243 lines
7.7 KiB
Python
243 lines
7.7 KiB
Python
from __future__ import annotations
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import datetime
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from typing import List, 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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def create_date_series(
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start_date: datetime.datetime, end_date: datetime.datetime, frequency: str, eomonth: bool = False
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) -> List[datetime.datetime]:
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"""Creates a date series using a frequency"""
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frequency = getattr(AllFrequencies, frequency)
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if eomonth and frequency.days < AllFrequencies.M.days:
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raise ValueError(f"eomonth cannot be set to True if frequency is higher than {AllFrequencies.M.name}")
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datediff = (end_date - start_date).days / frequency.days + 1
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dates = []
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for i in range(0, int(datediff)):
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diff = {frequency.freq_type: frequency.value * i}
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date = start_date + relativedelta(**diff)
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if eomonth:
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if date.month == 12:
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date = date.replace(day=31)
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else:
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date = date.replace(day=1).replace(month=date.month+1) - relativedelta(days=1)
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if date <= end_date:
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dates.append(date)
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return dates
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class TimeSeries(TimeSeriesCore):
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"""Container for TimeSeries objects"""
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def info(self):
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"""Summary info about the TimeSeries object"""
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total_dates = len(self.data.keys())
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res_string = "First date: {}\nLast date: {}\nNumber of rows: {}"
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return res_string.format(self.start_date, self.end_date, total_dates)
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def ffill(self, inplace: bool = False, limit: int = None) -> Union[TimeSeries, None]:
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"""Forward fill missing dates in the time series
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Parameters
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----------
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inplace : bool
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Modify the time-series data in place and return None.
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limit : int, optional
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Maximum number of periods to forward fill
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Returns
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-------
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Returns a TimeSeries object if inplace is False, otherwise None
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"""
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eomonth = True if self.frequency.days >= AllFrequencies.M.days else False
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dates_to_fill = create_date_series(self.start_date, self.end_date, self.frequency.symbol, eomonth)
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new_ts = dict()
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for cur_date in dates_to_fill:
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try:
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cur_val = self.data[cur_date]
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except KeyError:
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pass
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new_ts.update({cur_date: cur_val})
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if inplace:
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self.data = new_ts
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return None
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return TimeSeries(new_ts, frequency=self.frequency.symbol)
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def bfill(self, inplace: bool = False, limit: int = None) -> Union[TimeSeries, None]:
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"""Backward fill missing dates in the time series
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Parameters
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----------
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inplace : bool
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Modify the time-series data in place and return None.
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limit : int, optional
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Maximum number of periods to back fill
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Returns
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-------
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Returns a TimeSeries object if inplace is False, otherwise None
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"""
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eomonth = True if self.frequency.days >= AllFrequencies.M.days else False
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dates_to_fill = create_date_series(self.start_date, self.end_date, self.frequency.symbol, eomonth)
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dates_to_fill.append(self.end_date)
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bfill_ts = dict()
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for cur_date in reversed(dates_to_fill):
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try:
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cur_val = self.data[cur_date]
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except KeyError:
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pass
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bfill_ts.update({cur_date: cur_val})
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new_ts = {k: bfill_ts[k] for k in reversed(bfill_ts)}
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if inplace:
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self.data = new_ts
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return None
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return TimeSeries(new_ts, frequency=self.frequency.symbol)
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def calculate_returns(
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self,
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as_on: Union[str, datetime.datetime],
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as_on_match: str = "closest",
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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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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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Parameters
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----------
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as_on : datetime.datetime
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The date as on which the return is to be calculated.
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as_on_match : str, optional
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The mode of matching the as_on_date. Refer closest.
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prior_match : str, optional
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The mode of matching the prior_date. Refer closest.
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closest : str, optional
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The mode of matching the closest date.
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Valid values are 'exact', 'previous', 'next' and next.
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compounding : bool, optional
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Whether the return should be compounded annually.
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years : int, optional
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number of years for which the returns should be calculated
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Returns
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-------
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The float value of the returns.
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Raises
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------
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ValueError
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* If match mode for any of the dates is exact and the exact match is not found
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* If the arguments passsed for closest, as_on_match, and prior_match are invalid
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Example
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--------
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>>> calculate_returns(datetime.date(2020, 1, 1), years=1)
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"""
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as_on = _parse_date(as_on, date_format)
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as_on_delta, prior_delta = _preprocess_match_options(as_on_match, prior_match, closest)
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while True:
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current = self.data.get(as_on, None)
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if current is not None:
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break
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elif not as_on_delta:
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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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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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break
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elif not prior_delta:
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raise ValueError("Previous date not found")
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prev_date += prior_delta
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returns = current / previous
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if compounding:
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returns = returns ** (1 / years)
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return returns - 1
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def calculate_rolling_returns(
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self,
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from_date: Union[datetime.date, str],
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to_date: Union[datetime.date, str],
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frequency: str = None,
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as_on_match: str = "closest",
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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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date_format: str = None
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) -> List[tuple]:
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"""Calculates the rolling return"""
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from_date = _parse_date(from_date, date_format)
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to_date = _parse_date(to_date, date_format)
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if frequency is None:
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frequency = self.frequency
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else:
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try:
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frequency = getattr(AllFrequencies, frequency)
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except AttributeError:
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raise ValueError(f"Invalid argument for frequency {frequency}")
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dates = create_date_series(from_date, to_date, frequency.symbol)
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if frequency == AllFrequencies.D:
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dates = [i for i in dates if i in self.data]
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rolling_returns = []
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for i in dates:
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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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as_on_match=as_on_match,
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prior_match=prior_match,
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closest=closest,
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)
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rolling_returns.append((i, returns))
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rolling_returns.sort()
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return rolling_returns
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if __name__ == "__main__":
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date_series = [
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datetime.datetime(2020, 1, 1),
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datetime.datetime(2020, 1, 2),
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datetime.datetime(2020, 1, 3),
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datetime.datetime(2020, 1, 4),
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datetime.datetime(2020, 1, 7),
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datetime.datetime(2020, 1, 8),
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datetime.datetime(2020, 1, 9),
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datetime.datetime(2020, 1, 10),
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datetime.datetime(2020, 1, 12),
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]
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