def test_getters(self):
# Test Name
test_portfolio = Portfolio(a_name='myPortfolio')
self.assertIs(test_portfolio.portFolioName, 'myPortfolio')
# Test myAssets
asset1 = Asset(a_name='myAsset1', assetType='etf')
asset2 = Asset(a_name='myAsset2', assetType='fund')
test_portfolio.myAssets = [asset1, asset2]
self.assertIsInstance(test_portfolio.myAssets, list)
self.assertIsInstance(test_portfolio.myAssets[0], Asset)
self.assertIsInstance(test_portfolio.myAssets[1], Asset)
# Test Number of Assets
self.assertEqual(test_portfolio.assetsNumber, 2)
# Test Df
dummyDf = pd.DataFrame({'hey': [1, 2], 'ou': [3, 4]})
test_portfolio.portfolioDf = dummyDf
self.assertIsInstance(test_portfolio.portfolioDf, pd.DataFrame)
# Test inversion
test_portfolio.inversion = 1000
self.assertIsInstance(test_portfolio.inversion, int)
self.assertIs(test_portfolio.inversion, 1000)
# Test sharpeRatio
test_portfolio.sharpeRatio = pd.Series([1, 2, 3, 4])
self.assertIsInstance(test_portfolio.sharpeRatio, float)
self.assertEqual(round(test_portfolio.sharpeRatio, 2), 3.87)
def test_Getters(self):
test_Portfolio = Portfolio(a_name='pfolio')
test_asset1 = Asset('asset1', 'etf')
test_asset2 = Asset('asset1', 'fund')
test_Portfolio.myAssets = [test_asset1, test_asset2]
# Test Assets Number
self.assertEqual(test_Portfolio.assetsNumber, 2)
# Test getAssetByName
self.assertIsInstance(test_Portfolio.getAssetByName(a_name='asset1'),
Asset)
self.assertEqual(test_Portfolio. \
getAssetByName(a_name='asset1').assetName,
'asset1')
def test_setters(self):
test_portfolio = Portfolio(a_name='myPortfolio')
mydf = pd.DataFrame({'Data': [1, 2, 3], 'Other': [23, 32, 34]})
# Test AssetDF
with self.assertRaises(TypeError):
test_portfolio.portfolioDf = 'mydf'
with self.assertRaises(ValueError):
test_portfolio.portfolioDf = pd.DataFrame()
test_portfolio.portfolioDf = mydf
self.assertIsInstance(test_portfolio.portfolioDf, pd.DataFrame)
# Test Portfolio Name
self.assertEqual(test_portfolio.portFolioName, 'myPortfolio')
with self.assertRaises(TypeError):
test_portfolio.portFolioName = ['myname']
# Test my Assets
asset1 = Asset(a_name='myAsset1', assetType='etf')
asset2 = Asset(a_name='myAsset2', assetType='fund')
with self.assertRaises(TypeError):
test_portfolio.myAssets = asset1
with self.assertRaises(TypeError):
test_portfolio.myAssets = [asset1, 'asset2']
test_portfolio.myAssets = [asset1, asset2]
self.assertIsInstance(test_portfolio.myAssets, list)
self.assertIsInstance(test_portfolio.myAssets[0], Asset)
self.assertIsInstance(test_portfolio.myAssets[1], Asset)
# Test Initial Inversion
with self.assertRaises(TypeError):
test_portfolio.inversion = 0.25
with self.assertRaises(ValueError):
test_portfolio.inversion = 0
# Test Sharpe Ratio
myReturns = pd.Series([1.5, 2, 4.1, 5])
test_portfolio.sharpeRatio = myReturns
self.assertEqual(round(test_portfolio.sharpeRatio, 2), 3.77)
with self.assertRaises(TypeError):
test_portfolio.sharpeRatio = 3
def test_getters(self):
test_asset = Asset(a_name='myAsset', assetType='fund')
self.assertIs(test_asset.assetName, 'myAsset')
self.assertIs(test_asset.assetType, 'fund')
myDf = pd.DataFrame({'Col 1': [1, 2], 'Col 2': [3, 4]})
test_asset.assetDf = myDf
self.assertIsInstance(test_asset.assetDf, pd.DataFrame)
self.assertIs(test_asset.assetDf, myDf)
test_asset.allocation = 0.30
self.assertIsInstance(test_asset.allocation, float)
self.assertEqual(test_asset.allocation, 0.30)
test_asset.sharpeRatio = pd.Series([1, 2, 3, 4])
self.assertIsInstance(test_asset.sharpeRatio, float)
test_asset.initial_inversion = 1000
self.assertEqual(test_asset.initial_inversion, 1000)
def test_Constructor(self):
# Wrong type of assetType
with self.assertRaises(TypeError):
Asset(a_name='myAsset', assetType='an_etf')
# Wrong data type for assetType parameter
with self.assertRaises(TypeError):
Asset(a_name='myAsset', assetType=['test'])
# Wrong data type for a_name parameter
with self.assertRaises(TypeError):
Asset(a_name=2, assetType='etf')
# Wrong data type for assetType and a_name parameter
with self.assertRaises(TypeError):
Asset(a_name=2, assetType=['test'])
# No parameters in Constructor
with self.assertRaises(TypeError):
Asset()
test_asset = Asset(a_name='myAsset', assetType='fund')
self.assertIsInstance(test_asset, Asset)
self.assertIs(test_asset.assetName, 'myAsset')
self.assertIs(test_asset.assetType, 'fund')
def main():
euroStockIndex = Asset('eurozone-stock-index-inv-eur', 'fund')
euroStockIndex.initial_inversion = 1000
euroStockIndex.allocation = 0.25
ie00b246kl88 = Asset('ie00b246kl88', 'fund')
xetraGold = Asset('xetra-gold', 'etf')
lyxorAAAGov1_3yr = Asset('lyxor-euromts-aaa-gov-1-3-y', 'etf')
us500StockIndex = Asset('us-500-stock-index-inv-usd', 'fund')
dtla = Asset('dtla', 'etf')
swissGoldUSD = Asset('etfs-physical-swiss-gold-uk', 'etf')
isharesTreasuryUSD = Asset('ishares-treasury-bond-0-1yr-ucits', 'etf')
gobalStockIndexUSD = Asset('global-stock-index-ins-usd', 'fund')
gobalStockIndexUSD.allocation = 0.33
vanguardReit = Asset('vanguard-reit', 'etf')
vanguardReit.allocation = 0.33
vanguardTotalBondMarket = Asset('vanguard-total-bond-market', 'etf')
vanguardTotalBondMarket.allocation = 0.33
european_PP = Portfolio('European Permanent Portfolio')
european_PP.inversion = 4000
european_PP.myAssets = [
euroStockIndex, ie00b246kl88, xetraGold, lyxorAAAGov1_3yr
]
american_PP = Portfolio('American Permanent Portfolio')
american_PP.inversion = 4000
american_PP.myAssets = [
us500StockIndex, dtla, swissGoldUSD, isharesTreasuryUSD
]
talmud_pfolio = Portfolio('Talmud Portfolio')
talmud_pfolio.inversion = 3000
talmud_pfolio.myAssets = [
gobalStockIndexUSD, vanguardReit, vanguardTotalBondMarket
]
for folderName, portfolio in zip(
['EUR_PP', 'USA_PP', 'talmud_folio'],
[european_PP, american_PP, talmud_pfolio]):
runAssets(portfolio=portfolio,
folder=folderName,
fromDate='01/01/2020',
returnsUnit='Percentage')
def test_Setters(self):
test_asset = Asset(a_name='myAsset', assetType='fund')
test_asset.assetName = 'myAsset2'
test_asset.assetType = 'etf'
mydf = pd.DataFrame({'Data': [1, 2, 3], 'Other': [23, 32, 34]})
# Test AssetDF
with self.assertRaises(TypeError):
test_asset.assetDf = 'mydf'
with self.assertRaises(ValueError):
test_asset.assetDf = pd.DataFrame()
test_asset.assetDf = mydf
self.assertIsInstance(test_asset.assetDf, pd.DataFrame)
returns = [1, 2, 3, 4]
test_asset.assetStdDeviation = returns
# Test asset Name
self.assertEqual(test_asset.assetName, 'myAsset2')
with self.assertRaises(TypeError):
test_asset.assetName = ['myname']
# Test asset Type
self.assertEqual(test_asset.assetType, 'etf')
with self.assertRaises(TypeError):
test_asset.assetType = ['myname']
with self.assertRaises(ValueError):
test_asset.assetType = 'etf2'
# Test Allocation
with self.assertRaises(TypeError):
test_asset.allocation = 1000
with self.assertRaises(ValueError):
test_asset.allocation = 0.0
# Test Initial Inversion
with self.assertRaises(TypeError):
test_asset.initial_inversion = 0.25
with self.assertRaises(ValueError):
test_asset.initial_inversion = 0
# Test Sharpe Ratio
myReturns = pd.Series([1.5, 2, 4.1, 5])
test_asset.sharpeRatio = myReturns
self.assertEqual(round(test_asset.sharpeRatio, 2), 3.77)
with self.assertRaises(TypeError):
test_asset.sharpeRatio = 3