calculate_prof_pct(data)  # 计算收益
    # data = base.calculate_cum_prof(data)  # 计算累计收益率
    # data = base.caculate_max_drawdown(data)  # 最大回撤
    return data


if __name__ == '__main__':
    df = week_period_strategy('000001.XSHE', 'daily', None, datetime.date.today())
    print(df[['close', 'signal', 'profit_pct']])
    print(df[['close', 'signal', 'profit_pct']].describe())
    # df['profit_pct'].plot()
    # plt.hist(df['profit_pct'], bins=30)
    # plt.show()

    # 查看平安银行最大回撤
    # df = st.get_single_price('000001.XSHE', 'daily', '2006-01-01', '2021-01-01')
    # df = caculate_max_drawdown(df)
    # print(df[['close', 'roll_max', 'daily_dd', 'max_dd']])
    # df[['daily_dd', 'max_dd']].plot()
    # plt.show()

    # 计算夏普比率
    # df = st.get_single_price('000001.XSHE', 'daily', '2006-01-01', '2021-01-01')
    # sharpe = calculate_sharpe(df)
    # print(sharpe)