python：ffn 方差分析

pip install ffn 是一个专门为从事量化金融工作的人们提供金融数据分析功能的py包

以每日基金净值数据为样本  fund_std.py 

# coding: utf-8
import os, sys
import pandas as pd
import ffn

if len(sys.argv) ==2:
    code = sys.argv[1]
else:
    print('usage: python fund_std.py fundcode ')
    sys.exit(1)

if len(code) !=6:
    print('stock code length: 6')
    sys.exit(2)
    
f1 = code +'.csv'
df = pd.read_csv(f1, index_col='date')
df.index = pd.to_datetime(df.index)

# 18.1.3  ffn  计算简单收益率  p252
return1 = ffn.to_returns(df.jz).dropna()
print(return1.tail())
print(" min = {0} , max = {1}".format(return1.min(), return1.max()))

# 18.5  方差 p266
print(" std = {0}".format(return1.std()))
#  18.5.2 下行风险 DownSide Deviation
print(" DownSide Deviation = {0}".format(return1.quantile(0.05)))
# 协方差矩阵法 p270
from scipy.stats import norm
pp = norm.ppf(0.05, return1.mean(), return1.std())
print(" norm.ppf = {0}".format(pp))

运行 python fund_std.py 006671

Name: jz, dtype: float64
 min = -0.06453904908520336 , max = 0.05495658811182125
 std = 0.014247097909503239
 DownSide Deviation = -0.01904123902653393
 norm.ppf = -0.021504358883276994

参考书：[ 量化投资以Python为工具 ]