In [ ]:

%matplotlib inline
import numpy as np
import pandas as pd 
import matplotlib.pyplot as plt

41.5績效畫圖比較¶

In [ ]:

#stock_data
df_1 = pd.read_csv('stock_data.csv')
df_1

Out[ ]:

	TIME	OPEN	MAX	MIN	CLOSE
0	2010-01-04	65.0	65.0	64.0	64.9
1	2010-01-05	65.0	65.1	63.9	64.5
2	2010-01-06	64.5	64.9	63.7	64.9
3	2010-01-07	64.9	65.0	64.2	64.2
4	2010-01-08	63.5	64.3	63.5	64.0
...	...	...	...	...	...
2949	2021-12-24	606.0	609.0	604.0	604.0
2950	2021-12-27	604.0	610.0	604.0	606.0
2951	2021-12-28	610.0	615.0	610.0	615.0
2952	2021-12-29	615.0	619.0	614.0	616.0
2953	2021-12-30	619.0	620.0	615.0	615.0

2954 rows × 5 columns

In [ ]:

#篩選出2021年度數據
df_1=df_1[df_1['TIME']>='2021-02-01']
df_1.reset_index(drop=True, inplace=True)
df_1

Out[ ]:

	TIME	OPEN	MAX	MIN	CLOSE
0	2021-02-01	595.0	612.0	587.0	611.0
1	2021-02-02	629.0	638.0	622.0	632.0
2	2021-02-03	638.0	642.0	630.0	630.0
3	2021-02-04	626.0	632.0	620.0	627.0
4	2021-02-05	638.0	641.0	631.0	632.0
...	...	...	...	...	...
219	2021-12-24	606.0	609.0	604.0	604.0
220	2021-12-27	604.0	610.0	604.0	606.0
221	2021-12-28	610.0	615.0	610.0	615.0
222	2021-12-29	615.0	619.0	614.0	616.0
223	2021-12-30	619.0	620.0	615.0	615.0

224 rows × 5 columns

In [ ]:

#計算stock_data日報酬
df_1['日報酬'] = ''
for i in range(1,len(df_1)):
  df_1['日報酬'][i] = df_1['CLOSE'][i]/df_1['CLOSE'][i-1]-1

df_1['1+日報酬'] = ''
for i in range(1,len(df_1)):
  df_1['1+日報酬'][i] = df_1['日報酬'][i]+1

df_1['相乘'] = ''
a = 1
for i in range(1,len(df_1)):  
  a *= df_1['1+日報酬'][i]
  df_1['相乘'][i] = a

/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  after removing the cwd from sys.path.
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:8: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:10: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  # Remove the CWD from sys.path while we load stuff.
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

In [ ]:

def time(df):
  df['TIME'] = pd.to_datetime(df['TIME'])
  df=df.set_index(df.TIME)
  return df

In [ ]:

df_1=time(df_1)

/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

In [ ]:

#相乘 累積報酬，畫圖畫出曲線變化
df_1

Out[ ]:

	TIME	OPEN	MAX	MIN	CLOSE	日報酬	1+日報酬	相乘
TIME
2021-02-01	2021-02-01	595.0	612.0	587.0	611.0
2021-02-02	2021-02-02	629.0	638.0	622.0	632.0	0.03437	1.03437	1.03437
2021-02-03	2021-02-03	638.0	642.0	630.0	630.0	-0.003165	0.996835	1.031097
2021-02-04	2021-02-04	626.0	632.0	620.0	627.0	-0.004762	0.995238	1.026187
2021-02-05	2021-02-05	638.0	641.0	631.0	632.0	0.007974	1.007974	1.03437
...	...	...	...	...	...	...	...	...
2021-12-24	2021-12-24	606.0	609.0	604.0	604.0	-0.0033	0.9967	0.988543
2021-12-27	2021-12-27	604.0	610.0	604.0	606.0	0.003311	1.003311	0.991817
2021-12-28	2021-12-28	610.0	615.0	610.0	615.0	0.014851	1.014851	1.006547
2021-12-29	2021-12-29	615.0	619.0	614.0	616.0	0.001626	1.001626	1.008183
2021-12-30	2021-12-30	619.0	620.0	615.0	615.0	-0.001623	0.998377	1.006547

224 rows × 8 columns

In [ ]:

#匯入RL訓練出來的結果
rl_1 =pd.read_csv('1.csv')
rl_1

Out[ ]:

	Unnamed: 0	state	action	reward	q
0	2710	OPEN MAX MIN CLOSE\nTIME ...	0	0.000000	0.000000
1	2711	OPEN MAX MIN CLOSE\nTIME ...	0	0.000000	0.000000
2	2712	OPEN MAX MIN CLOSE\nTIME ...	0	0.000000	0.000000
3	2713	OPEN MAX MIN CLOSE\nTIME ...	0	0.000000	0.000000
4	2714	OPEN MAX MIN CLOSE\nTIME ...	0	0.000000	0.000000
...	...	...	...	...	...
219	2929	OPEN MAX MIN CLOSE\nTIME ...	0	-0.003300	-0.003300
220	2930	OPEN MAX MIN CLOSE\nTIME ...	0	0.003311	0.003311
221	2931	OPEN MAX MIN CLOSE\nTIME ...	0	0.014851	0.014851
222	2932	OPEN MAX MIN CLOSE\nTIME ...	0	0.001626	0.001626
223	2933	OPEN MAX MIN CLOSE\nTIME ...	0	NaN	NaN

224 rows × 5 columns

In [ ]:

rl_2 = df_1.copy()
rl_2

Out[ ]:

	TIME	OPEN	MAX	MIN	CLOSE	日報酬	1+日報酬	相乘
TIME
2021-02-01	2021-02-01	595.0	612.0	587.0	611.0
2021-02-02	2021-02-02	629.0	638.0	622.0	632.0	0.03437	1.03437	1.03437
2021-02-03	2021-02-03	638.0	642.0	630.0	630.0	-0.003165	0.996835	1.031097
2021-02-04	2021-02-04	626.0	632.0	620.0	627.0	-0.004762	0.995238	1.026187
2021-02-05	2021-02-05	638.0	641.0	631.0	632.0	0.007974	1.007974	1.03437
...	...	...	...	...	...	...	...	...
2021-12-24	2021-12-24	606.0	609.0	604.0	604.0	-0.0033	0.9967	0.988543
2021-12-27	2021-12-27	604.0	610.0	604.0	606.0	0.003311	1.003311	0.991817
2021-12-28	2021-12-28	610.0	615.0	610.0	615.0	0.014851	1.014851	1.006547
2021-12-29	2021-12-29	615.0	619.0	614.0	616.0	0.001626	1.001626	1.008183
2021-12-30	2021-12-30	619.0	620.0	615.0	615.0	-0.001623	0.998377	1.006547

224 rows × 8 columns

In [ ]:

#計算stock_data日報酬
rl_2['rl_reward'] = ''

for i in range(224):
  rl_2['rl_reward'][i] = rl_1.reward[i]

/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:5: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  """

In [ ]:

rl_2

Out[ ]:

	TIME	OPEN	MAX	MIN	CLOSE	日報酬	1+日報酬	相乘	rl_reward
TIME
2021-02-01	2021-02-01	595.0	612.0	587.0	611.0				0.0
2021-02-02	2021-02-02	629.0	638.0	622.0	632.0	0.03437	1.03437	1.03437	0.0
2021-02-03	2021-02-03	638.0	642.0	630.0	630.0	-0.003165	0.996835	1.031097	0.0
2021-02-04	2021-02-04	626.0	632.0	620.0	627.0	-0.004762	0.995238	1.026187	0.0
2021-02-05	2021-02-05	638.0	641.0	631.0	632.0	0.007974	1.007974	1.03437	0.0
...	...	...	...	...	...	...	...	...	...
2021-12-24	2021-12-24	606.0	609.0	604.0	604.0	-0.0033	0.9967	0.988543	-0.0033
2021-12-27	2021-12-27	604.0	610.0	604.0	606.0	0.003311	1.003311	0.991817	0.003311
2021-12-28	2021-12-28	610.0	615.0	610.0	615.0	0.014851	1.014851	1.006547	0.014851
2021-12-29	2021-12-29	615.0	619.0	614.0	616.0	0.001626	1.001626	1.008183	0.001626
2021-12-30	2021-12-30	619.0	620.0	615.0	615.0	-0.001623	0.998377	1.006547	NaN

224 rows × 9 columns

In [ ]:

rl_2['1+rl日報酬'] = ''
for i in range(0,len(rl_2)):
  rl_2['1+rl日報酬'][i] = rl_2['rl_reward'][i]+1

rl_2['rl相乘'] = ''
a = 1
for i in range(0,len(rl_2)):  
  a *= rl_2['1+rl日報酬'][i]
  rl_2['rl相乘'][i] = a

/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:3: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  This is separate from the ipykernel package so we can avoid doing imports until
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  if __name__ == '__main__':

In [ ]:

rl_2

Out[ ]:

	TIME	OPEN	MAX	MIN	CLOSE	日報酬	1+日報酬	相乘	rl_reward	1+rl日報酬	rl相乘
TIME
2021-02-01	2021-02-01	595.0	612.0	587.0	611.0				0.0	1.0	1.0
2021-02-02	2021-02-02	629.0	638.0	622.0	632.0	0.03437	1.03437	1.03437	0.0	1.0	1.0
2021-02-03	2021-02-03	638.0	642.0	630.0	630.0	-0.003165	0.996835	1.031097	0.0	1.0	1.0
2021-02-04	2021-02-04	626.0	632.0	620.0	627.0	-0.004762	0.995238	1.026187	0.0	1.0	1.0
2021-02-05	2021-02-05	638.0	641.0	631.0	632.0	0.007974	1.007974	1.03437	0.0	1.0	1.0
...	...	...	...	...	...	...	...	...	...	...	...
2021-12-24	2021-12-24	606.0	609.0	604.0	604.0	-0.0033	0.9967	0.988543	-0.0033	0.9967	1.015126
2021-12-27	2021-12-27	604.0	610.0	604.0	606.0	0.003311	1.003311	0.991817	0.003311	1.003311	1.018487
2021-12-28	2021-12-28	610.0	615.0	610.0	615.0	0.014851	1.014851	1.006547	0.014851	1.014851	1.033613
2021-12-29	2021-12-29	615.0	619.0	614.0	616.0	0.001626	1.001626	1.008183	0.001626	1.001626	1.035294
2021-12-30	2021-12-30	619.0	620.0	615.0	615.0	-0.001623	0.998377	1.006547	NaN	NaN	NaN

224 rows × 11 columns

In [ ]:

import matplotlib.gridspec as gridspec

In [ ]:

#某列更換成數值類型_使用pd.to_numeric
df_1['相乘']=pd.to_numeric(df_1['相乘'])
rl_2['rl相乘']=pd.to_numeric(rl_2['rl相乘'])

In [ ]:

plt.figure(figsize = (10,6))
plt.title('', fontsize = 16)
df_1.相乘.plot(color = 'blue', linewidth = 1)
rl_2.rl相乘.plot(color = 'green', linewidth = 1)

plt.grid()
plt.xlabel('time', fontsize = 13) # X座標名稱
plt.ylabel('return(%)', fontsize = 14) # Y座標名稱
plt.legend(['buy&hold','RL_model'],  bbox_to_anchor=(1, 1));
plt.savefig('績效圖.png') # 儲存圖片;

In [ ]: