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option to return nan in case of failure in return_calc

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return calc returns tuple
This commit is contained in:
Gourav Kumar 2022-02-25 10:38:20 +05:30
parent 9e4049a973
commit 870d0bd96b
1 changed files with 39 additions and 7 deletions
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46
fincal/fincal.py
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@ -122,9 +122,11 @@ class TimeSeries(TimeSeriesCore):
def calculate_returns( def calculate_returns(
self, self,
as_on: Union[str, datetime.datetime], as_on: Union[str, datetime.datetime],
return_actual_date: bool = True,
as_on_match: str = "closest", as_on_match: str = "closest",
prior_match: str = "closest", prior_match: str = "closest",
closest: str = "previous", closest: str = "previous",
if_not_found: Literal['fail', 'nan'] = 'fail',
compounding: bool = True, compounding: bool = True,
interval_type: Literal['years', 'months', 'days'] = 'years', interval_type: Literal['years', 'months', 'days'] = 'years',
interval_value: int = 1, interval_value: int = 1,
@ -137,6 +139,10 @@ class TimeSeries(TimeSeriesCore):
as_on : datetime.datetime as_on : datetime.datetime
The date as on which the return is to be calculated. The date as on which the return is to be calculated.
return_actual_date : bool, default True
If true, the output will contain the actual date based on which the return was calculated.
Set to False to return the date passed in the as_on argument.
as_on_match : str, optional as_on_match : str, optional
The mode of matching the as_on_date. Refer closest. The mode of matching the as_on_date. Refer closest.
@ -147,15 +153,28 @@ class TimeSeries(TimeSeriesCore):
The mode of matching the closest date. The mode of matching the closest date.
Valid values are 'exact', 'previous', 'next' and next. Valid values are 'exact', 'previous', 'next' and next.
if_not_found : 'fail' | 'nan'
What to do when required date is not found:
* fail: Raise a ValueError
* nan: Return nan as the value
compounding : bool, optional compounding : bool, optional
Whether the return should be compounded annually. Whether the return should be compounded annually.
years : int, optional interval_type : 'years', 'months', 'days'
number of years for which the returns should be calculated The type of time period to use for return calculation.
interval_value : int
The value of the specified interval type over which returns needs to be calculated.
date_format: str
The date format to use for this operation.
Should be passed as a datetime library compatible string.
Sets the date format only for this operation. To set it globally, use FincalOptions.date_format
Returns Returns
------- -------
The float value of the returns. A tuple containing the date and float value of the returns.
Raises Raises
------ ------
@ -170,13 +189,19 @@ class TimeSeries(TimeSeriesCore):
as_on = _parse_date(as_on, date_format) as_on = _parse_date(as_on, date_format)
as_on_delta, prior_delta = _preprocess_match_options(as_on_match, prior_match, closest) as_on_delta, prior_delta = _preprocess_match_options(as_on_match, prior_match, closest)
original_as_on = as_on
while True: while True:
current = self.data.get(as_on, None) current = self.data.get(as_on, None)
if current is not None: if current is not None:
break break
elif not as_on_delta: elif not as_on_delta:
raise ValueError("As on date not found") if if_not_found == 'fail':
raise ValueError(f"As on date {original_as_on} not found")
elif if_not_found == 'nan':
return as_on, float("NaN")
else:
raise ValueError(f"Invalid argument for if_not_found: {if_not_found}")
as_on += as_on_delta as_on += as_on_delta
prev_date = as_on - relativedelta(**{interval_type: interval_value}) prev_date = as_on - relativedelta(**{interval_type: interval_value})
@ -185,14 +210,19 @@ class TimeSeries(TimeSeriesCore):
if previous is not None: if previous is not None:
break break
elif not prior_delta: elif not prior_delta:
raise ValueError("Previous date not found") if if_not_found == 'fail':
raise ValueError(f"Previous date {previous} not found")
elif if_not_found == 'nan':
return (as_on if return_actual_date else original_as_on), float("NaN")
else:
raise ValueError(f"Invalid argument for if_not_found: {if_not_found}")
prev_date += prior_delta prev_date += prior_delta
returns = current / previous returns = current / previous
if compounding: if compounding:
years = _interval_to_years(interval_type, interval_value) years = _interval_to_years(interval_type, interval_value)
returns = returns ** (1 / years) returns = returns ** (1 / years)
return returns - 1 return (as_on if return_actual_date else original_as_on), returns - 1
def calculate_rolling_returns( def calculate_rolling_returns(
self, self,
@ -202,6 +232,7 @@ class TimeSeries(TimeSeriesCore):
as_on_match: str = "closest", as_on_match: str = "closest",
prior_match: str = "closest", prior_match: str = "closest",
closest: str = "previous", closest: str = "previous",
if_not_found: Literal['fail', 'nan'] = 'fail',
compounding: bool = True, compounding: bool = True,
interval_type: Literal['years', 'months', 'days'] = 'years', interval_type: Literal['years', 'months', 'days'] = 'years',
interval_value: int = 1, interval_value: int = 1,
@ -234,8 +265,9 @@ class TimeSeries(TimeSeriesCore):
as_on_match=as_on_match, as_on_match=as_on_match,
prior_match=prior_match, prior_match=prior_match,
closest=closest, closest=closest,
if_not_found=if_not_found
) )
rolling_returns.append((i, returns)) rolling_returns.append(returns)
rolling_returns.sort() rolling_returns.sort()
return self.__class__(rolling_returns, self.frequency.symbol) return self.__class__(rolling_returns, self.frequency.symbol)