96 lines
3.8 KiB
Python
96 lines
3.8 KiB
Python
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import datetime
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import math
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import random
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import pytest
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from fincal.exceptions import DateNotFoundError
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from fincal.fincal import TimeSeries, create_date_series
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from fincal.utils import FincalOptions
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def create_prices(s0: float, mu: float, sigma: float, num_prices: int) -> list:
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"""Generates a price following a geometric brownian motion process based on the input of the arguments:
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- s0: Asset inital price.
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- mu: Interest rate expressed annual terms.
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- sigma: Volatility expressed annual terms.
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- seed: seed for the random number generator
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- num_prices: number of prices to generate
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"""
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random.seed(1234) # WARNING! Changing the seed will cause most tests to fail
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all_values = []
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for _ in range(num_prices):
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s0 *= math.exp(
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(mu - 0.5 * sigma**2) * (1.0 / 365.0) + sigma * math.sqrt(1.0 / 365.0) * random.gauss(mu=0, sigma=1)
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)
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all_values.append(round(s0, 2))
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return all_values
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def create_data():
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"""Creates TimeSeries data"""
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dates = create_date_series("2017-01-01", "2020-10-31", "D", skip_weekends=True)
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values = create_prices(1000, 0.1, 0.05, 1000)
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ts = TimeSeries(dict(zip(dates, values)), frequency="D")
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return ts
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class TestReturns:
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def test_returns_calc(self):
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ts = create_data()
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returns = ts.calculate_returns(
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"2020-01-01", annual_compounded_returns=False, interval_type="years", interval_value=1
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)
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assert round(returns[1], 6) == 0.112913
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returns = ts.calculate_returns(
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"2020-04-01", annual_compounded_returns=False, interval_type="months", interval_value=3
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)
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assert round(returns[1], 6) == 0.015908
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returns = ts.calculate_returns(
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"2020-04-01", annual_compounded_returns=True, interval_type="months", interval_value=3
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)
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assert round(returns[1], 6) == 0.065167
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returns = ts.calculate_returns(
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"2020-04-01", annual_compounded_returns=False, interval_type="days", interval_value=90
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)
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assert round(returns[1], 6) == 0.017673
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returns = ts.calculate_returns(
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"2020-04-01", annual_compounded_returns=True, interval_type="days", interval_value=90
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)
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assert round(returns[1], 6) == 0.073632
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with pytest.raises(DateNotFoundError):
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ts.calculate_returns("2020-04-04", interval_type="days", interval_value=90, as_on_match="exact")
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with pytest.raises(DateNotFoundError):
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ts.calculate_returns("2020-04-04", interval_type="months", interval_value=3, prior_match="exact")
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def test_date_formats(self):
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ts = create_data()
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FincalOptions.date_format = "%d-%m-%Y"
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with pytest.raises(ValueError):
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ts.calculate_returns("2020-04-10", annual_compounded_returns=True, interval_type="days", interval_value=90)
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returns1 = ts.calculate_returns("2020-04-01", interval_type="days", interval_value=90, date_format="%Y-%m-%d")
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returns2 = ts.calculate_returns("01-04-2020", interval_type="days", interval_value=90)
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assert round(returns1[1], 6) == round(returns2[1], 6) == 0.073632
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FincalOptions.date_format = "%m-%d-%Y"
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with pytest.raises(ValueError):
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ts.calculate_returns("2020-04-01", annual_compounded_returns=True, interval_type="days", interval_value=90)
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returns1 = ts.calculate_returns("2020-04-01", interval_type="days", interval_value=90, date_format="%Y-%m-%d")
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returns2 = ts.calculate_returns("04-01-2020", interval_type="days", interval_value=90)
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assert round(returns1[1], 6) == round(returns2[1], 6) == 0.073632
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def test_limits(self):
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ts = create_data()
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FincalOptions.date_format = "%Y-%m-%d"
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with pytest.raises(DateNotFoundError):
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ts.calculate_returns("2020-11-25", interval_type="days", interval_value=90, closest_max_days=10)
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