38 lines
1.3 KiB
Python
38 lines
1.3 KiB
Python
|
# type: ignore
|
||
|
|
|
||
|
|
if __name__ == "__main__":
|
||
|
|
|
||
|
|
import datetime
|
||
|
|
import time
|
||
|
|
|
||
|
|
import pandas as pd
|
||
|
|
|
||
|
|
from fincal.fincal import TimeSeries
|
||
|
|
|
||
|
|
df = pd.read_csv('test_files/msft.csv')
|
||
|
|
df = df.sort_values(by='Date') # type: ignore
|
||
|
|
data_list = [(i.Date, i.Close) for i in df.itertuples()]
|
||
|
|
|
||
|
|
start = time.time()
|
||
|
|
ts_data = TimeSeries(data_list, frequency='D', date_format='%d-%m-%Y')
|
||
|
|
print(f"Instantiation took {round((time.time() - start)*1000, 2)} ms")
|
||
|
|
# ts_data.fill_missing_days()
|
||
|
|
start = time.time()
|
||
|
|
# ts_data.calculate_returns(as_on=datetime.datetime(2022, 1, 4), closest='next', years=1)
|
||
|
|
rr = ts_data.calculate_rolling_returns(datetime.datetime(1994, 1, 1),
|
||
|
|
datetime.datetime(2022, 2, 17),
|
||
|
|
frequency='D',
|
||
|
|
as_on_match='next',
|
||
|
|
prior_match='previous',
|
||
|
|
closest='previous',
|
||
|
|
years=1)
|
||
|
|
|
||
|
|
# ffill_data = ts_data.bfill()
|
||
|
|
print(f"Calculation took {round((time.time() - start)*1000, 2)} ms")
|
||
|
|
rr.sort()
|
||
|
|
for i in rr[:10]:
|
||
|
|
print(i)
|
||
|
|
# print(ffill_data)
|
||
|
|
# print(ts_data)
|
||
|
|
# print(repr(ts_data))
|