def loop_back(code: str, begin: date, parameters: tuple) -> tuple:
mongo = Mongo()
dic = mongo.load_info(code)
name, typ = dic['name'], dic['type']
print(name, typ)
name = '{}({})'.format(name if len(name) <= 10 else name[: 8] + '..', code[4:])
if typ in ['指数型', 'QDII'] and parameters[1]: # as exp ≠ 0
dic = mongo.get_threshold(code[4:])
index, refer, thr = dic['_id'], dic['参考指标'], dic['低估']
parameters += (thr, refer)
print(parameters)
df = mongo.load_valuation([index])
df = df.rename({index: 'valuation'}, axis=1)
else:
df = mongo.load_close_price('sh000985') # use '中证全指' as valuation
df = df.rename({'close': 'valuation'}, axis=1)
df['date'] = pd.to_datetime(df['date'])
# print(df[(df['date'] > begin) & (df['date'].dt.dayofweek == 1)])
df2 = mongo.load_close_price(code)
# print(df2[(df2['date'] > begin) & (df2['date'].dt.dayofweek == 1)])
df = pd.merge(df, df2, on='date', how='outer')
df = df.sort_values('date')
df.fillna(method='ffill', inplace=True) # fill NaN with previous value
df.fillna({'close': 1.0}, inplace=True) # no previous value, fill with 1.0
weekday = 1 # choose Tuesday, Mon: 0, Tue: 1, ... Sun: 6
df = df[(df['date'] > begin) & (df['date'].dt.dayofweek == weekday)]
# print(df)
df['每期定投金额'] = df.apply(lambda x: increment(x, *parameters), axis=1)
df['累计定投金额'] = df['每期定投金额'].cumsum()
fee_rate = 0.001
df['每期持仓数量'] = df['每期定投金额'] / df['close'] * (1 - fee_rate)
df['累计持仓数量'] = df['每期持仓数量'].cumsum()
df['累计持仓净值'] = df['close'] * df['累计持仓数量']
df['现金流'] = - df['每期定投金额']
m = df.shape[0] # number of row
cumulative_amount = df.iloc[m - 1, df.columns.get_loc('累计定投金额')]
cumulative_net = df.iloc[m - 1, df.columns.get_loc('累计持仓净值')]
hold_gain = cumulative_net - cumulative_amount
df.iloc[m - 1, df.columns.get_loc('现金流')] += cumulative_net
return_rate = xirr(df, 'date', '现金流')
df = df.rename({'累计持仓净值': name}, axis=1).set_index('date')
df = df.sort_index()
df.index.name = None
# print(df)
return (name, cumulative_amount, cumulative_net, hold_gain, return_rate), df[['累计定投金额', name]]
def get_scale(code: str, mongo=None) -> tuple:
if not mongo:
mongo = Mongo()
name = mongo.load_info(code)['name']
scale = mongo.load_indicator(code)['total_tna']
return name, scale
