def equal_weighted_factor(self, factors_dict):
"""
将若干个因子等权重合成新因子
:param factors_dict: 若干因子组成的字典(dict),形式为:
{"factor_name_1":factor_1,"factor_name_2":factor_2}
每个因子值格式为一个MultiIndex Series，索引(index)为date(level 0)和asset(level 1),
包含一列factor值。
:return: MultiFactor 对象。包含三个属性：
"name"：合成的因子名称（str)
"multifactor_value":合成因子值（MultiIndex Series,索引(index)为date(level 0)和asset(level 1),
包含一列factor值)
"weight": 加权方式 (str)
"""
from fxdayu_alphaman.factor.utility import MultiFactor
# 因子累加
gather_result = self.combine_factor(list(factors_dict.values()))
multifactor_name = "+".join(list(factors_dict.keys()))
multifactor = MultiFactor()
multifactor["name"] = multifactor_name
multifactor["multifactor_value"] = gather_result
multifactor["weight"] = "equal_weight"
return multifactor
def ic_shrink_cov_weighted_factor(self, factors_dict, ic_weight_shrink_df):
"""
根据 Ledoit-Wolf 压缩的协方差矩阵估算方法得到的因子权重,将若干个因子按该权重加权合成新因子
:param factors_dict: 若干因子组成的字典(dict),形式为:
{"factor_name_1":factor_1,"factor_name_2":factor_2}
每个因子值格式为一个MultiIndex Series，索引(index)为date(level 0)和asset(level 1),
包含一列factor值。
:param ic_weight_shrink_df: 使用Ledoit-Wolf 压缩的协方差矩阵估算方法得到的因子权重(pd.Dataframe),
可通过Admin.get_ic_weight_shrink_df 获取。
索引（index)为datetime,columns为待合成的因子名称，与factors_dict一致。
:return: MultiFactor 对象。包含三个属性：
"name"：合成的因子名称（str)
"multifactor_value":合成因子值（MultiIndex Series,索引(index)为date(level 0)和asset(level 1),
包含一列factor值)
"weight": 加权方式 (str)
"""
from fxdayu_alphaman.factor.utility import MultiFactor
weight = ic_weight_shrink_df
weighted_factor_value_list = []
for factor_name in factors_dict.keys():
original_factor = factors_dict[factor_name]
w = pd.DataFrame(
weight[factor_name].loc[original_factor.index.get_level_values(
level=0)])
weighted_factor = pd.DataFrame(original_factor)
weighted_factor.columns = [
"factor",
]
w.columns = [
"factor",
]
w.index = weighted_factor.index
weighted_factor = weighted_factor * w
weighted_factor_value_list.append(weighted_factor)
# 因子累加
gather_result = self.combine_factor(weighted_factor_value_list)
multifactor_name = "+".join(list(factors_dict.keys()))
multifactor = MultiFactor()
multifactor["name"] = multifactor_name
multifactor["multifactor_value"] = gather_result
multifactor["weight"] = " ic_shrink_cov_weight"
return multifactor