def test_get_possible_defenses(self):
a1 = AssetFundNetwork.Asset(price=1, daily_volume=10, symbol='a1')
a2 = AssetFundNetwork.Asset(price=2, daily_volume=4, symbol='a2')
a3 = AssetFundNetwork.Asset(price=7, daily_volume=2, symbol='a3')
f1 = Fund('f1', {'a1': 10, 'a2': 10, 'a3': 10}, 100, 1, 1)
f2 = Fund('f2', {'a1': 10}, 100, 1, 1)
SysConfig.set("STEP_ORDER_SIZE", 0.5)
network = AssetFundNetwork.AssetFundsNetwork(
funds={
'f1': f1,
'f2': f2
},
assets={
'a1': a1,
'a2': a2,
'a3': a3
},
mi_calc=MockMarketImpactTestCalculator())
actual_orders = get_possible_defenses(network, 10)
expected_orders = []
expected_orders.append(([Buy('a1', 5)], 5))
expected_orders.append(([Buy('a2', 2)], 4))
expected_orders.append(([Buy('a3', 1)], 7))
expected_orders.append(([Buy('a1', 5), Buy('a2', 2)], 9))
expected_orders.append(([], 0))
actual_orders.sort(key=operator.itemgetter(1))
expected_orders.sort(key=operator.itemgetter(1))
self.assertEqual(len(actual_orders), len(expected_orders))
for i in range(0, len(actual_orders)):
actual_orders[i][0].sort(key=lambda x: x.asset_symbol)
expected_orders[i][0].sort(key=lambda x: x.asset_symbol)
self.assertListEqual(actual_orders[i][0], expected_orders[i][0])
self.assertEqual(actual_orders[i][1], expected_orders[i][1])
def test_constructor(self):
a1 = AssetFundNetwork.Asset(price=1, daily_volume=100, symbol='a1')
a2 = AssetFundNetwork.Asset(price=2, daily_volume=200, symbol='a2')
a3 = AssetFundNetwork.Asset(price=3, daily_volume=300, symbol='a3')
assets = {'a1': a1, 'a2': a2, 'a3': a3}
mgr = ActionsManager(assets, 0.1)
sell_all_assets = [Sell('a1', 10), Sell('a2', 20), Sell('a3', 30)]
portfolio_dict = {
10: [Attack([Sell('a1', 10)], 10)],
40: [Attack([Sell('a2', 20)], 40)],
90: [Attack([Sell('a3', 30)], 90)],
50: [Attack([Sell('a1', 10), Buy('a2', 20)], 50)],
100: [Attack([Sell('a1', 10), Buy('a3', 30)], 100)],
130: [Attack([Sell('a2', 20), Buy('a3', 30)], 130)],
140:
[Attack(
[Sell('a1', 10), Sell('a2', 20),
Buy('a3', 30)], 140)],
0: [Attack([], 0)]
}
self.assertEqual(mgr._ActionsManager__step_order_size, 0.1)
self.assertDictEqual({
1: 'a1',
2: 'a2',
3: 'a3'
}, mgr._ActionsManager__id_to_sym)
self.assertDictEqual(portfolio_dict,
mgr._ActionsManager__portfolios_dict)
self.assertListEqual([0, 10, 40, 50, 90, 100, 130, 140],
list(mgr._ActionsManager__sorted_keys))
self.assertListEqual(sell_all_assets,
mgr._ActionsManager__sell_all_assets)
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_get_possible_defenses_integ(self):
a1 = AssetFundNetwork.Asset(price=1, daily_volume=100, symbol='a1')
a2 = AssetFundNetwork.Asset(price=2, daily_volume=100, symbol='a2')
a3 = AssetFundNetwork.Asset(price=3, daily_volume=100, symbol='a3')
a4 = AssetFundNetwork.Asset(price=1, daily_volume=100, symbol='a4')
f1 = Fund('f1', {'a1': 10, 'a2': 10, 'a3': 10}, 100, 1, 1)
f2 = Fund('f2', {'a4': 10}, 100, 1, 1)
network = AssetFundNetwork.AssetFundsNetwork(
funds={
'f1': f1,
'f2': f2
},
assets={
'a1': a1,
'a2': a2,
'a3': a3,
'a4': a4
},
mi_calc=MockMarketImpactTestCalculator())
actions_mgr = ActionsManager(network.assets, 0.1)
history = {BUY: {'a1': 2}, SELL: {'a1': 1, 'a2': 2}}
budget = 20
actions_mgr._ActionsManager__funds_under_risk = MagicMock(
return_value=['f1'])
actual_defenses = actions_mgr.get_possible_defenses(
network, budget, history)
self.assertListEqual(actual_defenses, [([Buy('a2', 10)], 20), ([], 0)])
actions_mgr._ActionsManager__funds_under_risk.assert_called_once_with(
network)
def test_simulate_trade_sell_orders_in_buy_command(self):
a1 = AssetFundNetwork.Asset(price=1, daily_volume=1, symbol='a1')
a2 = AssetFundNetwork.Asset(price=2, daily_volume=1, symbol='a2')
f1 = Fund('f1', {'a1': 10}, 100, 1, 1)
f2 = Fund('f2', {'a2': 10}, 100, 1, 1)
mi_calc = MarketImpactCalculator()
mi_calc.get_updated_price = MagicMock()
network = AssetFundNetwork.AssetFundsNetwork(funds={
'f1': f1,
'f2': f2
},
assets={
'a1': a1,
'a2': a2
},
mi_calc=mi_calc,
limit_trade_step=False)
exception = False
try:
network.submit_buy_orders([Buy('a1', 2), Sell('a1', 2)])
except TypeError:
exception = True
mi_calc.get_updated_price.assert_not_called()
self.assertTrue(exception)
def test_simulate_trade_sell_more_than_buy(self):
a1 = AssetFundNetwork.Asset(price=1, daily_volume=1, symbol='a1')
a2 = AssetFundNetwork.Asset(price=2, daily_volume=1, symbol='a2')
f1 = Fund('f1', {'a1': 10}, 100, 1, 1)
f2 = Fund('f2', {'a2': 10}, 100, 1, 1)
mi_calc = MarketImpactCalculator()
mi_calc.get_updated_price = MagicMock(return_value=0.5)
network = AssetFundNetwork.AssetFundsNetwork(funds={
'f1': f1,
'f2': f2
},
assets={
'a1': a1,
'a2': a2
},
mi_calc=mi_calc,
limit_trade_step=False)
network.submit_buy_orders([Buy('a1', 2)])
network.submit_sell_orders([Sell('a1', 3)])
log = network.simulate_trade()
self.assertDictEqual({'a1': '1->0.5'}, log)
mi_calc.get_updated_price.assert_called_once_with(1, a1, -1)
self.assertFalse(network.buy_orders)
self.assertFalse(network.sell_orders)
self.assertTrue(a1.price == 0.5)
self.assertTrue(a2.price == 2)
def test_simulate_trade_buy_equals_sell(self):
a1 = AssetFundNetwork.Asset(price=1, daily_volume=1, symbol='a1')
a2 = AssetFundNetwork.Asset(price=2, daily_volume=1, symbol='a2')
f1 = Fund('f1', {'a1': 10}, 100, 1, 1)
f2 = Fund('f2', {'a2': 10}, 100, 1, 1)
mi_calc = MarketImpactCalculator()
mi_calc.get_updated_price = MagicMock()
network = AssetFundNetwork.AssetFundsNetwork(funds={
'f1': f1,
'f2': f2
},
assets={
'a1': a1,
'a2': a2
},
mi_calc=mi_calc,
limit_trade_step=False)
network.submit_buy_orders([Buy('a1', 3)])
network.submit_sell_orders([Sell('a1', 3)])
log = network.simulate_trade()
mi_calc.get_updated_price.assert_not_called()
self.assertFalse(log)
self.assertFalse(network.buy_orders)
self.assertFalse(network.sell_orders)
self.assertTrue(a1.price == 1)
self.assertTrue(a2.price == 2)
def test_simulate_trade_mix_trades(self):
a1 = AssetFundNetwork.Asset(price=1, daily_volume=1, symbol='a1')
a2 = AssetFundNetwork.Asset(price=2, daily_volume=1, symbol='a2')
f1 = Fund('f1', {'a1': 10}, 100, 1, 1)
f2 = Fund('f2', {'a2': 10}, 100, 1, 1)
mi_calc = MarketImpactCalculator()
mi_calc.get_updated_price = MagicMock(return_value=1.5)
network = AssetFundNetwork.AssetFundsNetwork(funds={
'f1': f1,
'f2': f2
},
assets={
'a1': a1,
'a2': a2
},
mi_calc=mi_calc,
limit_trade_step=False)
network.submit_sell_orders([Sell('a2', 2)])
network.submit_buy_orders([Buy('a1', 2)])
log = network.simulate_trade()
calls = [call(2, a2, -1), call(2, a1, 1)]
mi_calc.get_updated_price.assert_has_calls(calls, any_order=True)
self.assertDictEqual({'a1': '1->1.5', 'a2': '2->1.5'}, log)
self.assertFalse(network.buy_orders)
self.assertFalse(network.sell_orders)
def dont_test_get_possible_defenses(self):
a1 = AssetFundNetwork.Asset(price=1, daily_volume=10, symbol='a1')
a2 = AssetFundNetwork.Asset(price=2, daily_volume=4, symbol='a2')
a3 = AssetFundNetwork.Asset(price=7, daily_volume=2, symbol='a3')
f1 = Fund('f1', {'a1': 10, 'a2': 10, 'a3': 10}, 100, 1, 1)
f2 = Fund('f2', {'a1': 10}, 100, 1, 1)
SysConfig.set("ORDER_SIZES", [0.5, 1])
network = AssetFundNetwork.AssetFundsNetwork(
funds={
'f1': f1,
'f2': f2
},
assets={
'a1': a1,
'a2': a2,
'a3': a3
},
mi_calc=MockMarketImpactTestCalculator())
actual_orders = get_possible_defenses(network, 10)
expected_orders = []
expected_orders.append(([Buy('a1', 5)], 5))
expected_orders.append(([Buy('a1', 10)], 10))
expected_orders.append(([Buy('a2', 2)], 4))
expected_orders.append(([Buy('a2', 4)], 8))
expected_orders.append(([Buy('a3', 1)], 7))
expected_orders.append(([Buy('a1', 5), Buy('a2', 2)], 9))
expected_orders.append(([], 0))
self.assertEqual(actual_orders, expected_orders)
def test_filter_from_history(self):
sell_action1 = Attack([Sell('a1', 1), Sell('a2', 1)], 10)
sell_action2 = Attack([Sell('a1', 1), Sell('a3', 1)], 10)
buy_action1 = Attack([Buy('a1', 1), Buy('a2', 1)], 10)
buy_action2 = Attack([Buy('a2', 1)], 10)
history = {BUY: {'a1': 2}, SELL: {'a1': 1, 'a2': 2}}
self.assertTrue(
ActionsManager._ActionsManager__filter_from_history(
sell_action1, history, SELL))
self.assertFalse(
ActionsManager._ActionsManager__filter_from_history(
sell_action2, history, SELL))
self.assertTrue(
ActionsManager._ActionsManager__filter_from_history(
buy_action1, history, BUY))
self.assertFalse(
ActionsManager._ActionsManager__filter_from_history(
buy_action2, history, BUY))
def test_get_defenses_in_budget(self):
a1 = AssetFundNetwork.Asset(price=1, daily_volume=100, symbol='a1')
a2 = AssetFundNetwork.Asset(price=2, daily_volume=200, symbol='a2')
a3 = AssetFundNetwork.Asset(price=2, daily_volume=300, symbol='a3')
assets = {'a1': a1, 'a2': a2, 'a3': a3}
single_asset_orders = [Buy('a1', 10), Buy('a2', 20), Buy('a3', 30)]
expected_defenses = [([Buy('a1', 10)], 10), ([Buy('a2', 20)], 40),
([Buy('a3', 30)], 60),
([Buy('a1', 10), Buy('a2', 20)], 50)]
actual_defenses = ActionsManager._ActionsManager__get_defenses_in_budget(
assets, single_asset_orders, lambda a: a.price, 60)
self.assertListEqual(expected_defenses, actual_defenses)
def test_get_all_attacks(self):
a1 = AssetFundNetwork.Asset(price=1, daily_volume=100, symbol='a1')
a2 = AssetFundNetwork.Asset(price=2, daily_volume=200, symbol='a2')
a3 = AssetFundNetwork.Asset(price=3, daily_volume=300, symbol='a3')
assets = {'a1': a1, 'a2': a2, 'a3': a3}
expected_attacks = [
Attack([Sell('a1', 10)], 10),
Attack([Sell('a2', 20)], 40),
Attack([Sell('a3', 30)], 90),
Attack([Sell('a1', 10), Buy('a2', 20)], 50),
Attack([Sell('a1', 10), Buy('a3', 30)], 100),
Attack([Sell('a2', 20), Buy('a3', 30)], 130),
Attack(
[Sell('a1', 10), Sell('a2', 20),
Buy('a3', 30)], 140),
Attack([], 0)
]
mgr = ActionsManager(assets, 0.1)
actual_attacks = mgr._ActionsManager__get_all_attacks(assets, 3)
actual_attacks.sort(key=lambda a: a.cost)
expected_attacks.sort(key=lambda a: a.cost)
self.assertListEqual(actual_attacks, expected_attacks)
def test_simulate_trade_limit_trade_step(self):
a1 = AssetFundNetwork.Asset(price=1, daily_volume=1000, symbol='a1')
f1 = Fund('f1', {'a1': 10}, 100, 1, 1)
mi_calc = MarketImpactCalculator()
mi_calc.get_updated_price = MagicMock(return_value=1.5)
network = AssetFundNetwork.AssetFundsNetwork(funds={'f1': f1},
assets={'a1': a1},
mi_calc=mi_calc)
SysConfig.set('TIME_STEP_MINUTES', 1)
SysConfig.set('DAILY_PORTION_PER_MIN', 0.001)
network.submit_buy_orders([Buy('a1', 2)])
log = network.simulate_trade()
self.assertDictEqual({'a1': '1->1.5'}, log)
mi_calc.get_updated_price.assert_called_once_with(1, a1, 1)
self.assertEqual(network.buy_orders['a1'], 1)
def test_reset_books(self):
a1 = AssetFundNetwork.Asset(price=1, daily_volume=1, symbol='a1')
a2 = AssetFundNetwork.Asset(price=2, daily_volume=1, symbol='a2')
f1 = Fund('f1', {'a1': 10}, 100, 1, 1)
f2 = Fund('f2', {'a2': 10}, 100, 1, 1)
network = AssetFundNetwork.AssetFundsNetwork(
funds={
'f1': f1,
'f2': f2
},
assets={
'a1': a1,
'a2': a2
},
mi_calc=MockMarketImpactTestCalculator(),
limit_trade_step=True)
network.submit_buy_orders([Buy('a1', 2)])
network.submit_sell_orders([Sell('a1', 2)])
self.assertTrue(network.sell_orders)
self.assertTrue(network.buy_orders)
network.reset_order_books()
self.assertFalse(network.sell_orders)
self.assertFalse(network.buy_orders)
def dont_test_get_possible_defenses_unit(self):
a1 = AssetFundNetwork.Asset(price=1, daily_volume=100, symbol='a1')
a2 = AssetFundNetwork.Asset(price=2, daily_volume=100, symbol='a2')
a3 = AssetFundNetwork.Asset(price=3, daily_volume=100, symbol='a3')
a4 = AssetFundNetwork.Asset(price=1, daily_volume=100, symbol='a4')
f1 = Fund('f1', {'a1': 10, 'a2': 10, 'a3': 10}, 100, 1, 1)
f2 = Fund('f2', {'a4': 10}, 100, 1, 1)
network = AssetFundNetwork.AssetFundsNetwork(
funds={
'f1': f1,
'f2': f2
},
assets={
'a1': a1,
'a2': a2,
'a3': a3,
'a4': a4
},
mi_calc=MockMarketImpactTestCalculator())
actions_mgr = ActionsManager(network.assets, 0.1)
actions_mgr.funds_under_risk = MagicMock(return_value=['f1'])
actions_mgr.get_single_orders = MagicMock(
return_value=[Buy('a1', 10),
Buy('a2', 10),
Buy('a3', 10)])
expected_order_set = [[Buy('a1', 10)]]
actions_mgr.get_defenses_in_budget = MagicMock(
return_value=[(expected_order_set, 10)])
history = {BUY: {'a1': 2}, SELL: {'a1': 1, 'a2': 2}}
budget = 60
actual_defenses = actions_mgr.get_possible_defenses(
network, budget, history)
self.assertListEqual(actual_defenses, [(expected_order_set, 10),
([], 0)])
actions_mgr.funds_under_risk.assert_called_once_with(network)
defense_assets = {
'a2': a2,
'a1': a1,
'a3': a3,
}
actions_mgr.get_single_orders.assert_called_once_with(defense_assets)
filtered_defenses = [Buy('a2', 10), Buy('a3', 10)]
actions_mgr.get_defenses_in_budget.assert_called_once_with(
defense_assets, filtered_defenses)
def test_market_impact_buy_sqrt(self):
calc = SqrtMarketImpactCalculator(0.5)
order = Buy('a1', 10)
a = Asset(price=2, daily_volume=1000, volatility=1.5, symbol='a1')
mi = calc.get_market_impact(order, a, )
npt.assert_almost_equal(0.075, mi, decimal=4)
def test_market_impact_buy_order_exp(self):
calc = ExponentialMarketImpactCalculator(2)
order = Buy('a1', 10)
a = Asset(price=2, daily_volume=100, volatility=1.5, symbol='a1')
mi = calc.get_market_impact(order, a)
npt.assert_almost_equal(1.2214, mi, decimal=4)
def gen_tree(self, ):
sell = str([Sell('a1', 50)])
buy = str([Buy('a1', 50)])
nope = str([])
sell_actions = [nope, sell]
buy_actions = [nope, buy]
root = {
'name': 'root',
'to_move': CHANCE,
'actions': ['40', '30'],
'inf_set': '.',
'terminal': False
}
price_drop_log = "{'a1': '1->0.6'}"
price_bump_log = "{'a1': '1->1.5'}"
price_bump_log_06 = "{'a1': '0.6->1.5'}"
empty_log = '{}'
node_1_0 = self.fill_dict(name='node_1_0',
to_move=ATTACKER,
actions=sell_actions,
history_assets_dict={
BUY: {},
SELL: {}
},
budget=Budget(attacker=50, defender=50),
actions_history={
BUY: [],
SELL: [],
SIM_TRADE: []
},
inf_set='.50.A_HISTORY:[]')
node_1_0_0 = self.fill_dict(name='node_1_0_0',
to_move=DEFENDER,
actions=buy_actions,
history_assets_dict={
BUY: {},
SELL: {
'a1': 1
}
},
budget=Budget(attacker=0, defender=50),
actions_history={
BUY: [],
SELL: [sell],
SIM_TRADE: []
},
inf_set='.50.D_HISTORY:[]')
node_1_0_1 = self.fill_dict(name='node_1_0_1',
to_move=DEFENDER,
actions=buy_actions,
history_assets_dict={
BUY: {},
SELL: {}
},
budget=Budget(attacker=50, defender=50),
actions_history={
BUY: [],
SELL: [nope],
SIM_TRADE: []
},
inf_set='.50.D_HISTORY:[]')
node_1_0_1_0 = self.fill_dict(
name='node_1_0_1_0',
to_move=MARKET,
actions=[],
history_assets_dict={
BUY: {},
SELL: {}
},
budget=Budget(attacker=50, defender=50),
actions_history={
BUY: [nope],
SELL: [nope],
SIM_TRADE: []
},
inf_set=".MARKET_HISTORY:[].BUY:{}.SELL:{}",
terminal=True,
eval=0)
node_1_0_1_1 = self.fill_dict(
name='node_1_0_1_1',
to_move=MARKET,
actions=[price_bump_log],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {}
},
budget=Budget(attacker=50, defender=0),
actions_history={
BUY: [buy],
SELL: [nope],
SIM_TRADE: []
},
inf_set=".MARKET_HISTORY:[].BUY:{'a1': 50}.SELL:{}")
node_1_0_1_1_0 = self.fill_dict(
name='node_1_0_1_1_0',
to_move=ATTACKER,
actions=['[]'],
history_assets_dict={
BUY: {},
SELL: {
'a1': 1
}
},
budget=Budget(attacker=0, defender=50),
actions_history={
BUY: [nope, price_drop_log],
SELL: [sell, price_drop_log],
SIM_TRADE: [price_drop_log]
},
inf_set=".0.A_HISTORY:['[Sell a1 50]', \"{'a1': '1->0.6'}\"]")
node_1_0_1_1_0_0 = self.fill_dict(
name='node_1_0_1_1_0_0',
to_move=DEFENDER,
actions=buy_actions,
history_assets_dict={
BUY: {},
SELL: {
'a1': 1
}
},
budget=Budget(attacker=0, defender=50),
actions_history={
BUY: [nope, price_drop_log],
SELL: [sell, price_drop_log, nope],
SIM_TRADE: [price_drop_log]
},
inf_set=".50.D_HISTORY:['[]', \"{'a1': '1->0.6'}\"]")
node_1_0_1_1_0_0_0 = self.fill_dict(
name='node_1_0_1_1_0_0_0',
to_move=MARKET,
actions=[],
history_assets_dict={
BUY: {},
SELL: {
'a1': 1
}
},
budget=Budget(attacker=0, defender=50),
actions_history={
BUY: [nope, price_drop_log, nope],
SELL: [sell, price_drop_log, nope],
SIM_TRADE: [price_drop_log]
},
inf_set=".MARKET_HISTORY:[\"{'a1': '1->0.6'}\"].BUY:{}.SELL:{}",
terminal=True,
eval=0)
node_1_0_0_0 = self.fill_dict(
name='node_1_0_0_0',
to_move=MARKET,
actions=[empty_log],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {
'a1': 1
}
},
budget=Budget(attacker=0, defender=0),
actions_history={
BUY: [buy],
SELL: [sell],
SIM_TRADE: []
},
inf_set=".MARKET_HISTORY:[].BUY:{'a1': 50}.SELL:{'a1': 50}")
node_1_0_0_1 = self.fill_dict(
name='node_1_0_0_1',
to_move=MARKET,
actions=[price_drop_log],
history_assets_dict={
BUY: {},
SELL: {
'a1': 1
}
},
budget=Budget(attacker=0, defender=50),
actions_history={
BUY: [nope],
SELL: [sell],
SIM_TRADE: []
},
inf_set=".MARKET_HISTORY:[].BUY:{}.SELL:{'a1': 50}")
node_1_0_0_1_0 = self.fill_dict(
name='node_1_0_0_1_0',
to_move=ATTACKER,
actions=['[]'],
history_assets_dict={
BUY: {},
SELL: {
'a1': 1
}
},
budget=Budget(attacker=0, defender=50),
actions_history={
BUY: [nope, price_drop_log],
SELL: [sell, price_drop_log],
SIM_TRADE: [price_drop_log]
},
inf_set=".0.A_HISTORY:['[Sell a1 50]', \"{'a1': '1->0.6'}\"]")
node_1_0_0_1_0_0 = self.fill_dict(
name='node_1_0_0_1_0_0',
to_move=DEFENDER,
actions=buy_actions,
history_assets_dict={
BUY: {},
SELL: {
'a1': 1
}
},
budget=Budget(attacker=0, defender=50),
actions_history={
BUY: [nope, price_drop_log],
SELL: [sell, price_drop_log, nope],
SIM_TRADE: [price_drop_log]
},
inf_set=".50.D_HISTORY:['[]', \"{'a1': '1->0.6'}\"]")
node_1_0_0_1_0_0_0 = self.fill_dict(
name='node_1_0_0_1_0_0_0',
to_move=MARKET,
actions=[],
history_assets_dict={
BUY: {},
SELL: {
'a1': 1
}
},
budget=Budget(attacker=0, defender=50),
actions_history={
BUY: [nope, price_drop_log, nope],
SELL: [sell, price_drop_log, nope],
SIM_TRADE: [price_drop_log]
},
inf_set=".MARKET_HISTORY:[\"{'a1': '1->0.6'}\"].BUY:{}.SELL:{}",
terminal=True,
eval=-1)
node_1_0_0_1_0_0_1 = self.fill_dict(
name='node_1_0_0_1_0_0_1',
to_move=MARKET,
actions=["{'a1': '0.6->1.5'}"],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {
'a1': 1
}
},
budget=Budget(attacker=0, defender=20),
actions_history={
BUY: [nope, price_drop_log, buy],
SELL: [sell, price_drop_log, nope],
SIM_TRADE: [price_drop_log]
},
inf_set=
".MARKET_HISTORY:[\"{'a1': '1->0.6'}\"].BUY:{'a1': 50}.SELL:{}")
node_1_0_0_1_0_0_1_0 = self.fill_dict(
name='node_1_0_0_1_0_0_1_0',
to_move=ATTACKER,
actions=['[]'],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {
'a1': 1
}
},
budget=Budget(attacker=0, defender=20),
actions_history={
BUY: [nope, price_drop_log, buy, price_bump_log_06],
SELL: [sell, price_drop_log, nope, price_bump_log_06],
SIM_TRADE: [price_drop_log, price_bump_log_06]
},
inf_set=
".0.A_HISTORY:['[Sell a1 50]', \"{'a1': '1->0.6'}\", '[]', \"{'a1': '0.6->1.5'}\"]"
)
node_1_0_0_1_0_0_1_0_0 = self.fill_dict(
name='node_1_0_0_1_0_0_1_0_0',
to_move=DEFENDER,
actions=['[]'],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {
'a1': 1
}
},
budget=Budget(attacker=0, defender=20),
actions_history={
BUY: [nope, price_drop_log, buy, price_bump_log_06],
SELL: [sell, price_drop_log, nope, price_bump_log_06, nope],
SIM_TRADE: [price_drop_log, price_bump_log_06]
},
inf_set=
".20.0.D_HISTORY:['[]', \"{'a1': '1->0.6'}\", '[Buy a1 50]', \"{'a1': '0.6->1.5'}\"]"
)
node_1_0_0_1_0_0_1_0_0_0 = self.fill_dict(
name='node_1_0_0_1_0_0_1_0_0_0',
to_move=MARKET,
actions=[],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {
'a1': 1
}
},
budget=Budget(attacker=0, defender=20),
actions_history={
BUY: [nope, price_drop_log, buy, price_bump_log_06, nope],
SELL: [sell, price_drop_log, nope, price_bump_log_06, nope],
SIM_TRADE: [price_drop_log, price_bump_log_06]
},
inf_set=
".MARKET_HISTORY:[\"{'a1': '1->0.6'}\", \"{'a1': '0.6->1.5'}\"].BUY:{}.SELL:{}",
terminal=True,
eval=0)
node_1_0_0_0_0 = self.fill_dict(
name='node_1_0_0_0_0',
to_move=ATTACKER,
actions=['[]'],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {
'a1': 1
}
},
budget=Budget(attacker=0, defender=0),
actions_history={
BUY: [buy, empty_log],
SELL: [sell, empty_log],
SIM_TRADE: [empty_log]
},
inf_set=".0.A_HISTORY:['[Sell a1 50]', '{}']")
node_1_0_0_0_0_0 = self.fill_dict(
name='node_1_0_0_0_0_0',
to_move=DEFENDER,
actions=['[]'],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {
'a1': 1
}
},
budget=Budget(attacker=0, defender=0),
actions_history={
BUY: [buy, empty_log],
SELL: [sell, empty_log, nope],
SIM_TRADE: [empty_log]
},
inf_set=".0.D_HISTORY:['[Buy a1 50]', '{}']")
node_1_0_0_0_0_0_0 = self.fill_dict(
name='node_1_0_0_0_0_0_0',
to_move=MARKET,
actions=[],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {
'a1': 1
}
},
budget=Budget(attacker=0, defender=0),
actions_history={
BUY: [buy, empty_log, nope],
SELL: [sell, empty_log, nope],
SIM_TRADE: [empty_log]
},
inf_set=".MARKET_HISTORY:['{}'].BUY:{}.SELL:{}",
terminal=True,
eval=0)
###########
node_1_1 = self.fill_dict(name='node_1_1',
to_move=ATTACKER,
actions=[nope],
history_assets_dict={
BUY: {},
SELL: {}
},
budget=Budget(attacker=30, defender=50),
actions_history={
BUY: [],
SELL: [],
SIM_TRADE: []
},
inf_set='.30.A_HISTORY:[]')
node_1_1_0 = self.fill_dict(name='node_1_1_0',
to_move=DEFENDER,
actions=buy_actions,
history_assets_dict={
BUY: {},
SELL: {}
},
budget=Budget(attacker=30, defender=50),
actions_history={
BUY: [],
SELL: [nope],
SIM_TRADE: []
},
inf_set='.50.D_HISTORY:[]')
node_1_1_0_0 = self.fill_dict(
name='node_1_1_0_0',
to_move=MARKET,
actions=[price_bump_log],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {}
},
budget=Budget(attacker=30, defender=0),
actions_history={
BUY: [buy],
SELL: [nope],
SIM_TRADE: []
},
inf_set=".MARKET_HISTORY:[].BUY:{'a1': 50}.SELL:{}")
node_1_1_0_0_0 = self.fill_dict(
name='node_1_1_0_0_0',
to_move=ATTACKER,
actions=[nope],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {}
},
budget=Budget(attacker=30, defender=0),
actions_history={
BUY: [buy, price_bump_log],
SELL: [nope, price_bump_log],
SIM_TRADE: [price_bump_log]
},
inf_set=".30.A_HISTORY:['[]', \"{'a1': '1->1.5'}\"]")
node_1_1_0_0_0_0 = self.fill_dict(
name='node_1_1_0_0_0_0',
to_move=DEFENDER,
actions=[nope],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {}
},
budget=Budget(attacker=30, defender=0),
actions_history={
BUY: [buy, price_bump_log],
SELL: [nope, price_bump_log, nope],
SIM_TRADE: [price_bump_log]
},
inf_set=".0.D_HISTORY:['[Buy a1 50]', \"{'a1': '1->1.5'}\"]")
node_1_1_0_0_0_0_0 = self.fill_dict(
name='node_1_1_0_0_0_0_0',
to_move=MARKET,
actions=[],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {}
},
budget=Budget(attacker=30, defender=0),
actions_history={
BUY: [buy, price_bump_log, nope],
SELL: [nope, price_bump_log, nope],
SIM_TRADE: [price_bump_log]
},
terminal=True,
eval=0,
inf_set=".MARKET_HISTORY:[\"{'a1': '1->1.5'}\"].BUY:{}.SELL:{}")
node_1_1_0_1 = self.fill_dict(
name='node_1_1_0_1',
to_move=MARKET,
actions=[],
history_assets_dict={
BUY: {},
SELL: {}
},
budget=Budget(attacker=30, defender=50),
actions_history={
BUY: [nope],
SELL: [nope],
SIM_TRADE: []
},
inf_set=".MARKET_HISTORY:[].BUY:{}.SELL:{}",
terminal=True,
eval=0)
##########
root['children'] = {'50': node_1_0, '30': node_1_1}
node_1_0['children'] = {sell: node_1_0_0, nope: node_1_0_1}
node_1_0_0['children'] = {buy: node_1_0_0_0, nope: node_1_0_0_1}
node_1_0_1['children'] = {nope: node_1_0_1_0, buy: node_1_0_1_1}
node_1_0_0_0['children'] = {empty_log: node_1_0_0_0_0}
node_1_0_0_1['children'] = {price_drop_log: node_1_0_0_1_0}
node_1_0_0_0_0['children'] = {nope: node_1_0_0_0_0_0}
node_1_0_0_0_0_0['children'] = {nope: node_1_0_0_0_0_0_0}
node_1_0_0_0_0_0_0['children'] = {}
node_1_0_1_0['children'] = {}
node_1_0_1_1['children'] = {price_bump_log: node_1_0_1_1_0}
node_1_0_0_1_0['children'] = {nope: node_1_0_0_1_0_0}
node_1_1['children'] = {nope: node_1_1_0}
node_1_1_0['children'] = {buy: node_1_1_0_0, nope: node_1_1_0_1}
node_1_1_0_0['children'] = {price_bump_log: node_1_1_0_0_0}
node_1_1_0_0_0['children'] = {nope: node_1_1_0_0_0_0}
node_1_1_0_0_0_0['children'] = {nope: node_1_1_0_0_0_0_0}
node_1_1_0_0_0_0_0['children'] = {}
node_1_1_0_1['children'] = {}
node_1_0_0_1_0_0['children'] = {
nope: node_1_0_0_1_0_0_0,
buy: node_1_0_0_1_0_0_1
}
node_1_0_0_1_0_0_0['children'] = {}
node_1_0_0_1_0_0_1['children'] = {
price_bump_log_06: node_1_0_0_1_0_0_1_0
}
node_1_0_0_1_0_0_1_0['children'] = {nope: node_1_0_0_1_0_0_1_0_0}
node_1_0_0_1_0_0_1_0_0['children'] = {nope: node_1_0_0_1_0_0_1_0_0_0}
node_1_0_0_1_0_0_1_0_0_0['children'] = {}
return root
def gen_buy_order(asset, size):
return Buy(asset.symbol, int(floor(size * asset.daily_volume)))
def test_updated_price_buy_sqrt(self):
calc = SqrtMarketImpactCalculator(0.5)
order = Buy('a1', 10)
a = Asset(price=2, daily_volume=1000, volatility=1.5, symbol='a1')
mi = calc.get_updated_price(order.num_shares, a, 1)
npt.assert_almost_equal(2.075, mi, decimal=4)
def gen_tree(self, ):
sell_order = Sell('a1', 50)
sell = str([sell_order])
buy = str([Buy('a1', 50)])
nope = str([])
buy_actions = [nope, buy]
root = {
'tree_size': 8,
'to_move': CHANCE,
'actions': ['p1', 'p2'],
'inf_set': '.',
'terminal': False
}
price_drop_log = "{'a1': '1->0.5'}"
empty_log = '{}'
node_1_0 = self.fill_dict(tree_size=6,
to_move=ATTACKER,
actions=[sell],
history_assets_dict={
BUY: {},
SELL: {}
},
players_info=PlayersHiddenInfo(
attacker_attack=[sell_order],
attacker_pid='p2',
defender_budget=50),
actions_history={
BUY: [],
SELL: [],
SIM_TRADE: []
},
inf_set='.p2.A_HISTORY:[]',
terminal=False,
eval=None)
node_1_0_0 = self.fill_dict(tree_size=5,
to_move=DEFENDER,
actions=buy_actions,
history_assets_dict={
BUY: {},
SELL: {
'a1': 1
}
},
players_info=PlayersHiddenInfo(
attacker_attack=[],
attacker_pid='p2',
defender_budget=50),
actions_history={
BUY: [],
SELL: [sell],
SIM_TRADE: []
},
inf_set='.50.D_HISTORY:[]',
terminal=False,
eval=None)
node_1_0_0_0 = self.fill_dict(
tree_size=2,
to_move=MARKET,
actions=[empty_log],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {
'a1': 1
}
},
players_info=PlayersHiddenInfo(attacker_attack=[],
attacker_pid='p2',
defender_budget=0),
actions_history={
BUY: [buy],
SELL: [sell],
SIM_TRADE: []
},
inf_set=".MARKET_HISTORY:[].BUY:{'a1': 50}.SELL:{'a1': 50}",
terminal=False,
eval=None)
node_1_0_0_1 = self.fill_dict(
tree_size=2,
to_move=MARKET,
actions=[price_drop_log],
history_assets_dict={
BUY: {},
SELL: {
'a1': 1
}
},
players_info=PlayersHiddenInfo(attacker_attack=[],
attacker_pid='p2',
defender_budget=50),
actions_history={
BUY: [nope],
SELL: [sell],
SIM_TRADE: []
},
inf_set=".MARKET_HISTORY:[].BUY:{}.SELL:{'a1': 50}",
terminal=False,
eval=None)
node_1_0_0_0_0 = self.fill_dict(
tree_size=1,
terminal=True,
eval=0,
to_move=ATTACKER,
actions=[],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {
'a1': 1
}
},
players_info=PlayersHiddenInfo(attacker_attack=[],
attacker_pid='p2',
defender_budget=0),
actions_history={
BUY: [buy, empty_log],
SELL: [sell, empty_log],
SIM_TRADE: [empty_log]
},
inf_set=".p2.A_HISTORY:['[Sell a1 50]', '{}']")
node_1_0_0_1_0 = self.fill_dict(
tree_size=1,
terminal=True,
eval=-1,
to_move=ATTACKER,
actions=[],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {
'a1': 1
}
},
players_info=PlayersHiddenInfo(attacker_attack=[],
attacker_pid='p2',
defender_budget=50),
actions_history={
BUY: [nope, price_drop_log],
SELL: [sell, price_drop_log],
SIM_TRADE: [price_drop_log]
},
inf_set=".p2.A_HISTORY:['[Sell a1 50]', \"{'a1': '1->0.5'}\"]")
###########
node_1_1 = self.fill_dict(tree_size=1,
terminal=True,
eval=0,
to_move=ATTACKER,
actions=[],
history_assets_dict={
BUY: {},
SELL: {}
},
players_info=PlayersHiddenInfo(
attacker_attack=[],
attacker_pid='p1',
defender_budget=50),
actions_history={
BUY: [],
SELL: [],
SIM_TRADE: []
},
inf_set='.p1.A_HISTORY:[]')
##########
root['children'] = {'p2': node_1_0, 'p1': node_1_1}
node_1_0['children'] = {sell: node_1_0_0}
node_1_0_0['children'] = {buy: node_1_0_0_0, nope: node_1_0_0_1}
node_1_0_0_0['children'] = {empty_log: node_1_0_0_0_0}
node_1_0_0_1['children'] = {price_drop_log: node_1_0_0_1_0}
node_1_0_0_0_0['children'] = {}
node_1_0_0_1_0['children'] = {}
node_1_1['children'] = {}
return root
def gen_tree(self, ):
buy = str([Buy('a1', 50)])
nope = str([])
buy_actions = [nope, buy]
root = {
'tree_size': 15,
'name': 'root',
'to_move': CHANCE,
'actions': ['40', '30'],
'inf_set': '.',
'terminal': False
}
price_bump_log = "{'a1': '1->1.5'}"
node_1_0 = self.fill_dict(tree_size=7,
name='node_1_0',
to_move=ATTACKER,
actions=[nope],
history_assets_dict={
BUY: {},
SELL: {}
},
budget=Budget(attacker=40, defender=50),
actions_history={
BUY: [],
SELL: [],
SIM_TRADE: []
},
inf_set='.40.A_HISTORY:[]')
node_1_0_0 = self.fill_dict(tree_size=6,
name='node_1_0_0',
to_move=DEFENDER,
actions=buy_actions,
history_assets_dict={
BUY: {},
SELL: {}
},
budget=Budget(attacker=40, defender=50),
actions_history={
BUY: [],
SELL: [nope],
SIM_TRADE: []
},
inf_set='.50.D_HISTORY:[]')
node_1_0_0_0 = self.fill_dict(
tree_size=4,
name='node_1_0_0_0',
to_move=MARKET,
actions=[price_bump_log],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {}
},
budget=Budget(attacker=40, defender=0),
actions_history={
BUY: [buy],
SELL: [nope],
SIM_TRADE: []
},
inf_set=".MARKET_HISTORY:[].BUY:{'a1': 50}.SELL:{}")
node_1_0_0_0_0 = self.fill_dict(
tree_size=3,
name='node_1_0_0_0_0',
to_move=ATTACKER,
actions=[nope],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {}
},
budget=Budget(attacker=40, defender=0),
actions_history={
BUY: [buy, price_bump_log],
SELL: [nope, price_bump_log],
SIM_TRADE: [price_bump_log]
},
inf_set=".40.A_HISTORY:['[]', \"{'a1': '1->1.5'}\"]")
node_1_0_0_0_0_0 = self.fill_dict(
tree_size=2,
name='node_1_0_0_0_0_0',
to_move=DEFENDER,
actions=[nope],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {}
},
budget=Budget(attacker=40, defender=0),
actions_history={
BUY: [buy, price_bump_log],
SELL: [nope, price_bump_log, nope],
SIM_TRADE: [price_bump_log]
},
inf_set=".0.D_HISTORY:['[Buy a1 50]', \"{'a1': '1->1.5'}\"]")
node_1_0_0_0_0_0_0 = self.fill_dict(
tree_size=1,
name='node_1_0_0_0_0_0_0',
to_move=MARKET,
actions=[],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {}
},
budget=Budget(attacker=40, defender=0),
actions_history={
BUY: [buy, price_bump_log, nope],
SELL: [nope, price_bump_log, nope],
SIM_TRADE: [price_bump_log]
},
terminal=True,
eval=0,
inf_set=".MARKET_HISTORY:[\"{'a1': '1->1.5'}\"].BUY:{}.SELL:{}")
node_1_0_0_1 = self.fill_dict(
tree_size=1,
name='node_1_0_0_1',
to_move=MARKET,
actions=[],
history_assets_dict={
BUY: {},
SELL: {}
},
budget=Budget(attacker=40, defender=50),
actions_history={
BUY: [nope],
SELL: [nope],
SIM_TRADE: []
},
inf_set=".MARKET_HISTORY:[].BUY:{}.SELL:{}",
terminal=True,
eval=0)
###########
node_1_1 = self.fill_dict(tree_size=7,
name='node_1_1',
to_move=ATTACKER,
actions=[nope],
history_assets_dict={
BUY: {},
SELL: {}
},
budget=Budget(attacker=30, defender=50),
actions_history={
BUY: [],
SELL: [],
SIM_TRADE: []
},
inf_set='.30.A_HISTORY:[]')
node_1_1_0 = self.fill_dict(tree_size=6,
name='node_1_1_0',
to_move=DEFENDER,
actions=buy_actions,
history_assets_dict={
BUY: {},
SELL: {}
},
budget=Budget(attacker=30, defender=50),
actions_history={
BUY: [],
SELL: [nope],
SIM_TRADE: []
},
inf_set='.50.D_HISTORY:[]')
node_1_1_0_0 = self.fill_dict(
tree_size=4,
name='node_1_1_0_0',
to_move=MARKET,
actions=[price_bump_log],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {}
},
budget=Budget(attacker=30, defender=0),
actions_history={
BUY: [buy],
SELL: [nope],
SIM_TRADE: []
},
inf_set=".MARKET_HISTORY:[].BUY:{'a1': 50}.SELL:{}")
node_1_1_0_0_0 = self.fill_dict(
tree_size=3,
name='node_1_1_0_0_0',
to_move=ATTACKER,
actions=[nope],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {}
},
budget=Budget(attacker=30, defender=0),
actions_history={
BUY: [buy, price_bump_log],
SELL: [nope, price_bump_log],
SIM_TRADE: [price_bump_log]
},
inf_set=".30.A_HISTORY:['[]', \"{'a1': '1->1.5'}\"]")
node_1_1_0_0_0_0 = self.fill_dict(
tree_size=2,
name='node_1_1_0_0_0_0',
to_move=DEFENDER,
actions=[nope],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {}
},
budget=Budget(attacker=30, defender=0),
actions_history={
BUY: [buy, price_bump_log],
SELL: [nope, price_bump_log, nope],
SIM_TRADE: [price_bump_log]
},
inf_set=".0.D_HISTORY:['[Buy a1 50]', \"{'a1': '1->1.5'}\"]")
node_1_1_0_0_0_0_0 = self.fill_dict(
tree_size=1,
name='node_1_1_0_0_0_0_0',
to_move=MARKET,
actions=[],
history_assets_dict={
BUY: {
'a1': 1
},
SELL: {}
},
budget=Budget(attacker=30, defender=0),
actions_history={
BUY: [buy, price_bump_log, nope],
SELL: [nope, price_bump_log, nope],
SIM_TRADE: [price_bump_log]
},
terminal=True,
eval=0,
inf_set=".MARKET_HISTORY:[\"{'a1': '1->1.5'}\"].BUY:{}.SELL:{}")
node_1_1_0_1 = self.fill_dict(
tree_size=1,
name='node_1_1_0_1',
to_move=MARKET,
actions=[],
history_assets_dict={
BUY: {},
SELL: {}
},
budget=Budget(attacker=30, defender=50),
actions_history={
BUY: [nope],
SELL: [nope],
SIM_TRADE: []
},
inf_set=".MARKET_HISTORY:[].BUY:{}.SELL:{}",
terminal=True,
eval=0)
##########
root['children'] = {'40': node_1_0, '30': node_1_1}
node_1_0['children'] = {nope: node_1_0_0}
node_1_0_0['children'] = {buy: node_1_0_0_0, nope: node_1_0_0_1}
node_1_0_0_0['children'] = {price_bump_log: node_1_0_0_0_0}
node_1_0_0_0_0['children'] = {nope: node_1_0_0_0_0_0}
node_1_0_0_0_0_0['children'] = {nope: node_1_0_0_0_0_0_0}
node_1_0_0_0_0_0_0['children'] = {}
node_1_0_0_1['children'] = {}
node_1_1['children'] = {nope: node_1_1_0}
node_1_1_0['children'] = {buy: node_1_1_0_0, nope: node_1_1_0_1}
node_1_1_0_0['children'] = {price_bump_log: node_1_1_0_0_0}
node_1_1_0_0_0['children'] = {nope: node_1_1_0_0_0_0}
node_1_1_0_0_0_0['children'] = {nope: node_1_1_0_0_0_0_0}
node_1_1_0_0_0_0_0['children'] = {}
node_1_1_0_1['children'] = {}
return root