Merge branch 'master' of http://192.168.0.114:3000/buddy/fincal
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						b34c14d778
					
				| @ -3,7 +3,7 @@ from __future__ import annotations | ||||
| import datetime | ||||
| import math | ||||
| import statistics | ||||
| from typing import Iterable, List, Literal, Mapping, Union | ||||
| from typing import Iterable, List, Literal, Mapping, TypedDict, Union | ||||
| 
 | ||||
| from dateutil.relativedelta import relativedelta | ||||
| 
 | ||||
| @ -16,6 +16,12 @@ from .utils import ( | ||||
| ) | ||||
| 
 | ||||
| 
 | ||||
| class MaxDrawdown(TypedDict): | ||||
|     start_date: datetime.datetime | ||||
|     end_date: datetime.datetime | ||||
|     drawdown: float | ||||
| 
 | ||||
| 
 | ||||
| @date_parser(0, 1) | ||||
| def create_date_series( | ||||
|     start_date: Union[str, datetime.datetime], | ||||
| @ -115,11 +121,11 @@ class TimeSeries(TimeSeriesCore): | ||||
| 
 | ||||
|         super().__init__(data, frequency, date_format) | ||||
| 
 | ||||
|     def info(self): | ||||
|     def info(self) -> str: | ||||
|         """Summary info about the TimeSeries object""" | ||||
| 
 | ||||
|         total_dates = len(self.data.keys()) | ||||
|         res_string = "First date: {}\nLast date: {}\nNumber of rows: {}" | ||||
|         total_dates: int = len(self.data.keys()) | ||||
|         res_string: str = "First date: {}\nLast date: {}\nNumber of rows: {}" | ||||
|         return res_string.format(self.start_date, self.end_date, total_dates) | ||||
| 
 | ||||
|     def ffill(self, inplace: bool = False, limit: int = None) -> Union[TimeSeries, None]: | ||||
| @ -138,7 +144,7 @@ class TimeSeries(TimeSeriesCore): | ||||
|             Returns a TimeSeries object if inplace is False, otherwise None | ||||
|         """ | ||||
| 
 | ||||
|         eomonth = True if self.frequency.days >= AllFrequencies.M.days else False | ||||
|         eomonth: bool = True if self.frequency.days >= AllFrequencies.M.days else False | ||||
|         dates_to_fill = create_date_series(self.start_date, self.end_date, self.frequency.symbol, eomonth) | ||||
| 
 | ||||
|         new_ts = dict() | ||||
| @ -171,7 +177,7 @@ class TimeSeries(TimeSeriesCore): | ||||
|             Returns a TimeSeries object if inplace is False, otherwise None | ||||
|         """ | ||||
| 
 | ||||
|         eomonth = True if self.frequency.days >= AllFrequencies.M.days else False | ||||
|         eomonth: bool = True if self.frequency.days >= AllFrequencies.M.days else False | ||||
|         dates_to_fill = create_date_series(self.start_date, self.end_date, self.frequency.symbol, eomonth) | ||||
|         dates_to_fill.append(self.end_date) | ||||
| 
 | ||||
| @ -517,21 +523,31 @@ class TimeSeries(TimeSeriesCore): | ||||
|         rr = self.calculate_rolling_returns(**kwargs) | ||||
|         return statistics.mean(rr.values) | ||||
| 
 | ||||
|     def max_drawdown(self): | ||||
|         max_val_dict = {} | ||||
|     def max_drawdown(self) -> MaxDrawdown: | ||||
|         """Calculates the maximum fall the stock has taken between any two points. | ||||
| 
 | ||||
|         prev_val = 0 | ||||
|         prev_date = list(self.data)[0] | ||||
|         Returns | ||||
|         ------- | ||||
|         MaxDrawdown | ||||
|             Returns the start_date, end_date, and the drawdown value in decimal. | ||||
|         """ | ||||
| 
 | ||||
|         drawdowns: dict = dict() | ||||
| 
 | ||||
|         prev_val: float = 0 | ||||
|         prev_date: datetime.datetime = list(self.data)[0] | ||||
| 
 | ||||
|         for dt, val in self.data.items(): | ||||
|             if val > prev_val: | ||||
|                 max_val_dict[dt] = (dt, val, 0) | ||||
|                 drawdowns[dt] = (dt, val, 0) | ||||
|                 prev_date, prev_val = dt, val | ||||
|             else: | ||||
|                 max_val_dict[dt] = (prev_date, prev_val, val / prev_val - 1) | ||||
|                 drawdowns[dt] = (prev_date, prev_val, val / prev_val - 1) | ||||
| 
 | ||||
|         max_drawdown = min(max_val_dict.items(), key=lambda x: x[1][2]) | ||||
|         max_drawdown = dict(start_date=max_drawdown[1][0], end_date=max_drawdown[0], drawdown=max_drawdown[1][2]) | ||||
|         max_drawdown = min(drawdowns.items(), key=lambda x: x[1][2]) | ||||
|         max_drawdown: MaxDrawdown = dict( | ||||
|             start_date=max_drawdown[1][0], end_date=max_drawdown[0], drawdown=max_drawdown[1][2] | ||||
|         ) | ||||
| 
 | ||||
|         return max_drawdown | ||||
| 
 | ||||
|  | ||||
| @ -1,12 +1,13 @@ | ||||
| import datetime | ||||
| import math | ||||
| import random | ||||
| from unittest import skip | ||||
| 
 | ||||
| import pytest | ||||
| from dateutil.relativedelta import relativedelta | ||||
| from fincal.core import AllFrequencies, Frequency | ||||
| from fincal.exceptions import DateNotFoundError | ||||
| from fincal.fincal import TimeSeries, create_date_series | ||||
| from fincal.fincal import MaxDrawdown, TimeSeries, create_date_series | ||||
| from fincal.utils import FincalOptions | ||||
| 
 | ||||
| 
 | ||||
| @ -77,7 +78,9 @@ def create_test_timeseries( | ||||
| 
 | ||||
|     start_date = datetime.datetime(2017, 1, 1) | ||||
|     timedelta_dict = { | ||||
|         frequency.freq_type: int(frequency.value * num * (7 / 5 if frequency == "D" and skip_weekends else 1)) | ||||
|         frequency.freq_type: int( | ||||
|             frequency.value * num * (7 / 5 if frequency == AllFrequencies.D and skip_weekends else 1) | ||||
|         ) | ||||
|     } | ||||
|     end_date = start_date + relativedelta(**timedelta_dict) | ||||
|     dates = create_date_series(start_date, end_date, frequency.symbol, skip_weekends=skip_weekends) | ||||
| @ -88,7 +91,7 @@ def create_test_timeseries( | ||||
| 
 | ||||
| class TestReturns: | ||||
|     def test_returns_calc(self): | ||||
|         ts = create_test_timeseries() | ||||
|         ts = create_test_timeseries(AllFrequencies.D, skip_weekends=True) | ||||
|         returns = ts.calculate_returns( | ||||
|             "2020-01-01", annual_compounded_returns=False, return_period_unit="years", return_period_value=1 | ||||
|         ) | ||||
| @ -120,7 +123,7 @@ class TestReturns: | ||||
|             ts.calculate_returns("2020-04-04", return_period_unit="months", return_period_value=3, prior_match="exact") | ||||
| 
 | ||||
|     def test_date_formats(self): | ||||
|         ts = create_test_timeseries() | ||||
|         ts = create_test_timeseries(AllFrequencies.D, skip_weekends=True) | ||||
|         FincalOptions.date_format = "%d-%m-%Y" | ||||
|         with pytest.raises(ValueError): | ||||
|             ts.calculate_returns( | ||||
| @ -147,7 +150,7 @@ class TestReturns: | ||||
| 
 | ||||
|     def test_limits(self): | ||||
|         FincalOptions.date_format = "%Y-%m-%d" | ||||
|         ts = create_test_timeseries() | ||||
|         ts = create_test_timeseries(AllFrequencies.D) | ||||
|         with pytest.raises(DateNotFoundError): | ||||
|             ts.calculate_returns("2020-11-25", return_period_unit="days", return_period_value=90, closest_max_days=10) | ||||
| 
 | ||||
| @ -177,3 +180,31 @@ class TestVolatility: | ||||
|             annualize_volatility=False, | ||||
|         ) | ||||
|         assert round(sd, 6) == 0.020547 | ||||
| 
 | ||||
| 
 | ||||
| class TestDrawdown: | ||||
|     def test_daily_ts(self): | ||||
|         ts = create_test_timeseries(AllFrequencies.D, skip_weekends=True) | ||||
|         mdd = ts.max_drawdown() | ||||
|         assert isinstance(mdd, dict) | ||||
|         assert len(mdd) == 3 | ||||
|         assert all(i in mdd for i in ["start_date", "end_date", "drawdown"]) | ||||
|         expeced_response = { | ||||
|             "start_date": datetime.datetime(2017, 6, 6, 0, 0), | ||||
|             "end_date": datetime.datetime(2017, 7, 31, 0, 0), | ||||
|             "drawdown": -0.028293686030751997, | ||||
|         } | ||||
|         assert mdd == expeced_response | ||||
| 
 | ||||
|     def test_weekly_ts(self): | ||||
|         ts = create_test_timeseries(AllFrequencies.W, mu=1, sigma=0.5) | ||||
|         mdd = ts.max_drawdown() | ||||
|         assert isinstance(mdd, dict) | ||||
|         assert len(mdd) == 3 | ||||
|         assert all(i in mdd for i in ["start_date", "end_date", "drawdown"]) | ||||
|         expeced_response = { | ||||
|             "start_date": datetime.datetime(2019, 2, 17, 0, 0), | ||||
|             "end_date": datetime.datetime(2019, 11, 17, 0, 0), | ||||
|             "drawdown": -0.2584760499552089, | ||||
|         } | ||||
|         assert mdd == expeced_response | ||||
|  | ||||
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