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if statement in for loop with pandas dataframes

Time:08-21

I am making a Dollar Cost Average code where I want to choose between 2 equations. I made an excel spreadsheet that I'm trying to portover to python. I've gotten pretty far except for the last step. The last step has had me searching for a solution for 3 weeks now. The errors happen when I try a for loop in a df when looping through. I would like to check a column with an if the statement. If is true then do an equation if false do another equation. I can get the for loop to work and I can the if statements to work, but not combined. See all commented out code for whats been tried. I have tried np.where instead of the if statements as well. I have tried .loc. I have tried lamda. I have tried list comp. Nothing is working please help. FYI the code referring is ['trend bal'] column. ***see end with correct code.

What the df looks like:

    Index   timestamp         Open         High          Low  ...      rate  account bal  invested ST_10_1.0  if trend
0       0   8/16/2021  4382.439941  4444.350098  4367.729980  ...  1.000000  $10,000.00      10000         1         0
1       1   8/23/2021  4450.290039  4513.330078  4450.290039  ...  0.015242  $10,252.42      10100         1         0
2       2   8/30/2021  4513.759766  4545.850098  4513.759766  ...  0.005779  $10,411.67      10200         1         0
3       3    9/6/2021  4535.379883  4535.379883  4457.660156  ... -0.016944  $10,335.25      10300         1         0
4       4   9/13/2021  4474.810059  4492.990234  4427.759766  ... -0.005739  $10,375.93      10400         1         0
5       5   9/20/2021  4402.950195  4465.399902  4305.910156  ...  0.005073  $10,528.57      10500         1         0
6       6   9/27/2021  4442.120117  4457.299805  4288.520020  ... -0.022094  $10,395.95      10600         1         0
7       7   10/4/2021  4348.839844  4429.970215  4278.939941  ...  0.007872  $10,577.79      10700         1         0
8       8  10/11/2021  4385.439941  4475.819824  4329.919922  ...  0.018225  $10,870.57      10800         1         0
9       9  10/18/2021  4463.720215  4559.669922  4447.470215  ...  0.016445  $11,149.33      10900         1         0
10     10  10/25/2021  4553.689941  4608.080078  4537.359863  ...  0.013307  $11,397.70      11000         1         0
11     11   11/1/2021  4610.620117  4718.500000  4595.060059  ...  0.020009  $11,725.75      11100         1         0
12     12   11/8/2021  4701.479980  4714.919922  4630.859863  ... -0.003125  $11,789.11      11200         1         0
13     13  11/15/2021  4689.299805  4717.750000  4672.779785  ...  0.003227  $11,927.15      11300         1         0
14     14  11/22/2021  4712.000000  4743.830078  4585.430176  ... -0.021997  $11,764.79      11400         1         0
15     15  11/29/2021  4628.750000  4672.950195  4495.120117  ... -0.012230  $11,720.92      11500        -1       100
16     16   12/6/2021  4548.370117  4713.569824  4540.509766  ...  0.038249  $12,269.23      11600        -1       100
17     17  12/13/2021  4710.299805  4731.990234  4600.220215  ... -0.019393  $12,131.29      11700         1         0
18     18  12/20/2021  4587.899902  4740.740234  4531.100098  ...  0.022757  $12,507.36      11800         1         0
19     19  12/27/2021  4733.990234  4808.930176  4733.990234  ...  0.008547  $12,714.25      11900         1         0
20     20    1/3/2022  4778.140137  4818.620117  4662.740234  ... -0.018705  $12,576.44      12000         1         0
21     21   1/10/2022  4655.339844  4748.830078  4582.240234  ... -0.003032  $12,638.31      12100         1         0
22     22   1/17/2022  4632.240234  4632.240234  4395.339844  ... -0.056813  $12,020.29      12200         1         0
23     23   1/24/2022  4356.319824  4453.229980  4222.620117  ...  0.007710  $12,212.97      12300        -1       100
24     24   1/31/2022  4431.790039  4595.310059  4414.020020  ...  0.015497  $12,502.23      12400        -1       100
25     25    2/7/2022  4505.750000  4590.029785  4401.410156  ... -0.018196  $12,374.75      12500         1         0
26     26   2/14/2022  4412.609863  4489.549805  4327.220215  ... -0.015790  $12,279.35      12600         1         0
27     27   2/21/2022  4332.740234  4385.339844  4114.649902  ...  0.008227  $12,480.38      12700         1         0
28     28   2/28/2022  4354.169922  4416.779785  4279.540039  ... -0.012722  $12,421.61      12800         1         0
29     29    3/7/2022  4327.009766  4327.009766  4157.870117  ... -0.028774  $12,164.19      12900        -1       100
30     30   3/14/2022  4202.750000  4465.399902  4161.720215  ...  0.061558  $13,012.99      13000        -1       100
31     31   3/21/2022  4462.399902  4546.029785  4424.299805  ...  0.017911  $13,346.07      13100         1         0
32     32   3/28/2022  4541.089844  4637.299805  4507.569824  ...  0.000616  $13,454.30      13200         1         0
33     33    4/4/2022  4547.970215  4593.450195  4450.040039  ... -0.012666  $13,383.88      13300         1         0
34     34   4/11/2022  4462.640137  4471.000000  4381.339844  ... -0.021320  $13,198.53      13400         1         0
35     35   4/18/2022  4385.629883  4512.939941  4267.620117  ... -0.027503  $12,935.53      13500        -1       100
36     36   4/25/2022  4255.339844  4308.450195  4124.279785  ... -0.032738  $12,612.05      13600        -1       100
37     37    5/2/2022  4130.609863  4307.660156  4062.510010  ... -0.002079  $12,685.83      13700        -1       100
38     38    5/9/2022  4081.270020  4081.270020  3858.870117  ... -0.024119  $12,479.86      13800        -1       100
39     39   5/16/2022  4013.020020  4090.719971  3810.320068  ... -0.030451  $12,199.84      13900        -1       100
40     40   5/23/2022  3919.419922  4158.490234  3875.129883  ...  0.065844  $13,103.12      14000        -1       100
41     41   5/30/2022  4151.089844  4177.509766  4073.850098  ... -0.011952  $13,046.51      14100         1         0
42     42    6/6/2022  4134.720215  4168.779785  3900.159912  ... -0.050548  $12,487.03      14200         1         0
43     43   6/13/2022  3838.149902  3838.149902  3636.870117  ... -0.057941  $11,863.52      14300        -1       100
44     44   6/20/2022  3715.310059  3913.649902  3715.310059  ...  0.064465  $12,728.31      14400        -1       100
45     45   6/27/2022  3920.760010  3945.860107  3738.669922  ... -0.022090  $12,547.14      14500        -1       100
46     46    7/4/2022  3792.610107  3918.500000  3742.060059  ...  0.019358  $12,890.03      14600        -1       100
47     47   7/11/2022  3880.939941  3880.939941  3721.560059  ... -0.009289  $12,870.29      14700        -1       100
48     48   7/18/2022  3883.790039  4012.439941  3818.629883  ...  0.025489  $13,298.35      14800        -1       100
49     49   7/25/2022  3965.719971  4140.149902  3910.739990  ...  0.042573  $13,964.51      14900         1         0
50     50    8/1/2022  4112.379883  4167.660156  4079.810059  ...  0.003607  $14,114.88      15000         1         0
51     51    8/8/2022  4155.930176  4280.470215  4112.089844  ...  0.032558  $14,674.44      15100         1         0
52     52   8/15/2022  4269.370117  4325.279785  4253.080078  ...  0.000839  $14,786.75      15200         1         0
53     53   8/19/2022  4266.310059  4266.310059  4218.700195  ... -0.012900  $14,696.00      15300         1         0

   

What it should look like:

    Index   timestamp         Open         High          Low  ...   account bal  invested  ST_10_1.0 if trend     trend bal
0       0   8/16/2021  4382.439941  4444.350098  4367.729980  ...   $10,000.00      10000          1        0   $10,000.00        
1       1   8/23/2021  4450.290039  4513.330078  4450.290039  ...   $10,252.42      10100          1        0   $10,252.42        
2       2   8/30/2021  4513.759766  4545.850098  4513.759766  ...   $10,411.67      10200          1        0   $10,411.67        
3       3    9/6/2021  4535.379883  4535.379883  4457.660156  ...   $10,335.25      10300          1        0   $10,335.25        
4       4   9/13/2021  4474.810059  4492.990234  4427.759766  ...   $10,375.93      10400          1        0   $10,375.93        
5       5   9/20/2021  4402.950195  4465.399902  4305.910156  ...   $10,528.57      10500          1        0   $10,528.57        
6       6   9/27/2021  4442.120117  4457.299805  4288.520020  ...   $10,395.95      10600          1        0   $10,395.95        
7       7   10/4/2021  4348.839844  4429.970215  4278.939941  ...   $10,577.79      10700          1        0   $10,577.79        
8       8  10/11/2021  4385.439941  4475.819824  4329.919922  ...   $10,870.57      10800          1        0   $10,870.57        
9       9  10/18/2021  4463.720215  4559.669922  4447.470215  ...   $11,149.33      10900          1        0   $11,149.33        
10     10  10/25/2021  4553.689941  4608.080078  4537.359863  ...   $11,397.70      11000          1        0   $11,397.70        
11     11   11/1/2021  4610.620117  4718.500000  4595.060059  ...   $11,725.75      11100          1        0   $11,725.75        
12     12   11/8/2021  4701.479980  4714.919922  4630.859863  ...   $11,789.11      11200          1        0   $11,789.11        
13     13  11/15/2021  4689.299805  4717.750000  4672.779785  ...   $11,927.15      11300          1        0   $11,927.15        
14     14  11/22/2021  4712.000000  4743.830078  4585.430176  ...   $11,764.79      11400          1        0   $11,764.79        
15     15  11/29/2021  4628.750000  4672.950195  4495.120117  ...   $11,720.92      11500         -1      100   $11,720.92        
16     16   12/6/2021  4548.370117  4713.569824  4540.509766  ...   $12,269.23      11600         -1      100   $11,820.92        
17     17  12/13/2021  4710.299805  4731.990234  4600.220215  ...   $12,131.29      11700          1        0   $11,920.92        
18     18  12/20/2021  4587.899902  4740.740234  4531.100098  ...   $12,507.36      11800          1        0   $12,292.19        
19     19  12/27/2021  4733.990234  4808.930176  4733.990234  ...   $12,714.25      11900          1        0   $12,497.25        
20     20    1/3/2022  4778.140137  4818.620117  4662.740234  ...   $12,576.44      12000          1        0   $12,363.49        
21     21   1/10/2022  4655.339844  4748.830078  4582.240234  ...   $12,638.31      12100          1        0   $12,426.01        
22     22   1/17/2022  4632.240234  4632.240234  4395.339844  ...   $12,020.29      12200          1        0   $11,820.05        
23     23   1/24/2022  4356.319824  4453.229980  4222.620117  ...   $12,212.97      12300         -1      100   $12,011.19        
24     24   1/31/2022  4431.790039  4595.310059  4414.020020  ...   $12,502.23      12400         -1      100   $12,111.19        
25     25    2/7/2022  4505.750000  4590.029785  4401.410156  ...   $12,374.75      12500          1        0   $12,211.19        
26     26   2/14/2022  4412.609863  4489.549805  4327.220215  ...   $12,279.35      12600          1        0   $12,118.38        
27     27   2/21/2022  4332.740234  4385.339844  4114.649902  ...   $12,480.38      12700          1        0   $12,318.08        
28     28   2/28/2022  4354.169922  4416.779785  4279.540039  ...   $12,421.61      12800          1        0   $12,261.37        
29     29    3/7/2022  4327.009766  4327.009766  4157.870117  ...   $12,164.19      12900         -1      100   $12,008.56        
30     30   3/14/2022  4202.750000  4465.399902  4161.720215  ...   $13,012.99      13000         -1      100   $12,108.56        
31     31   3/21/2022  4462.399902  4546.029785  4424.299805  ...   $13,346.07      13100          1        0   $12,208.56        
32     32   3/28/2022  4541.089844  4637.299805  4507.569824  ...   $13,454.30      13200          1        0   $12,316.09        
33     33    4/4/2022  4547.970215  4593.450195  4450.040039  ...   $13,383.88      13300          1        0   $12,260.08        
34     34   4/11/2022  4462.640137  4471.000000  4381.339844  ...   $13,198.53      13400          1        0   $12,098.70        
35     35   4/18/2022  4385.629883  4512.939941  4267.620117  ...   $12,935.53      13500         -1      100   $11,865.95        
36     36   4/25/2022  4255.339844  4308.450195  4124.279785  ...   $12,612.05      13600         -1      100   $11,965.95        
37     37    5/2/2022  4130.609863  4307.660156  4062.510010  ...   $12,685.83      13700         -1      100   $12,065.95        
38     38    5/9/2022  4081.270020  4081.270020  3858.870117  ...   $12,479.86      13800         -1      100   $12,165.95        
39     39   5/16/2022  4013.020020  4090.719971  3810.320068  ...   $12,199.84      13900         -1      100   $12,265.95        
40     40   5/23/2022  3919.419922  4158.490234  3875.129883  ...   $13,103.12      14000         -1      100   $12,365.95        
41     41   5/30/2022  4151.089844  4177.509766  4073.850098  ...   $13,046.51      14100          1        0   $12,465.95        
42     42    6/6/2022  4134.720215  4168.779785  3900.159912  ...   $12,487.03      14200          1        0   $11,935.81        
43     43   6/13/2022  3838.149902  3838.149902  3636.870117  ...   $11,863.52      14300         -1      100   $11,344.24        
44     44   6/20/2022  3715.310059  3913.649902  3715.310059  ...   $12,728.31      14400         -1      100   $11,444.24        
45     45   6/27/2022  3920.760010  3945.860107  3738.669922  ...   $12,547.14      14500         -1      100   $11,544.24        
46     46    7/4/2022  3792.610107  3918.500000  3742.060059  ...   $12,890.03      14600         -1      100   $11,644.24        
47     47   7/11/2022  3880.939941  3880.939941  3721.560059  ...   $12,870.29      14700         -1      100   $11,744.24        
48     48   7/18/2022  3883.790039  4012.439941  3818.629883  ...   $13,298.35      14800         -1      100   $11,844.24        
49     49   7/25/2022  3965.719971  4140.149902  3910.739990  ...   $13,964.51      14900          1        0   $11,944.24        
50     50    8/1/2022  4112.379883  4167.660156  4079.810059  ...   $14,114.88      15000          1        0   $12,087.33        
51     51    8/8/2022  4155.930176  4280.470215  4112.089844  ...   $14,674.44      15100          1        0   $12,580.87        
52     52   8/15/2022  4269.370117  4325.279785  4253.080078  ...   $14,786.75      15200          1        0   $12,691.42        
53     53   8/19/2022  4266.310059  4266.310059  4218.700195  ...   $14,696.00      15300          1        0   $12,627.70        

Python Code:

from ctypes.wintypes import VARIANT_BOOL
from xml.dom.expatbuilder import FilterVisibilityController
import ccxt
from matplotlib import pyplot as plt
import config
import schedule
import pandas as pd
import pandas_ta as ta
pd.set_option('display.max_rows', None)
#pd.set_option('display.max_columns', None)

import warnings
warnings.filterwarnings('ignore')

import numpy as np
from datetime import datetime
import time

import yfinance as yf

ticker = yf.Ticker('^GSPC')

df = ticker.history(period="1y", interval="1wk")
df.reset_index(inplace=True)
df.rename(columns = {'Date':'timestamp'}, inplace = True)
#df.drop(columns ={'Open', 'High', 'Low', 'Volume'}, inplace=True, axis=1)
df.drop(columns ={'Dividends', 'Stock Splits'}, inplace=True, axis=1)
# df['Close'].ffill(axis = 0, inplace = True)

invest = 10000
weekly = 100

fee = .15/100
fees = 1-fee 

df.loc[df.index == 0, 'rate'] = 1
df.loc[df.index > 0, 'rate'] = (df['Close'] / df['Close'].shift(1))-1

df.loc[df.index == 0, 'account bal'] = invest
for i in range(1, len(df)):
    df.loc[i, 'account bal'] = (df.loc[i-1, 'account bal'] * (1   df.loc[i, 'rate']))   weekly

df['invested'] = (df.index*weekly) invest
    
#Supertrend
ATR = 10
Mult = 1.0

ST = ta.supertrend(df['High'], df['Low'], df['Close'], ATR, Mult)
df[f'ST_{ATR}_{Mult}'] = ST[f'SUPERTd_{ATR}_{Mult}']

df[f'ST_{ATR}_{Mult}'] = df[f'ST_{ATR}_{Mult}'].shift(1).fillna(1)

df.loc[df[f'ST_{ATR}_{Mult}'] == 1, 'if trend'] = 0
df.loc[df[f'ST_{ATR}_{Mult}'] == -1, 'if trend'] = weekly


# df.loc[df.index == 0, 'trend bal'] = invest
# for i in range(1, len(df)):
#     np.where(df.loc[df[f'ST_{ATR}_{Mult}'] == 1, 'trend bal'], (df.loc[i-1, 'trend bal'] * (1   df.loc[i, 'rate']))   weekly, df.loc[i-i, 'trend bal']   df['if trend'])



# df.loc[df.index == 0, 'trend bal'] = invest
# for i in range(1, len(df)):
#     if df[f'ST_{ATR}_{Mult}'] == 1:
#         df.loc[i, 'trend bal'] = (df.loc[i-1, 'trend bal'] * (1   df.loc[i, 'rate']))   weekly
#     else:
#         df.loc[i, 'trend bal'] = df.loc[i-i, 'trend bal']   df['if trend']


# for i in range(1, len(df)):
#     df.loc[df[f'ST_{ATR}_{Mult}'].shift(1) == 1, 'trend bal'] = (df.loc[i-1, 'trend bal'] * (1   df.loc[i, 'rate']))   weekly
#     df.loc[df[f'ST_{ATR}_{Mult}'].shift(1) == -1, 'trend bal'] = df.loc[i-i, 'trend bal']   df['if trend'] 


#df.to_csv('GSPC.csv',index=False,mode='a')

# plt.plot(df['timestamp'], df['account bal'])
# plt.plot(df['timestamp'], df['invested'])
# plt.plot(df['timestamp'], df['close'])
# plt.show()
print(df)

What some errors looks like:

    np.where(df.loc[df[f'ST_{ATR}_{Mult}'] == 1, 'trend bal'], (df.loc[i-1, 'trend bal'] * (1   df.loc[i, 'rate']))   weekly, df.loc[i-i, 'trend bal']   df['if trend'])
  File "<__array_function__ internals>", line 180, in where
ValueError: operands could not be broadcast together with shapes (36,) () (54,)

Another error:

line 1535, in __nonzero__
    raise ValueError(
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

No error but not the correct amounts:

df['trend bal'] = 0
for i in range(1, len(df)):
    df.loc[df[f'ST_{ATR}_{Mult}'].shift(1) == 1, 'trend bal'] = (df.loc[i-1, 'trend bal'] * (1   df.loc[i, 'rate']))   weekly
    df.loc[df[f'ST_{ATR}_{Mult}'].shift(1) == -1, 'trend bal'] = df.loc[i-i, 'trend bal']   df['if trend'] 

See photo of screenshot of excel formula: excel spreadsheet

*** Made correct calculations thanks to Ingwersen_erik:

from re import X
import pandas as pd
import pandas_ta as ta
import numpy as np
pd.set_option('display.max_rows', None)

df = pd.read_csv('etcusd.csv')


invest = 10000
weekly = 100

fee = .15/100
fees = 1-fee 

df.loc[df.index == 0, 'rate'] = 1
df.loc[df.index > 0, 'rate'] = (df['Close'] / df['Close'].shift(1))-1

df.loc[df.index == 0, 'account bal'] = invest
for i in range(1, len(df)):
    df.loc[i, 'account bal'] = (df.loc[i-1, 'account bal'] * (1   df.loc[i, 'rate']))   weekly

df['invested'] = (df.index*weekly) invest

MDD = ((df['account bal']-df['account bal'].max()) / df['account bal'].max()).min()

#Supertrend
ATR = 10
Mult = 1.0

ST = ta.supertrend(df['High'], df['Low'], df['Close'], ATR, Mult)
df[f'ST_{ATR}_{Mult}'] = ST[f'SUPERTd_{ATR}_{Mult}']

df[f'ST_{ATR}_{Mult}'] = df[f'ST_{ATR}_{Mult}'].shift(1).fillna(1)

df.loc[df.index == 0, "trend bal"] = invest

for index, row in df.iloc[1:].iterrows():
    row['trend bal'] = np.where(
        df.loc[index - 1, f'ST_{ATR}_{Mult}'] == 1,
        (df.loc[index - 1, 'trend bal'] * (1   row['rate']))   weekly,
        df.loc[index - 1, 'trend bal']   weekly,
    )
    df.loc[df.index == index, 'trend bal'] = row['trend bal']

print(df)

CodePudding user response:

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import time
import ccxt
import warnings
import pandas as pd
import pandas_ta as ta
import yfinance as yf
import numpy as np
import matplotlib.pyplot as plt
from datetime import datetime
from ctypes.wintypes import VARIANT_BOOL
from xml.dom.expatbuilder import FilterVisibilityController


warnings.filterwarnings("ignore")
pd.set_option("display.max_rows", None)
pd.set_option("display.max_columns", None)

invest = 10_000
weekly = 100
fee = 0.15 / 100
fees = 1 - fee
ATR = 10
Mult = 1.0

ticker = yf.Ticker("^GSPC")
df = (
    ticker.history(period="1y", interval="1wk")
    .reset_index()
    .rename(columns={"Date": "timestamp"})
    .drop(columns={"Dividends", "Stock Splits"}, errors="ignore")
)
df.loc[df.index == 0, "rate"] = 1
df.loc[df.index > 0, "rate"] = (df["Close"] / df["Close"].shift(1)) - 1
df.loc[df.index == 0, "account bal"] = invest

df.loc[df.index == 0, "account bal"] = invest

for i in range(1, len(df)):
    df.loc[i, "account bal"] = (
        df.loc[i - 1, "account bal"] * (1   df.loc[i, "rate"])
    )   weekly


df["invested"] = (df.index * weekly)   invest

# Super-trend
ST = ta.supertrend(df["High"], df["Low"], df["Close"], ATR, Mult)
df[f"ST_{ATR}_{Mult}"] = ST[f"SUPERTd_{ATR}_{Mult}"]
df[f"ST_{ATR}_{Mult}"] = df[f"ST_{ATR}_{Mult}"].shift(1).fillna(1)
df.loc[df[f"ST_{ATR}_{Mult}"] == 1, "if trend"] = 0
df.loc[df[f"ST_{ATR}_{Mult}"] == -1, "if trend"] = weekly

df.loc[df.index == 0, "trend bal"] = invest

# === Potential correction to the np.where ==============================
for index, row in df.iloc[1:].iterrows():
    row["trend bal"] = np.where(
        row[f"ST_{ATR}_{Mult}"] == 1,
        (df.loc[index - 1, "trend bal"] * (1   row["rate"]))   weekly,
        df.loc[index - 1, "trend bal"]   row["if trend"],
    )
    # NOTE: The original "otherwise" clause from `np.where` had the
    #       following value: `df.loc[index - index, "trend bal"]   ...`
    #       I assumed you meant `index -1`, instead of `index - index`,
    #       therefore the above code uses `index -1`. If you really meant
    #       `index - index`, please change the code accordingly.

    df.loc[df.index == index, "trend bal"] = row["trend bal"]

df

Result:

timestamp Open High Low Close Volume rate account bal invested ST_10_1.0 if trend trend bal
2021-08-16 4382.44 4444.35 4367.73 4441.67 5988610000 1 10000 10000 1 0 10000
2021-08-23 4450.29 4513.33 4450.29 4509.37 14124930000 0.0152421 10252.4 10100 1 0 10252.4
2021-08-30 4513.76 4545.85 4513.76 4535.43 14256180000 0.00577909 10411.7 10200 1 0 10411.7
2021-09-06 4535.38 4535.38 4457.66 4458.58 11793790000 -0.0169444 10335.3 10300 1 0 10335.3
2021-09-13 4474.81 4492.99 4427.76 4432.99 17763120000 -0.00573946 10375.9 10400 1 0 10375.9
2021-09-20 4402.95 4465.4 4305.91 4455.48 15697030000 0.00507327 10528.6 10500 1 0 10528.6
2021-09-27 4442.12 4457.3 4288.52 4357.04 15555390000 -0.0220941 10396 10600 1 0 10396
2021-10-04 4348.84 4429.97 4278.94 4391.34 14795520000 0.00787227 10577.8 10700 1 0 10577.8
2021-10-11 4385.44 4475.82 4329.92 4471.37 13758090000 0.0182246 10870.6 10800 1 0 10870.6
2021-10-18 4463.72 4559.67 4447.47 4544.9 13966070000 0.0164446 11149.3 10900 1 0 11149.3
2021-10-25 4553.69 4608.08 4537.36 4605.38 16206040000 0.0133072 11397.7 11000 1 0 11397.7
2021-11-01 4610.62 4718.5 4595.06 4697.53 16397220000 0.0200092 11725.8 11100 1 0 11725.8
2021-11-08 4701.48 4714.92 4630.86 4682.85 15646510000 -0.00312498 11789.1 11200 1 0 11789.1
2021-11-15 4689.3 4717.75 4672.78 4697.96 15279660000 0.00322664 11927.2 11300 1 0 11927.2
2021-11-22 4712 4743.83 4585.43 4594.62 11775840000 -0.0219967 11764.8 11400 1 0 11764.8
2021-11-29 4628.75 4672.95 4495.12 4538.43 20242840000 -0.0122295 11720.9 11500 -1 100 11864.8
2021-12-06 4548.37 4713.57 4540.51 4712.02 15411530000 0.0382489 12269.2 11600 -1 100 11964.8
2021-12-13 4710.3 4731.99 4600.22 4620.64 19184960000 -0.0193929 12131.3 11700 1 0 11832.8
2021-12-20 4587.9 4740.74 4531.1 4725.79 10594350000 0.0227566 12507.4 11800 1 0 12202
2021-12-27 4733.99 4808.93 4733.99 4766.18 11687720000 0.00854675 12714.3 11900 1 0 12406.3
2022-01-03 4778.14 4818.62 4662.74 4677.03 16800900000 -0.0187048 12576.4 12000 1 0 12274.3
2022-01-10 4655.34 4748.83 4582.24 4662.85 17126800000 -0.00303177 12638.3 12100 1 0 12337.1
2022-01-17 4632.24 4632.24 4395.34 4397.94 14131200000 -0.0568129 12020.3 12200 1 0 11736.1
2022-01-24 4356.32 4453.23 4222.62 4431.85 21218590000 0.00771046 12213 12300 -1 100 11836.1
2022-01-31 4431.79 4595.31 4414.02 4500.53 18846100000 0.0154968 12502.2 12400 -1 100 11936.1
2022-02-07 4505.75 4590.03 4401.41 4418.64 19119200000 -0.0181956 12374.7 12500 1 0 11819
2022-02-14 4412.61 4489.55 4327.22 4348.87 17775970000 -0.0157899 12279.4 12600 1 0 11732.3
2022-02-21 4332.74 4385.34 4114.65 4384.65 16834460000 0.00822737 12480.4 12700 1 0 11928.9
2022-02-28 4354.17 4416.78 4279.54 4328.87 22302830000 -0.0127216 12421.6 12800 1 0 11877.1
2022-03-07 4327.01 4327.01 4157.87 4204.31 23849630000 -0.0287743 12164.2 12900 -1 100 11977.1
2022-03-14 4202.75 4465.4 4161.72 4463.12 24946690000 0.0615583 13013 13000 -1 100 12077.1
2022-03-21 4462.4 4546.03 4424.3 4543.06 19089240000 0.0179112 13346.1 13100 1 0 12393.4
2022-03-28 4541.09 4637.3 4507.57 4545.86 19212230000 0.000616282 13454.3 13200 1 0 12501.1
2022-04-04 4547.97 4593.45 4450.04 4488.28 19383860000 -0.0126665 13383.9 13300 1 0 12442.7
2022-04-11 4462.64 4471 4381.34 4392.59 13812410000 -0.02132 13198.5 13400 1 0 12277.4
2022-04-18 4385.63 4512.94 4267.62 4271.78 18149540000 -0.0275032 12935.5 13500 -1 100 12377.4
2022-04-25 4255.34 4308.45 4124.28 4131.93 19610750000 -0.032738 12612 13600 -1 100 12477.4
2022-05-02 4130.61 4307.66 4062.51 4123.34 21039720000 -0.00207901 12685.8 13700 -1 100 12577.4
2022-05-09 4081.27 4081.27 3858.87 4023.89 23166570000 -0.0241188 12479.9 13800 -1 100 12677.4
2022-05-16 4013.02 4090.72 3810.32 3901.36 20590520000 -0.0304506 12199.8 13900 -1 100 12777.4
2022-05-23 3919.42 4158.49 3875.13 4158.24 19139100000 0.0658437 13103.1 14000 -1 100 12877.4
2022-05-30 4151.09 4177.51 4073.85 4108.54 16049940000 -0.0119522 13046.5 14100 1 0 12823.5
2022-06-06 4134.72 4168.78 3900.16 3900.86 17547150000 -0.0505484 12487 14200 1 0 12275.3
2022-06-13 3838.15 3838.15 3636.87 3674.84 24639140000 -0.0579411 11863.5 14300 -1 100 12375.3
2022-06-20 3715.31 3913.65 3715.31 3911.74 19287840000 0.0644654 12728.3 14400 -1 100 12475.3
2022-06-27 3920.76 3945.86 3738.67 3825.33 17735450000 -0.0220899 12547.1 14500 -1 100 12575.3
2022-07-04 3792.61 3918.5 3742.06 3899.38 14223350000 0.0193578 12890 14600 -1 100 12675.3
2022-07-11 3880.94 3880.94 3721.56 3863.16 16313500000 -0.00928865 12870.3 14700 -1 100 12775.3
2022-07-18 3883.79 4012.44 3818.63 3961.63 16859220000 0.0254895 13298.4 14800 -1 100 12875.3
2022-07-25 3965.72 4140.15 3910.74 4130.29 17356830000 0.0425734 13964.5 14900 1 0 13523.5
2022-08-01 4112.38 4167.66 4079.81 4145.19 18072230000 0.00360747 14114.9 15000 1 0 13672.3
2022-08-08 4155.93 4280.47 4112.09 4280.15 18117740000 0.0325582 14674.4 15100 1 0 14217.4
2022-08-15 4269.37 4325.28 4218.7 4228.48 16255850000 -0.012072 14597.3 15200 1 0 14145.8
2022-08-19 4266.31 4266.31 4218.7 4228.48 2045645000 0 14697.3 15300 1 0 14245.8
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