def test_dividends_multiple_assets(self):
start_date = date(1986, 12, 31)
end_date = date(2019, 12, 31)
msft_vals = self.msft_vals.reindex(pd.date_range(start_date, end_date)).ffill()
msft_dividends = self.msft_dividends.reindex(
pd.date_range(start_date, end_date)
).dropna()
aapl_vals = self.aapl_vals.reindex(pd.date_range(start_date, end_date)).ffill()
aapl_dividends = self.aapl_dividends.reindex(
pd.date_range(start_date, end_date)
).dropna()
assets = [
anda.Asset("MSFT", Decimal("0.5"), msft_vals, msft_dividends),
anda.Asset("AAPL", Decimal("0.5"), aapl_vals, aapl_dividends),
]
strategy = anda.Strategy(
start_date,
end_date,
self.starting_balance,
assets,
self.contribution_dates,
self.contribution_amount,
self.rebalancing_dates,
)
self.assertAlmostEqual(
anda.total_return(strategy)[end_date], Decimal("9856511.60"), delta=1
)
def test_sortino_ratio_multi_asset(self):
start_date = date(1989, 12, 29)
end_date = date(2000, 12, 29)
msft_vals = self.msft_vals.reindex(pd.date_range(start_date, end_date)).ffill()
berkshire_vals = self.berkshire_vals.reindex(
pd.date_range(start_date, end_date)
).ffill()
risk_free_vals = (
self.risk_free_vals.dropna()["Close"]
.reindex(pd.date_range(start_date, end_date))
.ffill()
)
assets = [
anda.Asset("MSFT", Decimal(0.6), msft_vals),
anda.Asset("BRK-A", Decimal(0.4), berkshire_vals),
]
strategy = anda.Strategy(
start_date,
end_date,
self.starting_balance,
assets,
self.contribution_dates,
self.contribution_amount,
self.rebalancing_dates,
)
self.assertAlmostEqual(
anda.sortino_ratio(strategy, risk_free_vals), Decimal("1.56"), delta=0.2
)
def test_mult_assets(self):
starting_balance = Decimal("100.00")
contribution_dates = set()
contribution_amount = Decimal("0.0")
rebalancing_dates = set()
assets = [
anda.Asset("GOLD", Decimal("0.4"), self.gold_data),
anda.Asset("SLV", Decimal("0.6"), self.silver_data),
]
strategy = anda.Strategy(
self.start,
self.end,
starting_balance,
assets,
contribution_dates,
contribution_amount,
rebalancing_dates,
)
roi = anda.total_return(strategy)
self.assertEqual(roi[self.start], Decimal("100.00"))
self.assertEqual(roi[self.start + timedelta(days=14)], Decimal("220.40"))
self.assertEqual(roi[self.end], Decimal("320.40"))
def get_assets(tickers, proportions, start_date, end_date):
"""
Gets data for each ticker and puts it in an anda.Asset.
Returns a list of all assets.
"""
assert len(tickers) == len(proportions)
data = util.get_data(tickers, start_date, end_date)
data = data.rename(columns={
"AOpen": "Open",
"AClose": "Close",
"ALow": "Low",
"AHigh": "High"
})
if data.empty:
# raise error
return None
assets = []
for tick, prop in zip(tickers, proportions):
asset_data = data[(data.AssetTicker == tick)]
only_market_data = asset_data[[
"ADate", "Open", "Close", "Low", "High"
]]
only_market_data.index = only_market_data["ADate"]
assets.append(anda.Asset(tick, prop, only_market_data))
return assets
def test_msft(self):
start_date = date(1986, 3, 13)
end_date = date(2019, 1, 1)
msft_vals = self.msft_vals.reindex(pd.date_range(start_date, end_date)).ffill()
msft_dividends = self.msft_dividends.reindex(
pd.date_range(start_date, end_date)
).dropna()
assets = [anda.Asset("MSFT", Decimal("1.0"), msft_vals, msft_dividends)]
strategy = anda.Strategy(
start_date,
end_date,
self.starting_balance,
assets,
self.contribution_dates,
self.contribution_amount,
self.rebalancing_dates,
)
annual_returns = anda.relative_yearly_returns(strategy)
expected = [
# (year, change)
(1987, Decimal("125")),
(1988, Decimal("-2")),
(2000, Decimal("-63")),
(2001, Decimal("53")),
(2002, Decimal("-22")),
(2003, Decimal("7")),
(2017, Decimal("41")),
(2018, Decimal("21")),
]
for year, change in expected:
self.assertAlmostEqual(
annual_returns.at[date(year, 1, 1)], change, delta=Decimal("0.5")
)
def test_short_time(self):
start_date = date(1989, 1, 4)
end_date = date(1989, 12, 31)
self.msft_vals = self.msft_vals.reindex(
pd.date_range(start_date, end_date)
).ffill()
assets = [
anda.Asset("MSFT", Decimal("1.0"), self.msft_vals),
]
strategy = anda.Strategy(
start_date,
end_date,
self.starting_balance,
assets,
self.contribution_dates,
self.contribution_amount,
self.rebalancing_dates,
)
self.assertRaises(anda.InsufficientTimeframe, lambda: anda.best_year(strategy))
self.assertRaises(anda.InsufficientTimeframe, lambda: anda.worst_year(strategy))
self.assertRaises(
anda.InsufficientTimeframe, lambda: anda.best_year_no(strategy)
)
self.assertRaises(
anda.InsufficientTimeframe, lambda: anda.worst_year_no(strategy)
)
def test_simple(self):
start_date = date(1989, 1, 4)
end_date = date(2010, 1, 1)
self.msft_vals = self.msft_vals.reindex(
pd.date_range(start_date, end_date)
).ffill()
assets = [
anda.Asset("MSFT", Decimal("1.0"), self.msft_vals),
]
strategy = anda.Strategy(
start_date,
end_date,
self.starting_balance,
assets,
self.contribution_dates,
self.contribution_amount,
self.rebalancing_dates,
)
b = anda.best_year(strategy)
w = anda.worst_year(strategy)
self.assertAlmostEqual(b, Decimal("120"), delta=2)
self.assertAlmostEqual(w, Decimal("-63"), delta=2)
self.assertAlmostEqual(b, Decimal("122"), delta=Decimal("0.5"))
self.assertAlmostEqual(w, Decimal("-63"), delta=Decimal("0.5"))
b_year = anda.best_year_no(strategy)
w_year = anda.worst_year_no(strategy)
self.assertEqual(b_year, 1991)
self.assertEqual(w_year, 2000)
def test_sortino_ratio_single_asset(self):
start_date = date(1986, 12, 31)
end_date = date(2019, 12, 31)
msft_vals = self.msft_vals.reindex(pd.date_range(start_date, end_date)).ffill()
risk_free_vals = (
self.risk_free_vals.dropna()["Close"]
.reindex(pd.date_range(start_date, end_date))
.ffill()
)
assets = [anda.Asset("MSFT", Decimal(1.0), msft_vals)]
strategy = anda.Strategy(
start_date,
end_date,
self.starting_balance,
assets,
self.contribution_dates,
self.contribution_amount,
self.rebalancing_dates,
)
self.assertAlmostEqual(
anda.sortino_ratio(strategy, risk_free_vals), Decimal("1.34"), delta=0.1
)
def get_strategy(
tickers,
proportions,
handles,
start_date,
end_date,
input_money,
contribution_amount,
contribution_dates,
rebalancing_dates,
):
"""
Initializes and returns strategy object
"""
weights = [p for p in proportions if p is not None]
normalise(weights)
# Separate user-supplied data from Thalia-known data.
user_assets = []
thalia_tickers = []
thalia_weights = []
for ticker, weight, handle in zip(tickers, weights, handles):
if handle is None:
thalia_tickers.append(ticker)
thalia_weights.append(weight)
else:
user_assets.append((ticker, weight, handle))
thalia_data = get_assets(thalia_tickers, thalia_weights, start_date,
end_date)
if thalia_data is None:
# raise error
return None
user_supplied_data = [
anda.Asset(ticker, weight, user_csv.retrieve(handle))
for ticker, weight, handle in user_assets
]
all_asset_data = user_supplied_data + thalia_data
real_start_date = max(asset.values.index[0] for asset in all_asset_data)
real_end_date = min(asset.values.index[-1] for asset in all_asset_data)
if real_end_date < real_start_date:
# raise error
return None
strategy = anda.Strategy(
real_start_date,
real_end_date,
input_money,
all_asset_data,
contribution_dates,
contribution_amount,
rebalancing_dates,
)
return strategy
def test_max_drawdown_multi_asset(self):
start_date = date(1989, 12, 29)
end_date = date(2000, 12, 29)
msft_vals = self.msft_vals.reindex(pd.date_range(start_date, end_date)).ffill()
berkshire_vals = self.berkshire_vals.reindex(
pd.date_range(start_date, end_date)
).ffill()
assets = [
anda.Asset("MSFT", Decimal(0.6), msft_vals),
anda.Asset("BRK-A", Decimal(0.4), berkshire_vals),
]
strategy = anda.Strategy(
start_date,
end_date,
self.starting_balance,
assets,
self.contribution_dates,
self.contribution_amount,
self.rebalancing_dates,
)
self.assertAlmostEqual(anda.max_drawdown(strategy), Decimal("59.03"), delta=3)
def test_rebalancing(self):
# TODO
starting_balance = Decimal("10000.00")
contribution_dates = set()
contribution_amount = Decimal("0.0")
rebalancing_dates = self.dates
assets = [
anda.Asset("GOLD", Decimal("0.5"), self.gold_data),
anda.Asset("SLV", Decimal("0.5"), self.silver_data),
]
strategy = anda.Strategy(
self.start,
self.end,
starting_balance,
assets,
contribution_dates,
contribution_amount,
rebalancing_dates,
)
roi = anda.total_return(strategy)
roi # gotta keep flake8 happy.
def test_max_drawdown_single_asset(self):
start_date = date(1986, 12, 31)
end_date = date(2019, 12, 31)
msft_vals = self.msft_vals.reindex(pd.date_range(start_date, end_date)).ffill()
assets = [anda.Asset("MSFT", Decimal("1.0"), msft_vals)]
strategy = anda.Strategy(
start_date,
end_date,
self.starting_balance,
assets,
self.contribution_dates,
self.contribution_amount,
self.rebalancing_dates,
)
self.assertAlmostEqual(anda.max_drawdown(strategy), Decimal("72.33"), delta=2.5)
def test_single_asset(self):
starting_balance = Decimal("23.46")
contribution_dates = set()
contribution_amount = None
rebalancing_dates = set()
assets = [anda.Asset("Gold", Decimal("1.0"), self.gold_data)]
strategy = anda.Strategy(
self.start,
self.end,
starting_balance,
assets,
contribution_dates,
contribution_amount,
rebalancing_dates,
)
roi = anda.total_return(strategy)
self.assertEqual(roi.at[self.start], Decimal("23.46"))
self.assertEqual(roi.at[date(2000, 1, 12)], Decimal("24.75"))
self.assertEqual(roi.at[self.end], Decimal("25.69"))
def test_no_money(self):
starting_balance = Decimal("0.00")
contribution_dates = pd.date_range(
self.start, self.end, freq=timedelta(days=4)
)[1:]
contribution_amount = Decimal("1000.00")
rebalancing_dates = set()
assets = [anda.Asset("ST", Decimal("1.0"), self.rock_data)]
strategy = anda.Strategy(
self.start,
self.end,
starting_balance,
assets,
contribution_dates,
contribution_amount,
rebalancing_dates,
)
roi = anda.total_return(strategy)
roi # Just the lack of exception *should* be a sign of success.
def test_contribution(self):
starting_balance = Decimal("1.00")
contribution_dates = self.dates
contribution_amount = Decimal("1.00")
rebalancing_dates = set()
assets = [anda.Asset("ST", Decimal("1.00"), self.rock_data)]
strategy = anda.Strategy(
self.start,
self.end,
starting_balance,
assets,
contribution_dates,
contribution_amount,
rebalancing_dates,
)
roi = anda.total_return(strategy)
self.assertEqual(Decimal("2.00"), roi.at[self.start])
for (day, next_day) in zip(self.dates, self.dates[1:]):
self.assertEqual(roi[day] + Decimal("1.00"), roi[next_day])
def test_dividends_single_asset(self):
start_date = date(1986, 12, 31)
end_date = date(2019, 12, 31)
msft_vals = self.msft_vals.reindex(pd.date_range(start_date, end_date)).ffill()
msft_dividends = self.msft_dividends.reindex(
pd.date_range(start_date, end_date)
).dropna()
assets = [anda.Asset("MSFT", Decimal("1.0"), msft_vals, msft_dividends)]
strategy = anda.Strategy(
start_date,
end_date,
self.starting_balance,
assets,
self.contribution_dates,
self.contribution_amount,
self.rebalancing_dates,
)
self.assertAlmostEqual(
anda.total_return(strategy)[end_date], Decimal("14599199.22"), delta=1
)
