各个指标

1. 近N日收益率

近N日收益率 = (当日累计收益 - N日前的累计收益) / N日前的累计收益

2. 当周/月/年平均收益率

这里需要区分不同时间段的起始与终止区间

区间收益率 = (区间终值累计收益 - 区间初始累计收益) / 区间初始累计收益

示例代码

import pandas as pd
import numpy as np
from copy import deepcopydef fund_net_analyze(net_value_series, normalize_first_data=True):"""计算：近5日收益率,近20日收益率,近60日收益率,当年平均收益率，当月平均收益率,当周平均收益率:return:"""net_value_series = deepcopy(net_value_series)net_value_series.index = pd.to_datetime(net_value_series.index)net_value_series.sort_index(inplace=True)net_value_series.dropna(inplace=True)# 首日归一if normalize_first_data:net_value_series = net_value_series / net_value_series.iloc[0]collect_df = pd.DataFrame({"单位净值": net_value_series})# 开始计算历史滚动收益collect_df['近5日收益'] = (collect_df['单位净值'] - collect_df['单位净值'].shift(5)) / collect_df['单位净值'].shift(5)collect_df['近20日收益'] = (collect_df['单位净值'] - collect_df['单位净值'].shift(20)) / collect_df['单位净值'].shift(20)collect_df['近60日收益'] = (collect_df['单位净值'] - collect_df['单位净值'].shift(60)) / collect_df['单位净值'].shift(60)# 开始计算当年/月/周收益#  FutureWarning: weekofyear and week have been deprecated, please use DatetimeIndex.isocalendar().week instead,collect_df['__year'] = collect_df.index.isocalendar().year.astype(str)collect_df['__month'] = collect_df['__year'] + "_" + collect_df.index.month.astype(str)collect_df['__week'] = collect_df['__year'] + "_" + collect_df.index.isocalendar().week.astype(str)collect_df["当年平均收益率"] = collect_df.groupby("__year").apply(lambda v_df: (v_df['单位净值'] - v_df['单位净值'].iloc[0]) / v_df['单位净值'] / (v_df.index - v_df.index[0]).days).valuescollect_df["当月平均收益率"] = collect_df.groupby("__month").apply(lambda v_df: (v_df['单位净值'] - v_df['单位净值'].iloc[0]) / v_df['单位净值'] / (v_df.index - v_df.index[0]).days).valuescollect_df["当周平均收益率"] = collect_df.groupby("__week").apply(lambda v_df: (v_df['单位净值'] - v_df['单位净值'].iloc[0]) / v_df['单位净值'] / (v_df.index - v_df.index[0]).days).valuescollect_df.drop(["__year", "__month", "__week"], axis=1, inplace=True)return collect_dfdef main():# 生成数据_size = 500net_value = 1 + pd.Series(np.random.normal(0, 0.01, size=_size)).cumsum()net_value.index = pd.date_range("2024-01-01", periods=_size)# net_value为生成的净值数据# 计算各项指标collect_df = fund_net_analyze(net_value)collect_df.loc[:, "近5日收益":] = collect_df.loc[:, "近5日收益":].applymap(lambda x: format(x * 100, ".2f") + "%" if not pd.isna(x) else x)print(collect_df.tail())if __name__ == '__main__':main()