def test__compute_correctly_in_other_currencies():
okid10_usd = lib.portfolio_asset(name=__asset_name, end_period='2018-12', currency='usd')
okid10_rub = lib.portfolio_asset(name=__asset_name, end_period='2018-12', currency='rub')
okid10_currency_rate = okid10_usd.close() / okid10_rub.close()
vs_rub = lib.portfolio_asset(name='cbr/RUB',
start_period=okid10_currency_rate.start_period,
end_period=okid10_currency_rate.end_period,
currency='usd').close()
np.testing.assert_almost_equal(okid10_currency_rate.values, vs_rub.values, decimal_places)
def test__currency_conversion_should_be_inversive(currency1: Currency,
currency2: Currency):
vs1 = lib.portfolio_asset(name='cbr/' + currency1.name,
start_period='2015-1',
end_period='2016-12',
currency=currency2.name).close()
vs2 = lib.portfolio_asset(name='cbr/' + currency2.name,
start_period='2015-1',
end_period='2016-12',
currency=currency1.name).close()
np.testing.assert_almost_equal(vs1.values * vs2.values, 1.)
def test__currency_should_not_be_converted_to_itself_inside_datatable(
currency: Currency):
vs = lib.portfolio_asset(name='cbr/' + currency.name,
start_period='2015-1',
end_period='2017-1',
currency=currency.name).close()
np.testing.assert_equal(vs.values, 1.)
def test__currency_should_be_converted_other_currency():
vs = lib.portfolio_asset(name='cbr/EUR',
start_period='2015-1',
end_period='2017-1',
currency='USD').close()
assert np.all(vs.values > 1.05)
def test__have_valid_selected_period_range():
start_period = pd.Period('2013-1', freq='M')
end_period = pd.Period('2015-3', freq='M')
okid10 = lib.portfolio_asset(name=__asset_name, start_period=str(start_period), end_period=str(end_period))
assert okid10.close().start_period == start_period
assert okid10.close().end_period == end_period
def test__asset_should_be_converted_correctly():
vs_eur = lib.portfolio_asset(name='mut_ru/0890-94127385',
start_period='2011-1',
end_period='2017-2',
currency='EUR').close()
vs_usd = lib.portfolio_asset(name='mut_ru/0890-94127385',
start_period='2011-1',
end_period='2017-2',
currency='USD').close()
vs_curr = lib.portfolio_asset(name='cbr/USD',
start_period='2011-1',
end_period='2017-2',
currency='EUR').close()
np.testing.assert_almost_equal((vs_eur / vs_usd).values, vs_curr.values)
def test__us_data_source_values():
asset = lib.portfolio_asset(name='us/MSFT',
start_period='2017-11',
end_period='2018-2',
currency='usd')
period_range_expected = pd.period_range(start='2017-11',
end='2017-12',
freq='M')
assert asset.close().period_range() == list(period_range_expected)
def test__support_all_types_of_currency_conversions(currency_from: Currency,
currency_to: Currency):
vs = lib.portfolio_asset(name='cbr/' + currency_from.name,
start_period='2015-1',
end_period='2016-12',
currency=currency_to.name).close()
assert vs.size == 2 * 12
assert np.all(vs.values > 0.)
def test__default_periods():
asset = lib.portfolio_asset(name='micex/SBER')
assert asset.close().start_period >= pd.Period('1900-1', freq='M')
assert pd.Period.now(freq='M') >= asset.close().end_period
assert asset.currency.value == Currency.RUB
portfolio = lib.portfolio(assets={'micex/SBER': 1.}, currency='rub')
assert portfolio.get_return().start_period >= pd.Period('1900-1', freq='M')
assert pd.Period.now(freq='M') >= portfolio.get_return().end_period
def test__cagr_should_be_full_when_it_has_period_equal_to_ror():
start_period = pd.Period('2011-01', freq='M')
years_amount = 5
end_period = start_period + years_amount * 12
asset = lib.portfolio_asset(name=__asset_name,
start_period=str(start_period),
end_period=str(end_period),
currency='usd')
cagr1 = asset.cagr()
assert_that(cagr1.value, close_to(-.1426, delta))
cagr2 = asset.cagr(years_ago=years_amount)
assert_that(cagr2.value, close_to(cagr1.value, delta))
def test__risk():
short_asset = lib.portfolio_asset(name=__asset_name,
start_period='2016-8',
end_period='2016-12',
currency='USD')
assert_that(
calling(short_asset.risk).with_args(period='year'), raises(Exception))
assert __asset.risk().kind == TimeSeriesKind.REDUCED_VALUE
assert __asset.risk(period='year').kind == TimeSeriesKind.REDUCED_VALUE
assert __asset.risk(period='month').kind == TimeSeriesKind.REDUCED_VALUE
assert_that(__asset.risk().value, close_to(.2860, delta))
assert_that(__asset.risk(period='year').value, close_to(.2860, delta))
assert_that(__asset.risk(period='month').value, close_to(.0823, delta))
def test__get_cagr_invariants():
start_period = pd.Period('2009-3', freq='M')
end_period = pd.Period('2019-3', freq='M')
asset = lib.portfolio_asset(name=__asset_name,
start_period=str(start_period),
end_period=str(end_period),
currency='rub')
years_ago = 10
months_ago = years_ago * _MONTHS_PER_YEAR
cagr = asset.cagr()
cagr10 = asset.cagr(years_ago=years_ago)
assert cagr.start_period == cagr10.start_period == start_period + 1
assert cagr.end_period == cagr10.end_period == end_period
assert cagr.period_size == months_ago
ror_c = asset.get_return(kind='cumulative')
ror_from_cagr10 = (cagr10 + 1.)**years_ago - 1.
ror_from_cagr = (cagr + 1.)**years_ago - 1.
assert_that(ror_from_cagr.value, close_to(ror_c[-1].value, delta=delta))
assert_that(ror_from_cagr10.value, close_to(ror_c[-1].value, delta=delta))
def test__return_empty_list_or_none_if_symbol_doesnt_exist():
nonexisting_id = 'mut_ru/xxx'
asset = lib.portfolio_asset(name=nonexisting_id)
assert_that(asset, none())
assets = lib.portfolio_asset(names=[nonexisting_id])
assert_that(assets, empty())
assets = lib.portfolio_asset(names=['micex/FXRU', nonexisting_id])
assert_that(assets, has_length(1))
portfolio = lib.portfolio(assets={
'micex/FXRU': 1.,
nonexisting_id: 1.
},
currency='USD')
assert len(portfolio.assets) == 1
nonexisting_namespace = 'yyy/FXRU'
asset = lib.portfolio_asset(name=nonexisting_namespace)
assert_that(asset, none())
assets = lib.portfolio_asset(names=[nonexisting_namespace])
assert_that(assets, empty())
assets = lib.portfolio_asset(names=['micex/FXRU', nonexisting_namespace])
assert_that(assets, has_length(1))
portfolio = lib.portfolio(assets={
'micex/FXRU': 1.,
nonexisting_namespace: 1.
},
currency='USD')
assert_that(portfolio.assets, has_length(1))
def test__have_correct_values():
okid10 = lib.portfolio_asset(name=__asset_name, end_period='2018-12')
np.testing.assert_almost_equal(okid10.close()[:5].values,
[100., 100.9854, 101.9356, 102.8515, 103.7328], decimal_places)
np.testing.assert_almost_equal(okid10.close()[-5:].values,
[212.0694, 213.2737, 214.4767, 215.6832, 216.8961], decimal_places)
def test__have_valid_max_period_range():
okid10 = lib.portfolio_asset(name=__asset_name)
cbr_top10 = lib.information(name='cbr/TOP_rates')
assert okid10.close().start_period == cbr_top10.start_period + _MONTHS_PER_YEAR
assert (cbr_top10.end_period - okid10.close().end_period).n < 2
import numpy as np
import pandas as pd
from hamcrest import assert_that, close_to, calling, raises
import cifrum as lib
from conftest import decimal_places, delta
from cifrum._settings import _MONTHS_PER_YEAR
from cifrum.common.time_series import TimeSeriesKind
__asset_name = 'mut_ru/0890-94127385'
__portfolio_period_start = pd.Period('2011-1', freq='M')
__portfolio_period_end = pd.Period('2017-2', freq='M')
__asset = lib.portfolio_asset(name=__asset_name,
start_period=str(__portfolio_period_start),
end_period=str(__portfolio_period_end),
currency='USD')
def test__cumulative_get_return():
arors = __asset.get_return(kind='cumulative').values
assert_that(arors.max(), close_to(.0924, delta))
assert_that(arors.min(), close_to(-.5464, delta))
arors_real = __asset.get_return(kind='cumulative', real=True).values
assert_that(arors_real.max(), close_to(.0765, delta))
assert_that(arors_real.min(), close_to(-.5725, delta))
def test__ytd_get_return():
ror_ytd = __asset.get_return(kind='ytd')
assert ror_ytd.start_period == pd.Period('2012-1', freq='M')
def test__handle_asset_with_dash_in_name():
asset = lib.portfolio_asset(name='us/BRK-B')
assert_that(asset, not_none())
assert_that(asset.close(), is_not(empty()))