def setUpClass(cls):
cls.writer = writer("tmp_J32JFASDK", host="mongo")
cls.reader = reader("tmp_J32JFASDK", host="mongo")
# write assets into test database. Writing is slow!
cls.writer.update_assets(frame=read_frame("price.csv", parse_dates=True))
cls.writer.update_symbols(frame=read_frame("symbols.csv"))
cls.writer.update_portfolio("test", test_portfolio(), group="test")
def setUpClass(cls):
cls.writer = writer("tmp_JKJFDAFJJKFD", host="mongo")
cls.reader = reader("tmp_JKJFDAFJJKFD", host="mongo")
# write assets into test database. Writing is slow!
assets = read_frame("price.csv", parse_dates=True)
for asset in assets:
cls.writer.update_asset(asset, assets[asset])
frame = read_frame("symbols.csv")
cls.writer.update_symbols(frame)
p = test_portfolio()
cls.writer.update_portfolio("test", p, group="test", comment="test")
def test_transaction_report(self):
x = test_portfolio()
p1 = x.iron_threshold(threshold=0.05)
y = p1.transaction_report()
yy = read_frame("report.csv", index_col=[0, 1])
yy.index.names = [None, None]
pdt.assert_frame_equal(y, yy)
def test_build(self):
prices = read_frame("price.csv")
weights = pd.DataFrame(index=prices.index, data=0.1, columns=prices.keys())
portfolio = Portfolio(prices, weights)
# self.assertEqual(portfolio.index[0], pd.Timestamp('2013-01-01'))
self.assertAlmostEqual(portfolio.weights["B"][pd.Timestamp('2013-01-08')], 0.1, places=5)
def test_dcc(self):
frame = read_frame(name="price_data.csv")
vola = volatility(prices=frame)
volaAdj = volatility_adj_returns(prices=frame, volatility=vola)
dcc = DCC(volAdjReturns=volaAdj)
mat = dcc[pd.Timestamp("2013-10-09")]
self.assertAlmostEqual(mat["G"]["A"], 0.094022481720826195, places=10)
def test_portfolio(self):
portfolio = test_portfolio()
self.writer.update_symbols(frame=read_frame("symbols.csv", parse_dates=False))
self.writer.update_portfolio("test", portfolio, "test-group")
# self.archive.update_portfolio("test", portfolio, "test-group", n=10)
g = self.reader.portfolios["test"]
pdt.assert_frame_equal(portfolio.prices, g.prices)
pdt.assert_frame_equal(portfolio.weights, g.weights)
def test_master(self):
con = Configuration(self.writer, t0=pd.Timestamp("2013-01-01"))
self.assertEqual(con.name, "test")
self.assertEquals(con.group, "testgroup")
p = con.prices(assets=["A","B"])
pdt.assert_frame_equal(p[["A","B"]], read_frame("price.csv")[["A","B"]].truncate(before=pd.Timestamp("2013-01-01")), check_less_precise=True)
portfolio=con.portfolio()
self.assertAlmostEquals(portfolio.nav.statistics.sharpe, -0.017204147680543617, places=5)
def test_table(self):
s = read_series("ts.csv", parse_dates=True)
pdt.assert_almost_equal(
monthlytable(s), read_frame("monthtable.csv", parse_dates=False))
def test_monthlytable(self):
f = 100 * monthlytable(ts)
f = f[f.index >= 2008]
pdt.assert_frame_equal(f, read_frame("month.csv", parse_dates=False))
def setUpClass(cls):
cls.assets = read_frame("price.csv")
def test_csv(self):
reader = CsvArchive()
reader.put(name="price", frame=read_frame("price.csv", parse_dates=True))
a=reader.history(["A","B","C"], name="price", before=pd.Timestamp("2014-01-01"))
self.assertAlmostEqual(a["A"][pd.Timestamp("2014-01-01")], 1200.90, places=6)
def test_portfolio(self):
prices = read_frame("price_data.csv")
cashpos = pd.DataFrame(index=prices.index, columns=prices.columns, data=50000)
portfolio = Portfolio(prices=prices, cashPos=cashpos, size=1e6)
self.assertAlmostEqual(portfolio.nav.sharpe_ratio(), 0.286338249832, places=10)
def test_frame2html(self):
x = frame2html(read_frame("price.csv"), name="maffay")
self.assertTrue(x)
def test_sector_weights(self):
x = portfolio.sector_weights(pd.Series({"A": "A", "B": "A", "C": "B", "D": "B",
"E": "C", "F": "C", "G": "C"}))
pdt.assert_frame_equal(x.head(10), read_frame("sector_weights.csv", parse_dates=True))
def setUpClass(cls):
cls.writer = writer("tmp_ZHJKJFA8", host="mongo")
cls.writer.update_assets(read_frame("price.csv", parse_dates=True))
