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50c423611d
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50c423611d | ||
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308a4f1abb | ||
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0fbca4ae4c | ||
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66ccd2a3f8 | ||
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@ -114,6 +114,18 @@ def _parse_date(date: str, date_format: str = None):
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return date
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def _interval_to_years(interval_type: Literal['years', 'months', 'day'], interval_value: int) -> int:
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"""Converts any time period to years for use with compounding functions"""
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day_conversion_factor = {
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'years': 1,
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'months': 12,
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'days': 365
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}
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years = interval_value/day_conversion_factor[interval_type]
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return years
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class _IndexSlicer:
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"""Class to create a slice using iloc in TimeSeriesCore"""
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@ -1,11 +1,17 @@
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from __future__ import annotations
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import datetime
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from typing import List, Union
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from typing import List, Literal, Union
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from dateutil.relativedelta import relativedelta
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from .core import AllFrequencies, TimeSeriesCore, _parse_date, _preprocess_match_options
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from .core import (
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AllFrequencies,
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TimeSeriesCore,
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_interval_to_years,
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_parse_date,
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_preprocess_match_options,
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)
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def create_date_series(
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@ -120,7 +126,8 @@ class TimeSeries(TimeSeriesCore):
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prior_match: str = "closest",
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closest: str = "previous",
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compounding: bool = True,
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years: int = 1,
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interval_type: Literal['years', 'months', 'days'] = 'years',
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interval_value: int = 1,
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date_format: str = None
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) -> float:
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"""Method to calculate returns for a certain time-period as on a particular date
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@ -172,7 +179,7 @@ class TimeSeries(TimeSeriesCore):
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raise ValueError("As on date not found")
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as_on += as_on_delta
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prev_date = as_on - relativedelta(years=years)
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prev_date = as_on - relativedelta(**{interval_type: interval_value})
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while True:
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previous = self.data.get(prev_date, None)
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if previous is not None:
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@ -183,6 +190,7 @@ class TimeSeries(TimeSeriesCore):
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returns = current / previous
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if compounding:
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years = _interval_to_years(interval_type, interval_value)
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returns = returns ** (1 / years)
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return returns - 1
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@ -195,7 +203,8 @@ class TimeSeries(TimeSeriesCore):
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prior_match: str = "closest",
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closest: str = "previous",
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compounding: bool = True,
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years: int = 1,
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interval_type: Literal['years', 'months', 'days'] = 'years',
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interval_value: int = 1,
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date_format: str = None
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) -> List[tuple]:
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"""Calculates the rolling return"""
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@ -220,7 +229,8 @@ class TimeSeries(TimeSeriesCore):
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returns = self.calculate_returns(
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as_on=i,
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compounding=compounding,
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years=years,
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interval_type=interval_type,
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interval_value=interval_value,
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as_on_match=as_on_match,
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prior_match=prior_match,
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closest=closest,
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@ -1,5 +1,6 @@
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import datetime
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from typing import Mapping
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import random
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from typing import Literal, Mapping, Sequence
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from fincal.core import AllFrequencies, Frequency, Series, TimeSeriesCore
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from fincal.fincal import create_date_series
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@ -15,6 +16,48 @@ class TestFrequency:
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assert D.freq_type == 'days'
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def create_test_data(
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frequency: str,
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eomonth: bool,
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n: int,
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gaps: float,
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month_position: Literal["start", "middle", "end"],
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date_as_str: bool,
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as_outer_type: Literal["dict", "list"] = "list",
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as_inner_type: Literal["dict", "list", "tuple"] = "tuple",
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) -> Sequence[tuple]:
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start_dates = {
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"start": datetime.datetime(2016, 1, 1),
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"middle": datetime.datetime(2016, 1, 15),
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"end": datetime.datetime(2016, 1, 31),
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}
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end_date = datetime.datetime(2021, 12, 31)
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dates = create_date_series(start_dates[month_position], end_date, frequency=frequency, eomonth=eomonth)
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dates = dates[:n]
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if gaps:
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num_gaps = int(len(dates) * gaps)
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to_remove = random.sample(dates, num_gaps)
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for i in to_remove:
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dates.remove(i)
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if date_as_str:
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dates = [i.strftime("%Y-%m-%d") for i in dates]
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values = [random.randint(8000, 90000) / 100 for _ in dates]
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data = list(zip(dates, values))
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if as_outer_type == "list":
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if as_inner_type == "list":
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data = [list(i) for i in data]
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elif as_inner_type == "dict[1]":
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data = [dict((i,)) for i in data]
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elif as_inner_type == "dict[2]":
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data = [dict(date=i, value=j) for i, j in data]
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elif as_outer_type == "dict":
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data = dict(data)
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return data
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class TestAllFrequencies:
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def test_attributes(self):
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assert hasattr(AllFrequencies, 'D')
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@ -53,6 +96,15 @@ class TestSeries:
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class TestTimeSeriesCore:
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data = [('2021-01-01', 220), ('2021-02-01', 230), ('2021-03-01', 240)]
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def test_repr_str(self):
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ts = TimeSeriesCore(self.data, frequency='M')
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assert str(ts) in repr(ts).replace('\t', ' ')
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data = create_test_data(frequency="D", eomonth=False, n=50, gaps=0, month_position="start", date_as_str=True)
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ts = TimeSeriesCore(data, frequency="D")
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assert '...' in str(ts)
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assert '...' in repr(ts)
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def test_creation(self):
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ts = TimeSeriesCore(self.data, frequency='M')
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assert isinstance(ts, TimeSeriesCore)
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@ -115,7 +115,7 @@ class TestDateSeries:
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assert datetime.datetime(2020, 11, 30) in d
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class TestFincal:
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class TestFincalBasic:
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def test_creation(self):
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data = create_test_data(frequency="D", eomonth=False, n=50, gaps=0, month_position="start", date_as_str=True)
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time_series = TimeSeries(data, frequency="D")
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@ -130,7 +130,7 @@ class TestFincal:
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time_series = TimeSeries(data, frequency="D")
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assert len(time_series) == 450
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def test_ffill(self):
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def test_fill(self):
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data = create_test_data(frequency="D", eomonth=False, n=500, gaps=0.1, month_position="start", date_as_str=True)
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time_series = TimeSeries(data, frequency="D")
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ffill_data = time_series.ffill()
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@ -140,6 +140,23 @@ class TestFincal:
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assert ffill_data is None
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assert len(time_series) >= 498
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data = create_test_data(frequency="D", eomonth=False, n=500, gaps=0.1, month_position="start", date_as_str=True)
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time_series = TimeSeries(data, frequency="D")
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bfill_data = time_series.bfill()
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assert len(bfill_data) >= 498
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bfill_data = time_series.bfill(inplace=True)
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assert bfill_data is None
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assert len(time_series) >= 498
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data = [("2021-01-01", 220), ("2021-01-02", 230), ("2021-03-04", 240)]
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ts = TimeSeries(data, frequency="D")
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ff = ts.ffill()
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assert ff["2021-01-03"][1] == 230
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bf = ts.bfill()
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assert bf["2021-01-03"][1] == 240
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def test_iloc_slicing(self):
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data = create_test_data(frequency="D", eomonth=False, n=50, gaps=0, month_position="start", date_as_str=True)
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time_series = TimeSeries(data, frequency="D")
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@ -159,3 +176,31 @@ class TestFincal:
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assert isinstance(time_series["values"], Series)
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assert len(time_series.dates) == 50
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assert len(time_series.values) == 50
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def test_returns_calc(self):
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data = [
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('2020-01-01', 10),
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('2020-02-01', 12),
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('2020-03-01', 14),
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('2020-04-01', 16),
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('2020-05-01', 18),
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('2020-06-01', 20),
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('2020-07-01', 22),
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('2020-08-01', 24),
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('2020-09-01', 26),
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('2020-10-01', 28),
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('2020-11-01', 30),
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('2020-12-01', 32),
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('2021-01-01', 34)
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]
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ts = TimeSeries(data, frequency='M')
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returns = ts.calculate_returns("2021-01-01", compounding=False, interval_type='years', interval_value=1)
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assert returns == 2.4
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returns = ts.calculate_returns("2020-04-01", compounding=False, interval_type='months', interval_value=3)
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assert round(returns, 4) == 0.6
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returns = ts.calculate_returns("2020-04-01", compounding=True, interval_type='months', interval_value=3)
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assert round(returns, 4) == 5.5536
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returns = ts.calculate_returns("2020-04-01", compounding=False, interval_type='days', interval_value=90)
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assert round(returns, 4) == 0.6
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returns = ts.calculate_returns("2020-04-01", compounding=True, interval_type='days', interval_value=90)
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assert round(returns, 4) == 5.727
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