def test_compute_portfolio_value(self):
assets = {
'XXX': Asset(1, 20, 1.5, 'XXX'),
'YYY': Asset(4, 20, 1.5, 'yyy')
}
fund = Fund('F1', {'XXX': 10, 'YYY': 10}, 5, 2, 3)
self.assertEqual(50, fund.compute_portfolio_value(assets))
def test_get_orders(self):
assets = {
'XXX': Asset(1, 20, 1.5, 'XXX'),
'YYY': Asset(1, 20, 1.5, 'yyy')
}
fund = Fund('F1', {'XXX': 5, 'YYY': 4}, 5, 2, 0.25)
self.assertEqual(fund.get_orders(assets), [])
def test_run_intraday_simulation_raises_exception_for_price_reduction(
self):
a0 = Asset(price=1, daily_volume=40, volatility=1.5, symbol='a0')
a1 = Asset(price=2, daily_volume=40, volatility=1.5, symbol='a1')
f0 = Fund('f0', {'a0': 10},
initial_capital=2,
initial_leverage=8,
tolerance=2)
f1 = Fund('f1', {
'a0': 10,
'a1': 1
},
initial_capital=1,
initial_leverage=1,
tolerance=3)
network = AssetFundsNetwork({
'f0': f0,
'f1': f1
}, {
'a0': a0,
'a1': a1
}, MockMarketImpactTestCalculator())
with self.assertRaises(ValueError):
network.run_intraday_simulation(0.8, 0.7)
def test_get_canonical_form(self):
a0 = Asset(price=1, daily_volume=40, volatility=1.5, symbol='a0')
a1 = Asset(price=2, daily_volume=40, volatility=1.5, symbol='a1')
f0 = Fund('f0', {'a0': 10},
initial_capital=2,
initial_leverage=8,
tolerance=2)
f1 = Fund('f1', {
'a0': 10,
'a1': 10
},
initial_capital=1,
initial_leverage=1,
tolerance=3)
network = AssetFundsNetwork({
'f0': f0,
'f1': f1
}, {
'a0': a0,
'a1': a1
}, MockMarketImpactTestCalculator())
expected_canonical_form = np.array([[10., 0.], [10., 20.]])
actual_canonical_form = network.get_canonical_form()
self.assertTrue(
np.array_equal(expected_canonical_form, actual_canonical_form))
def test_update_funds(self):
assets = {
'XXX': Asset(1, 20, 1.5, 'XXX'),
'YYY': Asset(1, 20, 1.5, 'yyy')
}
f1 = Fund('F1', {'XXX': 10, 'YYY': 10}, 5, 2, 0.25)
f2 = Fund('F1', {'XXX': 5, 'YYY': 4}, 5, 2, 0.25)
f3 = Fund('F1', {'XXX': 20, 'YYY': 4}, 5, 2, 4)
network = AssetFundsNetwork({
'f1': f1,
'f2': f2,
'f3': f3
}, assets, MockMarketImpactTestCalculator())
network.update_funds()
self.assertTrue(f1.is_in_margin_call())
self.assertFalse(f1.default())
self.assertTrue(f2.is_in_margin_call())
self.assertTrue(f2.default())
self.assertFalse(f3.is_in_margin_call())
self.assertFalse(f3.default())
"""a0 = Asset(price=1, daily_volume=40, volatility=1.5, symbol='a0')
def test_marginal_call_true(self):
assets = {
'XXX': Asset(1, 20, 1.5, 'XXX'),
'YYY': Asset(1, 20, 1.5, 'yyy')
}
fund = Fund('F1', {'XXX': 10, 'YYY': 10}, 5, 2, 3)
self.assertTrue(True, fund.marginal_call(assets))
def test_compute_compute_curr_leverage(self):
assets = {
'XXX': Asset(1, 20, 1.5, 'XXX'),
'YYY': Asset(4, 20, 1.5, 'yyy')
}
fund = Fund('F1', {'XXX': 10, 'YYY': 10}, 5, 2, 3)
self.assertEqual(0.25, fund.compute_curr_leverage(assets))
def test_read_two_assets_from_file(self):
assets = AssetFundNetwork.read_assets_file(
'../../resources/assets.csv', 2)
expected_assets = {
'A1': Asset(price=145.6, daily_volume=605.3, symbol='A1'),
'A2': Asset(price=100, daily_volume=10, symbol='A2')
}
self.assertEqual(len(assets), 2)
self.assertEqual(assets, expected_assets)
def test_update_state_margin_only(self):
assets = {
'XXX': Asset(1, 20, 1.5, 'XXX'),
'YYY': Asset(1, 20, 1.5, 'yyy')
}
fund = Fund('F1', {'XXX': 10, 'YYY': 10}, 5, 2, 0.25)
fund.update_state(assets)
self.assertTrue(fund.is_in_margin_call())
self.assertFalse(fund.default())
def test_get_single_orders(self):
assets = {'a1': Asset(10, 100, 'a1'), 'a2': Asset(20, 200, 'a2')}
expected_sell_orders = [Sell('a1', 10), Sell('a2', 20)]
expected_buy_orders = [Buy('a1', 10), Buy('a2', 20)]
actions_mgr = ActionsManager(assets, 0.1)
actual_buy_orders = actions_mgr._ActionsManager__get_single_orders(
assets, ActionsManager._ActionsManager__gen_buy_order)
actual_sell_orders = actions_mgr._ActionsManager__get_single_orders(
assets, ActionsManager._ActionsManager__gen_sell_order)
self.assertListEqual(expected_sell_orders, actual_sell_orders)
self.assertListEqual(expected_buy_orders, actual_buy_orders)
def test_gen_liquidation_orders(self):
SysConfig.set("MINUTE_VOLUME_LIMIT", 0.1)
assets = {
'XXX': Asset(2, 3900, 1.5, 'XXX'),
'YYY': Asset(1, 7900, 1.5, 'yyy'),
'ZZZ': Asset(1, 7900, 1.5, 'yyy')
}
fund = Fund('F1', {'XXX': 10, 'YYY': 11, 'ZZZ': 2}, 5, 2, 0.25)
expected_orders = [Sell('XXX', 1), Sell('YYY', 2), Sell('ZZZ', 2)]
expected_portfolio = {'XXX': 9, 'YYY': 9}
orders = fund.gen_liquidation_orders(assets)
self.assertEqual(orders, expected_orders)
self.assertEqual(fund.portfolio, expected_portfolio)
def test_gen_network_from_graph_with_assets(self):
num_funds = 2
assets = {
'A1': Asset(price=1, daily_volume=3, symbol='A1', volatility=1.5),
'A2': Asset(price=2, daily_volume=4, symbol='A2', volatility=1)
}
initial_capitals = [100, 200]
initial_leverages = [1, 2]
tolerances = [4, 5]
investment_proportions = {'f0': [0.6, 0.4], 'f1': [1.0]}
g = nx.DiGraph()
g.add_nodes_from([0, 1, 2, 3])
g.add_edges_from([(0, 2), (0, 3), (1, 3)])
network = AssetFundsNetwork.gen_network_from_graph_with_assets(
g=g,
investment_proportions=investment_proportions,
initial_capitals=initial_capitals,
initial_leverages=initial_leverages,
tolerances=tolerances,
assets=assets,
mi_calc=ExponentialMarketImpactCalculator(1))
assets = network.assets
funds = network.funds
self.assertEqual(len(assets), 2)
self.assertEqual(len(funds), num_funds)
self.assertTrue((network.assets, assets))
for i in range(len(funds)):
fund = funds['f' + str(i)]
self.assertEqual(initial_capitals[i], fund.initial_capital)
self.assertEqual(initial_leverages[i], fund.initial_leverage)
self.assertEqual(tolerances[i], fund.tolerance)
prot0 = funds['f0'].portfolio
self.assertEqual(len(prot0.items()), 2)
self.assertEqual(prot0['A1'], 120)
self.assertEqual(prot0['A2'], 40)
prot1 = funds['f1'].portfolio
self.assertEqual(len(prot1.items()), 1)
self.assertEqual(prot1['A2'], 300)
self.assertTrue('A1' not in prot1)
def test_run_intraday_simulation_goal_leverage_reached(self):
a0 = Asset(price=1, daily_volume=40, volatility=1.5, symbol='a0')
a1 = Asset(price=2, daily_volume=40, volatility=1.5, symbol='a1')
f0 = Fund('f0', {'a0': 10},
initial_capital=2,
initial_leverage=8,
tolerance=2)
f1 = Fund('f1', {
'a0': 10,
'a1': 1
},
initial_capital=1,
initial_leverage=1,
tolerance=3)
assets = {'a0': a0, 'a1': a1}
network = AssetFundsNetwork({
'f0': f0,
'f1': f1
}, assets, MockMarketImpactTestCalculator())
network.run_intraday_simulation(2, 0.8)
self.assertTrue(f0.compute_curr_leverage(assets) <= 0.8)
self.assertTrue(f1.compute_curr_leverage(assets) <= 0.8)
def test_run_intraday_simulation_price_rises(self):
a0 = Asset(price=1, daily_volume=40, volatility=1.5, symbol='a0')
a1 = Asset(price=2, daily_volume=40, volatility=1.5, symbol='a1')
f0 = Fund('f0', {'a0': 10},
initial_capital=2,
initial_leverage=8,
tolerance=2)
f1 = Fund('f1', {
'a0': 10,
'a1': 1
},
initial_capital=1,
initial_leverage=1,
tolerance=3)
network = AssetFundsNetwork({
'f0': f0,
'f1': f1
}, {
'a0': a0,
'a1': a1
}, MockMarketImpactTestCalculator())
network.run_intraday_simulation(1.5, 1)
self.assertTrue(a0.price >= 1)
self.assertTrue(a1.price >= 2)
def test_updated_price_buy_exp(self):
calc = ExponentialMarketImpactCalculator(2)
a = Asset(price=2, daily_volume=100, volatility=1.5, symbol='a1')
updated_price = calc.get_updated_price(10, a, 1)
npt.assert_almost_equal(2.4428, updated_price, decimal=4)
def test_market_impact_sell_order_exp(self):
calc = ExponentialMarketImpactCalculator(2)
a = Asset(price=2, daily_volume=100, volatility=1.5, symbol='a1')
order = Sell('a1', 10)
mi = calc.get_market_impact(order, a)
npt.assert_almost_equal(0.8187, mi, decimal=4)
def test_updated_price_sell_sqrt(self):
calc = SqrtMarketImpactCalculator(0.5)
a = Asset(price=2, daily_volume=1000, volatility=1.5, symbol='a1')
order = Sell('a1', 10)
mi = calc.get_updated_price(order.num_shares, a, -1)
npt.assert_almost_equal(1.925, mi, decimal=4)
def test_market_impact_sell_sqrt(self):
calc = SqrtMarketImpactCalculator(0.5)
a = Asset(price=2, daily_volume=1000, volatility=1.5, symbol='a1')
order = Sell('a1', 10)
mi = calc.get_market_impact(order, a)
npt.assert_almost_equal(-0.075, mi, decimal=4)
def test_updated_price_sell_exp(self):
calc = ExponentialMarketImpactCalculator(2)
a = Asset(price=2, daily_volume=100, volatility=1.5, symbol='a1')
mi = calc.get_updated_price(10, a, -1)
npt.assert_almost_equal(1.6374, mi, decimal=4)
def test_set_price(self):
asset = Asset(2, 100, 1.5, 'a1')
asset.set_price(3)
self.assertEqual(3, asset.price)