从零实现量化回测引擎：风险平价、动量策略对比

继承完善我们的引擎，昨天我们完成了引擎主体，就是一个account.py。

01 引擎框架

def run(self, algo_list):
    self.algo_list = algo_list
    for index, date in enumerate(self.dates):
        self.curr_date = date
        self.step(index, date)

def step(self, index, date):
    return_se = self._get_curr_return_se(date)
    self.acc.update_bar(date, return_se)
    self.algo_processor()

def algo_processor(self):
    context = {'engine': self, 'acc': self.acc}
    for algo in self.algo_list:
        if algo(context) is True:  # 如果algo返回True,直接不运行，本次不调仓
            return None

def get_results_df(self):
    df = pd.DataFrame({'date': self.acc.cache_dates, 'portfolio': self.acc.cache_portfolio_mv})
    df['rate'] = df['portfolio'].pct_change()
    df['equity'] = (df['rate'] + 1).cumprod()
    df.set_index('date', inplace=True)
    df.dropna(inplace=True)
    return df

回测的结果通过get_results_df返回回来，交给分析器。

02 分析器

我这个分析器天然就可以添加N个基准，quantstats只能添加一个。

class Analyzer:
    def __init__(self, df_results, benchmarks=['000300.SH']):
        self.df_results = df_results
        self.benchmarks = benchmarks

    def show_results(self):
        returns = self.df_results['rate']
        import empyrical

        print('累计收益：', round(empyrical.cum_returns_final(returns), 3))
        print('年化收益：', round(empyrical.annual_return(returns), 3))
        print('最大回撤：', round(empyrical.max_drawdown(returns), 3))
        print('夏普比', round(empyrical.sharpe_ratio(returns), 3))
        print('卡玛比', round(empyrical.calmar_ratio(returns), 3))
        print('omega', round(empyrical.omega_ratio(returns)), 3)

    def plot(self):
        returns = []
        for s in self.benchmarks:
            df_bench = DataUtils.load_returns([s])
            se = df_bench['return']
            se.name = s
            returns.append(se)

        se_port = self.df_results['rate']
        se_port.name = 'strategy'
        returns.append(se_port)
        all_returns = pd.concat(returns, axis=1)
        all_returns.dropna(inplace=True)
        all_equity = (1 + all_returns).cumprod()

        import matplotlib.pyplot as plt
        all_equity.plot()
        plt.show()

03 等权-买入并持有

symbols = ['N225', '000300.SH', 'ADX', '000905.SH', '399673.SZ', 'HSI', 'GDAXI']
from engine.algo.algos import *

e = Engine(symbols)

print('初始总市值', e.acc.get_total_mv())
e.run(algo_list=[
    RunOnce(),
    SelectAll(),
    WeightEqually()
])
print('最终总市值', e.acc.get_total_mv())
e.show_results(benckmarks=['000300.SH'])