学习记录651@python之收益率与对数收益率案例实战

理论

代码

import tushare as ts
ts.set_token('你的token')
df=ts.get_k_data('399300', index=True,start='2016-01-01', end='2016-12-31')
df.head()

本接口即将停止更新，请尽快使用Pro版接口：https://tushare.pro/document/2

	date	open	close	high	low	volume	code
0	2016-01-04	3725.86	3470.41	3726.25	3469.01	115370674.0	sz399300
1	2016-01-05	3382.18	3478.78	3518.22	3377.28	162116984.0	sz399300
2	2016-01-06	3482.41	3539.81	3543.74	3468.47	145966144.0	sz399300
3	2016-01-07	3481.15	3294.38	3481.15	3284.74	44102641.0	sz399300
4	2016-01-08	3371.87	3361.56	3418.85	3237.93	185959451.0	sz399300

import numpy as np
# 基于价格的原始收益率
df['r']=(df['close'] - df['close'].shift(1)) / df['close'].shift(1)

# df['close'].shift(1) 下移一行
# 对数收益率定义为ln(e/s),其中e为下一期价格，s为上一期价格
df['rtn']=np.log(df['close'] / df['close'].shift(1))
df=df.dropna()
df.head()

	date	open	close	high	low	volume	code	r	rtn
1	2016-01-05	3382.18	3478.78	3518.22	3377.28	162116984.0	sz399300	0.002412	0.002409
2	2016-01-06	3482.41	3539.81	3543.74	3468.47	145966144.0	sz399300	0.017544	0.017391
3	2016-01-07	3481.15	3294.38	3481.15	3284.74	44102641.0	sz399300	-0.069334	-0.071855
4	2016-01-08	3371.87	3361.56	3418.85	3237.93	185959451.0	sz399300	0.020392	0.020187
5	2016-01-11	3303.12	3192.45	3342.48	3192.45	174638387.0	sz399300	-0.050307	-0.051617

df['close']-df['close'].shift(1).head()

1         NaN
2       61.03
3     -245.43
4       67.18
5     -169.11
        ...  
239       NaN
240       NaN
241       NaN
242       NaN
243       NaN
Name: close, Length: 243, dtype: float64

df.plot(figsize=(10,6),x='date',y='close') #价格曲线
df.plot(figsize=(10,6),x='date',y='r') #一般收益率
df.plot(figsize=(10,6),x='date',y='rtn') #对数收益率，平稳性更好

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